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llvm / llvm-project / llvm / 5c4b039b3e40c0c4f3ccfbbe875ca6a406e28206 / . / lib / Transforms / Vectorize / SLPVectorizer.cpp
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//===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This pass implements the Bottom Up SLP vectorizer. It detects consecutive
// stores that can be put together into vector-stores. Next, it attempts to
// construct vectorizable tree using the use-def chains. If a profitable tree
// was found, the SLP vectorizer performs vectorization on the tree.
//
// The pass is inspired by the work described in the paper:
// "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks.
//
//===----------------------------------------------------------------------===//
#include "llvm/Transforms/Vectorize/SLPVectorizer.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/DenseSet.h"
#include "llvm/ADT/PostOrderIterator.h"
#include "llvm/ADT/PriorityQueue.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/SetOperations.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/SmallBitVector.h"
#include "llvm/ADT/SmallPtrSet.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/SmallString.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/ADT/iterator.h"
#include "llvm/ADT/iterator_range.h"
#include "llvm/Analysis/AliasAnalysis.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/CodeMetrics.h"
#include "llvm/Analysis/DemandedBits.h"
#include "llvm/Analysis/GlobalsModRef.h"
#include "llvm/Analysis/IVDescriptors.h"
#include "llvm/Analysis/LoopAccessAnalysis.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/Analysis/MemoryLocation.h"
#include "llvm/Analysis/OptimizationRemarkEmitter.h"
#include "llvm/Analysis/ScalarEvolution.h"
#include "llvm/Analysis/ScalarEvolutionExpressions.h"
#include "llvm/Analysis/TargetLibraryInfo.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/Analysis/ValueTracking.h"
#include "llvm/Analysis/VectorUtils.h"
#include "llvm/IR/Attributes.h"
#include "llvm/IR/BasicBlock.h"
#include "llvm/IR/Constant.h"
#include "llvm/IR/Constants.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/DerivedTypes.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/Function.h"
#include "llvm/IR/IRBuilder.h"
#include "llvm/IR/InstrTypes.h"
#include "llvm/IR/Instruction.h"
#include "llvm/IR/Instructions.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/Intrinsics.h"
#include "llvm/IR/Module.h"
#include "llvm/IR/Operator.h"
#include "llvm/IR/PatternMatch.h"
#include "llvm/IR/Type.h"
#include "llvm/IR/Use.h"
#include "llvm/IR/User.h"
#include "llvm/IR/Value.h"
#include "llvm/IR/ValueHandle.h"
#ifdef EXPENSIVE_CHECKS
#include "llvm/IR/Verifier.h"
#endif
#include "llvm/Pass.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Compiler.h"
#include "llvm/Support/DOTGraphTraits.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/ErrorHandling.h"
#include "llvm/Support/GraphWriter.h"
#include "llvm/Support/InstructionCost.h"
#include "llvm/Support/KnownBits.h"
#include "llvm/Support/MathExtras.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Utils/InjectTLIMappings.h"
#include "llvm/Transforms/Utils/Local.h"
#include "llvm/Transforms/Utils/LoopUtils.h"
#include <algorithm>
#include <cassert>
#include <cstdint>
#include <iterator>
#include <memory>
#include <optional>
#include <set>
#include <string>
#include <tuple>
#include <utility>
#include <vector>
using namespace llvm;
using namespace llvm::PatternMatch;
using namespace slpvectorizer;
#define SV_NAME "slp-vectorizer"
#define DEBUG_TYPE "SLP"
STATISTIC(NumVectorInstructions, "Number of vector instructions generated");
cl::opt<bool> RunSLPVectorization("vectorize-slp", cl::init(true), cl::Hidden,
cl::desc("Run the SLP vectorization passes"));
static cl::opt<int>
SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden,
cl::desc("Only vectorize if you gain more than this "
"number "));
static cl::opt<bool>
ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden,
cl::desc("Attempt to vectorize horizontal reductions"));
static cl::opt<bool> ShouldStartVectorizeHorAtStore(
"slp-vectorize-hor-store", cl::init(false), cl::Hidden,
cl::desc(
"Attempt to vectorize horizontal reductions feeding into a store"));
// NOTE: If AllowHorRdxIdenityOptimization is true, the optimization will run
// even if we match a reduction but do not vectorize in the end.
static cl::opt<bool> AllowHorRdxIdenityOptimization(
"slp-optimize-identity-hor-reduction-ops", cl::init(true), cl::Hidden,
cl::desc("Allow optimization of original scalar identity operations on "
"matched horizontal reductions."));
static cl::opt<int>
MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden,
cl::desc("Attempt to vectorize for this register size in bits"));
static cl::opt<unsigned>
MaxVFOption("slp-max-vf", cl::init(0), cl::Hidden,
cl::desc("Maximum SLP vectorization factor (0=unlimited)"));
static cl::opt<int>
MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden,
cl::desc("Maximum depth of the lookup for consecutive stores."));
/// Limits the size of scheduling regions in a block.
/// It avoid long compile times for _very_ large blocks where vector
/// instructions are spread over a wide range.
/// This limit is way higher than needed by real-world functions.
static cl::opt<int>
ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden,
cl::desc("Limit the size of the SLP scheduling region per block"));
static cl::opt<int> MinVectorRegSizeOption(
"slp-min-reg-size", cl::init(128), cl::Hidden,
cl::desc("Attempt to vectorize for this register size in bits"));
static cl::opt<unsigned> RecursionMaxDepth(
"slp-recursion-max-depth", cl::init(12), cl::Hidden,
cl::desc("Limit the recursion depth when building a vectorizable tree"));
static cl::opt<unsigned> MinTreeSize(
"slp-min-tree-size", cl::init(3), cl::Hidden,
cl::desc("Only vectorize small trees if they are fully vectorizable"));
// The maximum depth that the look-ahead score heuristic will explore.
// The higher this value, the higher the compilation time overhead.
static cl::opt<int> LookAheadMaxDepth(
"slp-max-look-ahead-depth", cl::init(2), cl::Hidden,
cl::desc("The maximum look-ahead depth for operand reordering scores"));
// The maximum depth that the look-ahead score heuristic will explore
// when it probing among candidates for vectorization tree roots.
// The higher this value, the higher the compilation time overhead but unlike
// similar limit for operands ordering this is less frequently used, hence
// impact of higher value is less noticeable.
static cl::opt<int> RootLookAheadMaxDepth(
"slp-max-root-look-ahead-depth", cl::init(2), cl::Hidden,
cl::desc("The maximum look-ahead depth for searching best rooting option"));
static cl::opt<bool>
ViewSLPTree("view-slp-tree", cl::Hidden,
cl::desc("Display the SLP trees with Graphviz"));
// Limit the number of alias checks. The limit is chosen so that
// it has no negative effect on the llvm benchmarks.
static const unsigned AliasedCheckLimit = 10;
// Another limit for the alias checks: The maximum distance between load/store
// instructions where alias checks are done.
// This limit is useful for very large basic blocks.
static const unsigned MaxMemDepDistance = 160;
/// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling
/// regions to be handled.
static const int MinScheduleRegionSize = 16;
/// Predicate for the element types that the SLP vectorizer supports.
///
/// The most important thing to filter here are types which are invalid in LLVM
/// vectors. We also filter target specific types which have absolutely no
/// meaningful vectorization path such as x86_fp80 and ppc_f128. This just
/// avoids spending time checking the cost model and realizing that they will
/// be inevitably scalarized.
static bool isValidElementType(Type *Ty) {
return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() &&
!Ty->isPPC_FP128Ty();
}
/// \returns True if the value is a constant (but not globals/constant
/// expressions).
static bool isConstant(Value *V) {
return isa<Constant>(V) && !isa<ConstantExpr, GlobalValue>(V);
}
/// Checks if \p V is one of vector-like instructions, i.e. undef,
/// insertelement/extractelement with constant indices for fixed vector type or
/// extractvalue instruction.
static bool isVectorLikeInstWithConstOps(Value *V) {
if (!isa<InsertElementInst, ExtractElementInst>(V) &&
!isa<ExtractValueInst, UndefValue>(V))
return false;
auto *I = dyn_cast<Instruction>(V);
if (!I || isa<ExtractValueInst>(I))
return true;
if (!isa<FixedVectorType>(I->getOperand(0)->getType()))
return false;
if (isa<ExtractElementInst>(I))
return isConstant(I->getOperand(1));
assert(isa<InsertElementInst>(V) && "Expected only insertelement.");
return isConstant(I->getOperand(2));
}
/// \returns true if all of the instructions in \p VL are in the same block or
/// false otherwise.
static bool allSameBlock(ArrayRef<Value *> VL) {
Instruction *I0 = dyn_cast<Instruction>(VL[0]);
if (!I0)
return false;
if (all_of(VL, isVectorLikeInstWithConstOps))
return true;
BasicBlock *BB = I0->getParent();
for (int I = 1, E = VL.size(); I < E; I++) {
auto *II = dyn_cast<Instruction>(VL[I]);
if (!II)
return false;
if (BB != II->getParent())
return false;
}
return true;
}
/// \returns True if all of the values in \p VL are constants (but not
/// globals/constant expressions).
static bool allConstant(ArrayRef<Value *> VL) {
// Constant expressions and globals can't be vectorized like normal integer/FP
// constants.
return all_of(VL, isConstant);
}
/// \returns True if all of the values in \p VL are identical or some of them
/// are UndefValue.
static bool isSplat(ArrayRef<Value *> VL) {
Value *FirstNonUndef = nullptr;
for (Value *V : VL) {
if (isa<UndefValue>(V))
continue;
if (!FirstNonUndef) {
FirstNonUndef = V;
continue;
}
if (V != FirstNonUndef)
return false;
}
return FirstNonUndef != nullptr;
}
/// \returns True if \p I is commutative, handles CmpInst and BinaryOperator.
static bool isCommutative(Instruction *I) {
if (auto *Cmp = dyn_cast<CmpInst>(I))
return Cmp->isCommutative();
if (auto *BO = dyn_cast<BinaryOperator>(I))
return BO->isCommutative();
// TODO: This should check for generic Instruction::isCommutative(), but
// we need to confirm that the caller code correctly handles Intrinsics
// for example (does not have 2 operands).
return false;
}
/// \returns inserting index of InsertElement or InsertValue instruction,
/// using Offset as base offset for index.
static std::optional<unsigned> getInsertIndex(const Value *InsertInst,
unsigned Offset = 0) {
int Index = Offset;
if (const auto *IE = dyn_cast<InsertElementInst>(InsertInst)) {
const auto *VT = dyn_cast<FixedVectorType>(IE->getType());
if (!VT)
return std::nullopt;
const auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2));
if (!CI)
return std::nullopt;
if (CI->getValue().uge(VT->getNumElements()))
return std::nullopt;
Index *= VT->getNumElements();
Index += CI->getZExtValue();
return Index;
}
const auto *IV = cast<InsertValueInst>(InsertInst);
Type *CurrentType = IV->getType();
for (unsigned I : IV->indices()) {
if (const auto *ST = dyn_cast<StructType>(CurrentType)) {
Index *= ST->getNumElements();
CurrentType = ST->getElementType(I);
} else if (const auto *AT = dyn_cast<ArrayType>(CurrentType)) {
Index *= AT->getNumElements();
CurrentType = AT->getElementType();
} else {
return std::nullopt;
}
Index += I;
}
return Index;
}
namespace {
/// Specifies the way the mask should be analyzed for undefs/poisonous elements
/// in the shuffle mask.
enum class UseMask {
FirstArg, ///< The mask is expected to be for permutation of 1-2 vectors,
///< check for the mask elements for the first argument (mask
///< indices are in range [0:VF)).
SecondArg, ///< The mask is expected to be for permutation of 2 vectors, check
///< for the mask elements for the second argument (mask indices
///< are in range [VF:2*VF))
UndefsAsMask ///< Consider undef mask elements (-1) as placeholders for
///< future shuffle elements and mark them as ones as being used
///< in future. Non-undef elements are considered as unused since
///< they're already marked as used in the mask.
};
} // namespace
/// Prepares a use bitset for the given mask either for the first argument or
/// for the second.
static SmallBitVector buildUseMask(int VF, ArrayRef<int> Mask,
UseMask MaskArg) {
SmallBitVector UseMask(VF, true);
for (auto [Idx, Value] : enumerate(Mask)) {
if (Value == PoisonMaskElem) {
if (MaskArg == UseMask::UndefsAsMask)
UseMask.reset(Idx);
continue;
}
if (MaskArg == UseMask::FirstArg && Value < VF)
UseMask.reset(Value);
else if (MaskArg == UseMask::SecondArg && Value >= VF)
UseMask.reset(Value - VF);
}
return UseMask;
}
/// Checks if the given value is actually an undefined constant vector.
/// Also, if the \p UseMask is not empty, tries to check if the non-masked
/// elements actually mask the insertelement buildvector, if any.
template <bool IsPoisonOnly = false>
static SmallBitVector isUndefVector(const Value *V,
const SmallBitVector &UseMask = {}) {
SmallBitVector Res(UseMask.empty() ? 1 : UseMask.size(), true);
using T = std::conditional_t<IsPoisonOnly, PoisonValue, UndefValue>;
if (isa<T>(V))
return Res;
auto *VecTy = dyn_cast<FixedVectorType>(V->getType());
if (!VecTy)
return Res.reset();
auto *C = dyn_cast<Constant>(V);
if (!C) {
if (!UseMask.empty()) {
const Value *Base = V;
while (auto *II = dyn_cast<InsertElementInst>(Base)) {
Base = II->getOperand(0);
if (isa<T>(II->getOperand(1)))
continue;
std::optional<unsigned> Idx = getInsertIndex(II);
if (!Idx)
continue;
if (*Idx < UseMask.size() && !UseMask.test(*Idx))
Res.reset(*Idx);
}
// TODO: Add analysis for shuffles here too.
if (V == Base) {
Res.reset();
} else {
SmallBitVector SubMask(UseMask.size(), false);
Res &= isUndefVector<IsPoisonOnly>(Base, SubMask);
}
} else {
Res.reset();
}
return Res;
}
for (unsigned I = 0, E = VecTy->getNumElements(); I != E; ++I) {
if (Constant *Elem = C->getAggregateElement(I))
if (!isa<T>(Elem) &&
(UseMask.empty() || (I < UseMask.size() && !UseMask.test(I))))
Res.reset(I);
}
return Res;
}
/// Checks if the vector of instructions can be represented as a shuffle, like:
/// %x0 = extractelement <4 x i8> %x, i32 0
/// %x3 = extractelement <4 x i8> %x, i32 3
/// %y1 = extractelement <4 x i8> %y, i32 1
/// %y2 = extractelement <4 x i8> %y, i32 2
/// %x0x0 = mul i8 %x0, %x0
/// %x3x3 = mul i8 %x3, %x3
/// %y1y1 = mul i8 %y1, %y1
/// %y2y2 = mul i8 %y2, %y2
/// %ins1 = insertelement <4 x i8> poison, i8 %x0x0, i32 0
/// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1
/// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2
/// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3
/// ret <4 x i8> %ins4
/// can be transformed into:
/// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5,
/// i32 6>
/// %2 = mul <4 x i8> %1, %1
/// ret <4 x i8> %2
/// We convert this initially to something like:
/// %x0 = extractelement <4 x i8> %x, i32 0
/// %x3 = extractelement <4 x i8> %x, i32 3
/// %y1 = extractelement <4 x i8> %y, i32 1
/// %y2 = extractelement <4 x i8> %y, i32 2
/// %1 = insertelement <4 x i8> poison, i8 %x0, i32 0
/// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1
/// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2
/// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3
/// %5 = mul <4 x i8> %4, %4
/// %6 = extractelement <4 x i8> %5, i32 0
/// %ins1 = insertelement <4 x i8> poison, i8 %6, i32 0
/// %7 = extractelement <4 x i8> %5, i32 1
/// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1
/// %8 = extractelement <4 x i8> %5, i32 2
/// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2
/// %9 = extractelement <4 x i8> %5, i32 3
/// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3
/// ret <4 x i8> %ins4
/// InstCombiner transforms this into a shuffle and vector mul
/// Mask will return the Shuffle Mask equivalent to the extracted elements.
/// TODO: Can we split off and reuse the shuffle mask detection from
/// ShuffleVectorInst/getShuffleCost?
static std::optional<TargetTransformInfo::ShuffleKind>
isFixedVectorShuffle(ArrayRef<Value *> VL, SmallVectorImpl<int> &Mask) {
const auto *It =
find_if(VL, [](Value *V) { return isa<ExtractElementInst>(V); });
if (It == VL.end())
return std::nullopt;
auto *EI0 = cast<ExtractElementInst>(*It);
if (isa<ScalableVectorType>(EI0->getVectorOperandType()))
return std::nullopt;
unsigned Size =
cast<FixedVectorType>(EI0->getVectorOperandType())->getNumElements();
Value *Vec1 = nullptr;
Value *Vec2 = nullptr;
enum ShuffleMode { Unknown, Select, Permute };
ShuffleMode CommonShuffleMode = Unknown;
Mask.assign(VL.size(), PoisonMaskElem);
for (unsigned I = 0, E = VL.size(); I < E; ++I) {
// Undef can be represented as an undef element in a vector.
if (isa<UndefValue>(VL[I]))
continue;
auto *EI = cast<ExtractElementInst>(VL[I]);
if (isa<ScalableVectorType>(EI->getVectorOperandType()))
return std::nullopt;
auto *Vec = EI->getVectorOperand();
// We can extractelement from undef or poison vector.
if (isUndefVector(Vec).all())
continue;
// All vector operands must have the same number of vector elements.
if (cast<FixedVectorType>(Vec->getType())->getNumElements() != Size)
return std::nullopt;
if (isa<UndefValue>(EI->getIndexOperand()))
continue;
auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand());
if (!Idx)
return std::nullopt;
// Undefined behavior if Idx is negative or >= Size.
if (Idx->getValue().uge(Size))
continue;
unsigned IntIdx = Idx->getValue().getZExtValue();
Mask[I] = IntIdx;
// For correct shuffling we have to have at most 2 different vector operands
// in all extractelement instructions.
if (!Vec1 || Vec1 == Vec) {
Vec1 = Vec;
} else if (!Vec2 || Vec2 == Vec) {
Vec2 = Vec;
Mask[I] += Size;
} else {
return std::nullopt;
}
if (CommonShuffleMode == Permute)
continue;
// If the extract index is not the same as the operation number, it is a
// permutation.
if (IntIdx != I) {
CommonShuffleMode = Permute;
continue;
}
CommonShuffleMode = Select;
}
// If we're not crossing lanes in different vectors, consider it as blending.
if (CommonShuffleMode == Select && Vec2)
return TargetTransformInfo::SK_Select;
// If Vec2 was never used, we have a permutation of a single vector, otherwise
// we have permutation of 2 vectors.
return Vec2 ? TargetTransformInfo::SK_PermuteTwoSrc
: TargetTransformInfo::SK_PermuteSingleSrc;
}
/// \returns True if Extract{Value,Element} instruction extracts element Idx.
static std::optional<unsigned> getExtractIndex(Instruction *E) {
unsigned Opcode = E->getOpcode();
assert((Opcode == Instruction::ExtractElement ||
Opcode == Instruction::ExtractValue) &&
"Expected extractelement or extractvalue instruction.");
if (Opcode == Instruction::ExtractElement) {
auto *CI = dyn_cast<ConstantInt>(E->getOperand(1));
if (!CI)
return std::nullopt;
return CI->getZExtValue();
}
auto *EI = cast<ExtractValueInst>(E);
if (EI->getNumIndices() != 1)
return std::nullopt;
return *EI->idx_begin();
}
/// Tries to find extractelement instructions with constant indices from fixed
/// vector type and gather such instructions into a bunch, which highly likely
/// might be detected as a shuffle of 1 or 2 input vectors. If this attempt was
/// successful, the matched scalars are replaced by poison values in \p VL for
/// future analysis.
static std::optional<TTI::ShuffleKind>
tryToGatherExtractElements(SmallVectorImpl<Value *> &VL,
SmallVectorImpl<int> &Mask) {
// Scan list of gathered scalars for extractelements that can be represented
// as shuffles.
MapVector<Value *, SmallVector<int>> VectorOpToIdx;
SmallVector<int> UndefVectorExtracts;
for (int I = 0, E = VL.size(); I < E; ++I) {
auto *EI = dyn_cast<ExtractElementInst>(VL[I]);
if (!EI) {
if (isa<UndefValue>(VL[I]))
UndefVectorExtracts.push_back(I);
continue;
}
auto *VecTy = dyn_cast<FixedVectorType>(EI->getVectorOperandType());
if (!VecTy || !isa<ConstantInt, UndefValue>(EI->getIndexOperand()))
continue;
std::optional<unsigned> Idx = getExtractIndex(EI);
// Undefined index.
if (!Idx) {
UndefVectorExtracts.push_back(I);
continue;
}
SmallBitVector ExtractMask(VecTy->getNumElements(), true);
ExtractMask.reset(*Idx);
if (isUndefVector(EI->getVectorOperand(), ExtractMask).all()) {
UndefVectorExtracts.push_back(I);
continue;
}
VectorOpToIdx[EI->getVectorOperand()].push_back(I);
}
// Sort the vector operands by the maximum number of uses in extractelements.
MapVector<unsigned, SmallVector<Value *>> VFToVector;
for (const auto &Data : VectorOpToIdx)
VFToVector[cast<FixedVectorType>(Data.first->getType())->getNumElements()]
.push_back(Data.first);
for (auto &Data : VFToVector) {
stable_sort(Data.second, [&VectorOpToIdx](Value *V1, Value *V2) {
return VectorOpToIdx.find(V1)->second.size() >
VectorOpToIdx.find(V2)->second.size();
});
}
// Find the best pair of the vectors with the same number of elements or a
// single vector.
const int UndefSz = UndefVectorExtracts.size();
unsigned SingleMax = 0;
Value *SingleVec = nullptr;
unsigned PairMax = 0;
std::pair<Value *, Value *> PairVec(nullptr, nullptr);
for (auto &Data : VFToVector) {
Value *V1 = Data.second.front();
if (SingleMax < VectorOpToIdx[V1].size() + UndefSz) {
SingleMax = VectorOpToIdx[V1].size() + UndefSz;
SingleVec = V1;
}
Value *V2 = nullptr;
if (Data.second.size() > 1)
V2 = *std::next(Data.second.begin());
if (V2 && PairMax < VectorOpToIdx[V1].size() + VectorOpToIdx[V2].size() +
UndefSz) {
PairMax = VectorOpToIdx[V1].size() + VectorOpToIdx[V2].size() + UndefSz;
PairVec = std::make_pair(V1, V2);
}
}
if (SingleMax == 0 && PairMax == 0 && UndefSz == 0)
return std::nullopt;
// Check if better to perform a shuffle of 2 vectors or just of a single
// vector.
SmallVector<Value *> SavedVL(VL.begin(), VL.end());
SmallVector<Value *> GatheredExtracts(
VL.size(), PoisonValue::get(VL.front()->getType()));
if (SingleMax >= PairMax && SingleMax) {
for (int Idx : VectorOpToIdx[SingleVec])
std::swap(GatheredExtracts[Idx], VL[Idx]);
} else {
for (Value *V : {PairVec.first, PairVec.second})
for (int Idx : VectorOpToIdx[V])
std::swap(GatheredExtracts[Idx], VL[Idx]);
}
// Add extracts from undefs too.
for (int Idx : UndefVectorExtracts)
std::swap(GatheredExtracts[Idx], VL[Idx]);
// Check that gather of extractelements can be represented as just a
// shuffle of a single/two vectors the scalars are extracted from.
std::optional<TTI::ShuffleKind> Res =
isFixedVectorShuffle(GatheredExtracts, Mask);
if (!Res) {
// TODO: try to check other subsets if possible.
// Restore the original VL if attempt was not successful.
VL.swap(SavedVL);
return std::nullopt;
}
// Restore unused scalars from mask, if some of the extractelements were not
// selected for shuffle.
for (int I = 0, E = GatheredExtracts.size(); I < E; ++I) {
auto *EI = dyn_cast<ExtractElementInst>(VL[I]);
if (!EI || !isa<FixedVectorType>(EI->getVectorOperandType()) ||
!isa<ConstantInt, UndefValue>(EI->getIndexOperand()) ||
is_contained(UndefVectorExtracts, I))
continue;
if (Mask[I] == PoisonMaskElem && !isa<PoisonValue>(GatheredExtracts[I]))
std::swap(VL[I], GatheredExtracts[I]);
}
return Res;
}
namespace {
/// Main data required for vectorization of instructions.
struct InstructionsState {
/// The very first instruction in the list with the main opcode.
Value *OpValue = nullptr;
/// The main/alternate instruction.
Instruction *MainOp = nullptr;
Instruction *AltOp = nullptr;
/// The main/alternate opcodes for the list of instructions.
unsigned getOpcode() const {
return MainOp ? MainOp->getOpcode() : 0;
}
unsigned getAltOpcode() const {
return AltOp ? AltOp->getOpcode() : 0;
}
/// Some of the instructions in the list have alternate opcodes.
bool isAltShuffle() const { return AltOp != MainOp; }
bool isOpcodeOrAlt(Instruction *I) const {
unsigned CheckedOpcode = I->getOpcode();
return getOpcode() == CheckedOpcode || getAltOpcode() == CheckedOpcode;
}
InstructionsState() = delete;
InstructionsState(Value *OpValue, Instruction *MainOp, Instruction *AltOp)
: OpValue(OpValue), MainOp(MainOp), AltOp(AltOp) {}
};
} // end anonymous namespace
/// Chooses the correct key for scheduling data. If \p Op has the same (or
/// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is \p
/// OpValue.
static Value *isOneOf(const InstructionsState &S, Value *Op) {
auto *I = dyn_cast<Instruction>(Op);
if (I && S.isOpcodeOrAlt(I))
return Op;
return S.OpValue;
}
/// \returns true if \p Opcode is allowed as part of of the main/alternate
/// instruction for SLP vectorization.
///
/// Example of unsupported opcode is SDIV that can potentially cause UB if the
/// "shuffled out" lane would result in division by zero.
static bool isValidForAlternation(unsigned Opcode) {
if (Instruction::isIntDivRem(Opcode))
return false;
return true;
}
static InstructionsState getSameOpcode(ArrayRef<Value *> VL,
const TargetLibraryInfo &TLI,
unsigned BaseIndex = 0);
/// Checks if the provided operands of 2 cmp instructions are compatible, i.e.
/// compatible instructions or constants, or just some other regular values.
static bool areCompatibleCmpOps(Value *BaseOp0, Value *BaseOp1, Value *Op0,
Value *Op1, const TargetLibraryInfo &TLI) {
return (isConstant(BaseOp0) && isConstant(Op0)) ||
(isConstant(BaseOp1) && isConstant(Op1)) ||
(!isa<Instruction>(BaseOp0) && !isa<Instruction>(Op0) &&
!isa<Instruction>(BaseOp1) && !isa<Instruction>(Op1)) ||
BaseOp0 == Op0 || BaseOp1 == Op1 ||
getSameOpcode({BaseOp0, Op0}, TLI).getOpcode() ||
getSameOpcode({BaseOp1, Op1}, TLI).getOpcode();
}
/// \returns true if a compare instruction \p CI has similar "look" and
/// same predicate as \p BaseCI, "as is" or with its operands and predicate
/// swapped, false otherwise.
static bool isCmpSameOrSwapped(const CmpInst *BaseCI, const CmpInst *CI,
const TargetLibraryInfo &TLI) {
assert(BaseCI->getOperand(0)->getType() == CI->getOperand(0)->getType() &&
"Assessing comparisons of different types?");
CmpInst::Predicate BasePred = BaseCI->getPredicate();
CmpInst::Predicate Pred = CI->getPredicate();
CmpInst::Predicate SwappedPred = CmpInst::getSwappedPredicate(Pred);
Value *BaseOp0 = BaseCI->getOperand(0);
Value *BaseOp1 = BaseCI->getOperand(1);
Value *Op0 = CI->getOperand(0);
Value *Op1 = CI->getOperand(1);
return (BasePred == Pred &&
areCompatibleCmpOps(BaseOp0, BaseOp1, Op0, Op1, TLI)) ||
(BasePred == SwappedPred &&
areCompatibleCmpOps(BaseOp0, BaseOp1, Op1, Op0, TLI));
}
/// \returns analysis of the Instructions in \p VL described in
/// InstructionsState, the Opcode that we suppose the whole list
/// could be vectorized even if its structure is diverse.
static InstructionsState getSameOpcode(ArrayRef<Value *> VL,
const TargetLibraryInfo &TLI,
unsigned BaseIndex) {
// Make sure these are all Instructions.
if (llvm::any_of(VL, [](Value *V) { return !isa<Instruction>(V); }))
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
bool IsCastOp = isa<CastInst>(VL[BaseIndex]);
bool IsBinOp = isa<BinaryOperator>(VL[BaseIndex]);
bool IsCmpOp = isa<CmpInst>(VL[BaseIndex]);
CmpInst::Predicate BasePred =
IsCmpOp ? cast<CmpInst>(VL[BaseIndex])->getPredicate()
: CmpInst::BAD_ICMP_PREDICATE;
unsigned Opcode = cast<Instruction>(VL[BaseIndex])->getOpcode();
unsigned AltOpcode = Opcode;
unsigned AltIndex = BaseIndex;
// Check for one alternate opcode from another BinaryOperator.
// TODO - generalize to support all operators (types, calls etc.).
auto *IBase = cast<Instruction>(VL[BaseIndex]);
Intrinsic::ID BaseID = 0;
SmallVector<VFInfo> BaseMappings;
if (auto *CallBase = dyn_cast<CallInst>(IBase)) {
BaseID = getVectorIntrinsicIDForCall(CallBase, &TLI);
BaseMappings = VFDatabase(*CallBase).getMappings(*CallBase);
if (!isTriviallyVectorizable(BaseID) && BaseMappings.empty())
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
}
for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) {
auto *I = cast<Instruction>(VL[Cnt]);
unsigned InstOpcode = I->getOpcode();
if (IsBinOp && isa<BinaryOperator>(I)) {
if (InstOpcode == Opcode || InstOpcode == AltOpcode)
continue;
if (Opcode == AltOpcode && isValidForAlternation(InstOpcode) &&
isValidForAlternation(Opcode)) {
AltOpcode = InstOpcode;
AltIndex = Cnt;
continue;
}
} else if (IsCastOp && isa<CastInst>(I)) {
Value *Op0 = IBase->getOperand(0);
Type *Ty0 = Op0->getType();
Value *Op1 = I->getOperand(0);
Type *Ty1 = Op1->getType();
if (Ty0 == Ty1) {
if (InstOpcode == Opcode || InstOpcode == AltOpcode)
continue;
if (Opcode == AltOpcode) {
assert(isValidForAlternation(Opcode) &&
isValidForAlternation(InstOpcode) &&
"Cast isn't safe for alternation, logic needs to be updated!");
AltOpcode = InstOpcode;
AltIndex = Cnt;
continue;
}
}
} else if (auto *Inst = dyn_cast<CmpInst>(VL[Cnt]); Inst && IsCmpOp) {
auto *BaseInst = cast<CmpInst>(VL[BaseIndex]);
Type *Ty0 = BaseInst->getOperand(0)->getType();
Type *Ty1 = Inst->getOperand(0)->getType();
if (Ty0 == Ty1) {
assert(InstOpcode == Opcode && "Expected same CmpInst opcode.");
// Check for compatible operands. If the corresponding operands are not
// compatible - need to perform alternate vectorization.
CmpInst::Predicate CurrentPred = Inst->getPredicate();
CmpInst::Predicate SwappedCurrentPred =
CmpInst::getSwappedPredicate(CurrentPred);
if (E == 2 &&
(BasePred == CurrentPred || BasePred == SwappedCurrentPred))
continue;
if (isCmpSameOrSwapped(BaseInst, Inst, TLI))
continue;
auto *AltInst = cast<CmpInst>(VL[AltIndex]);
if (AltIndex != BaseIndex) {
if (isCmpSameOrSwapped(AltInst, Inst, TLI))
continue;
} else if (BasePred != CurrentPred) {
assert(
isValidForAlternation(InstOpcode) &&
"CmpInst isn't safe for alternation, logic needs to be updated!");
AltIndex = Cnt;
continue;
}
CmpInst::Predicate AltPred = AltInst->getPredicate();
if (BasePred == CurrentPred || BasePred == SwappedCurrentPred ||
AltPred == CurrentPred || AltPred == SwappedCurrentPred)
continue;
}
} else if (InstOpcode == Opcode || InstOpcode == AltOpcode) {
if (auto *Gep = dyn_cast<GetElementPtrInst>(I)) {
if (Gep->getNumOperands() != 2 ||
Gep->getOperand(0)->getType() != IBase->getOperand(0)->getType())
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
} else if (auto *EI = dyn_cast<ExtractElementInst>(I)) {
if (!isVectorLikeInstWithConstOps(EI))
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
} else if (auto *LI = dyn_cast<LoadInst>(I)) {
auto *BaseLI = cast<LoadInst>(IBase);
if (!LI->isSimple() || !BaseLI->isSimple())
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
} else if (auto *Call = dyn_cast<CallInst>(I)) {
auto *CallBase = cast<CallInst>(IBase);
if (Call->getCalledFunction() != CallBase->getCalledFunction())
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
if (Call->hasOperandBundles() &&
!std::equal(Call->op_begin() + Call->getBundleOperandsStartIndex(),
Call->op_begin() + Call->getBundleOperandsEndIndex(),
CallBase->op_begin() +
CallBase->getBundleOperandsStartIndex()))
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
Intrinsic::ID ID = getVectorIntrinsicIDForCall(Call, &TLI);
if (ID != BaseID)
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
if (!ID) {
SmallVector<VFInfo> Mappings = VFDatabase(*Call).getMappings(*Call);
if (Mappings.size() != BaseMappings.size() ||
Mappings.front().ISA != BaseMappings.front().ISA ||
Mappings.front().ScalarName != BaseMappings.front().ScalarName ||
Mappings.front().VectorName != BaseMappings.front().VectorName ||
Mappings.front().Shape.VF != BaseMappings.front().Shape.VF ||
Mappings.front().Shape.Parameters !=
BaseMappings.front().Shape.Parameters)
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
}
}
continue;
}
return InstructionsState(VL[BaseIndex], nullptr, nullptr);
}
return InstructionsState(VL[BaseIndex], cast<Instruction>(VL[BaseIndex]),
cast<Instruction>(VL[AltIndex]));
}
/// \returns true if all of the values in \p VL have the same type or false
/// otherwise.
static bool allSameType(ArrayRef<Value *> VL) {
Type *Ty = VL[0]->getType();
for (int i = 1, e = VL.size(); i < e; i++)
if (VL[i]->getType() != Ty)
return false;
return true;
}
/// \returns True if in-tree use also needs extract. This refers to
/// possible scalar operand in vectorized instruction.
static bool InTreeUserNeedToExtract(Value *Scalar, Instruction *UserInst,
TargetLibraryInfo *TLI) {
unsigned Opcode = UserInst->getOpcode();
switch (Opcode) {
case Instruction::Load: {
LoadInst *LI = cast<LoadInst>(UserInst);
return (LI->getPointerOperand() == Scalar);
}
case Instruction::Store: {
StoreInst *SI = cast<StoreInst>(UserInst);
return (SI->getPointerOperand() == Scalar);
}
case Instruction::Call: {
CallInst *CI = cast<CallInst>(UserInst);
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
for (unsigned i = 0, e = CI->arg_size(); i != e; ++i) {
if (isVectorIntrinsicWithScalarOpAtArg(ID, i))
return (CI->getArgOperand(i) == Scalar);
}
[[fallthrough]];
}
default:
return false;
}
}
/// \returns the AA location that is being access by the instruction.
static MemoryLocation getLocation(Instruction *I) {
if (StoreInst *SI = dyn_cast<StoreInst>(I))
return MemoryLocation::get(SI);
if (LoadInst *LI = dyn_cast<LoadInst>(I))
return MemoryLocation::get(LI);
return MemoryLocation();
}
/// \returns True if the instruction is not a volatile or atomic load/store.
static bool isSimple(Instruction *I) {
if (LoadInst *LI = dyn_cast<LoadInst>(I))
return LI->isSimple();
if (StoreInst *SI = dyn_cast<StoreInst>(I))
return SI->isSimple();
if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I))
return !MI->isVolatile();
return true;
}
/// Shuffles \p Mask in accordance with the given \p SubMask.
/// \param ExtendingManyInputs Supports reshuffling of the mask with not only
/// one but two input vectors.
static void addMask(SmallVectorImpl<int> &Mask, ArrayRef<int> SubMask,
bool ExtendingManyInputs = false) {
if (SubMask.empty())
return;
assert((!ExtendingManyInputs || SubMask.size() > Mask.size()) &&
"SubMask with many inputs support must be larger than the mask.");
if (Mask.empty()) {
Mask.append(SubMask.begin(), SubMask.end());
return;
}
SmallVector<int> NewMask(SubMask.size(), PoisonMaskElem);
int TermValue = std::min(Mask.size(), SubMask.size());
for (int I = 0, E = SubMask.size(); I < E; ++I) {
if (SubMask[I] == PoisonMaskElem ||
(!ExtendingManyInputs &&
(SubMask[I] >= TermValue || Mask[SubMask[I]] >= TermValue)))
continue;
NewMask[I] = Mask[SubMask[I]];
}
Mask.swap(NewMask);
}
/// Order may have elements assigned special value (size) which is out of
/// bounds. Such indices only appear on places which correspond to undef values
/// (see canReuseExtract for details) and used in order to avoid undef values
/// have effect on operands ordering.
/// The first loop below simply finds all unused indices and then the next loop
/// nest assigns these indices for undef values positions.
/// As an example below Order has two undef positions and they have assigned
/// values 3 and 7 respectively:
/// before: 6 9 5 4 9 2 1 0
/// after: 6 3 5 4 7 2 1 0
static void fixupOrderingIndices(SmallVectorImpl<unsigned> &Order) {
const unsigned Sz = Order.size();
SmallBitVector UnusedIndices(Sz, /*t=*/true);
SmallBitVector MaskedIndices(Sz);
for (unsigned I = 0; I < Sz; ++I) {
if (Order[I] < Sz)
UnusedIndices.reset(Order[I]);
else
MaskedIndices.set(I);
}
if (MaskedIndices.none())
return;
assert(UnusedIndices.count() == MaskedIndices.count() &&
"Non-synced masked/available indices.");
int Idx = UnusedIndices.find_first();
int MIdx = MaskedIndices.find_first();
while (MIdx >= 0) {
assert(Idx >= 0 && "Indices must be synced.");
Order[MIdx] = Idx;
Idx = UnusedIndices.find_next(Idx);
MIdx = MaskedIndices.find_next(MIdx);
}
}
namespace llvm {
static void inversePermutation(ArrayRef<unsigned> Indices,
SmallVectorImpl<int> &Mask) {
Mask.clear();
const unsigned E = Indices.size();
Mask.resize(E, PoisonMaskElem);
for (unsigned I = 0; I < E; ++I)
Mask[Indices[I]] = I;
}
/// Reorders the list of scalars in accordance with the given \p Mask.
static void reorderScalars(SmallVectorImpl<Value *> &Scalars,
ArrayRef<int> Mask) {
assert(!Mask.empty() && "Expected non-empty mask.");
SmallVector<Value *> Prev(Scalars.size(),
UndefValue::get(Scalars.front()->getType()));
Prev.swap(Scalars);
for (unsigned I = 0, E = Prev.size(); I < E; ++I)
if (Mask[I] != PoisonMaskElem)
Scalars[Mask[I]] = Prev[I];
}
/// Checks if the provided value does not require scheduling. It does not
/// require scheduling if this is not an instruction or it is an instruction
/// that does not read/write memory and all operands are either not instructions
/// or phi nodes or instructions from different blocks.
static bool areAllOperandsNonInsts(Value *V) {
auto *I = dyn_cast<Instruction>(V);
if (!I)
return true;
return !mayHaveNonDefUseDependency(*I) &&
all_of(I->operands(), [I](Value *V) {
auto *IO = dyn_cast<Instruction>(V);
if (!IO)
return true;
return isa<PHINode>(IO) || IO->getParent() != I->getParent();
});
}
/// Checks if the provided value does not require scheduling. It does not
/// require scheduling if this is not an instruction or it is an instruction
/// that does not read/write memory and all users are phi nodes or instructions
/// from the different blocks.
static bool isUsedOutsideBlock(Value *V) {
auto *I = dyn_cast<Instruction>(V);
if (!I)
return true;
// Limits the number of uses to save compile time.
constexpr int UsesLimit = 8;
return !I->mayReadOrWriteMemory() && !I->hasNUsesOrMore(UsesLimit) &&
all_of(I->users(), [I](User *U) {
auto *IU = dyn_cast<Instruction>(U);
if (!IU)
return true;
return IU->getParent() != I->getParent() || isa<PHINode>(IU);
});
}
/// Checks if the specified value does not require scheduling. It does not
/// require scheduling if all operands and all users do not need to be scheduled
/// in the current basic block.
static bool doesNotNeedToBeScheduled(Value *V) {
return areAllOperandsNonInsts(V) && isUsedOutsideBlock(V);
}
/// Checks if the specified array of instructions does not require scheduling.
/// It is so if all either instructions have operands that do not require
/// scheduling or their users do not require scheduling since they are phis or
/// in other basic blocks.
static bool doesNotNeedToSchedule(ArrayRef<Value *> VL) {
return !VL.empty() &&
(all_of(VL, isUsedOutsideBlock) || all_of(VL, areAllOperandsNonInsts));
}
namespace slpvectorizer {
/// Bottom Up SLP Vectorizer.
class BoUpSLP {
struct TreeEntry;
struct ScheduleData;
class ShuffleCostEstimator;
class ShuffleInstructionBuilder;
public:
using ValueList = SmallVector<Value *, 8>;
using InstrList = SmallVector<Instruction *, 16>;
using ValueSet = SmallPtrSet<Value *, 16>;
using StoreList = SmallVector<StoreInst *, 8>;
using ExtraValueToDebugLocsMap =
MapVector<Value *, SmallVector<Instruction *, 2>>;
using OrdersType = SmallVector<unsigned, 4>;
BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti,
TargetLibraryInfo *TLi, AAResults *Aa, LoopInfo *Li,
DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB,
const DataLayout *DL, OptimizationRemarkEmitter *ORE)
: BatchAA(*Aa), F(Func), SE(Se), TTI(Tti), TLI(TLi), LI(Li),
DT(Dt), AC(AC), DB(DB), DL(DL), ORE(ORE), Builder(Se->getContext()) {
CodeMetrics::collectEphemeralValues(F, AC, EphValues);
// Use the vector register size specified by the target unless overridden
// by a command-line option.
// TODO: It would be better to limit the vectorization factor based on
// data type rather than just register size. For example, x86 AVX has
// 256-bit registers, but it does not support integer operations
// at that width (that requires AVX2).
if (MaxVectorRegSizeOption.getNumOccurrences())
MaxVecRegSize = MaxVectorRegSizeOption;
else
MaxVecRegSize =
TTI->getRegisterBitWidth(TargetTransformInfo::RGK_FixedWidthVector)
.getFixedValue();
if (MinVectorRegSizeOption.getNumOccurrences())
MinVecRegSize = MinVectorRegSizeOption;
else
MinVecRegSize = TTI->getMinVectorRegisterBitWidth();
}
/// Vectorize the tree that starts with the elements in \p VL.
/// Returns the vectorized root.
Value *vectorizeTree();
/// Vectorize the tree but with the list of externally used values \p
/// ExternallyUsedValues. Values in this MapVector can be replaced but the
/// generated extractvalue instructions.
/// \param ReplacedExternals containd list of replaced external values
/// {scalar, replace} after emitting extractelement for external uses.
Value *
vectorizeTree(const ExtraValueToDebugLocsMap &ExternallyUsedValues,
SmallVectorImpl<std::pair<Value *, Value *>> &ReplacedExternals,
Instruction *ReductionRoot = nullptr);
/// \returns the cost incurred by unwanted spills and fills, caused by
/// holding live values over call sites.
InstructionCost getSpillCost() const;
/// \returns the vectorization cost of the subtree that starts at \p VL.
/// A negative number means that this is profitable.
InstructionCost getTreeCost(ArrayRef<Value *> VectorizedVals = std::nullopt);
/// Construct a vectorizable tree that starts at \p Roots, ignoring users for
/// the purpose of scheduling and extraction in the \p UserIgnoreLst.
void buildTree(ArrayRef<Value *> Roots,
const SmallDenseSet<Value *> &UserIgnoreLst);
/// Construct a vectorizable tree that starts at \p Roots.
void buildTree(ArrayRef<Value *> Roots);
/// Returns whether the root node has in-tree uses.
bool doesRootHaveInTreeUses() const {
return !VectorizableTree.empty() &&
!VectorizableTree.front()->UserTreeIndices.empty();
}
/// Return the scalars of the root node.
ArrayRef<Value *> getRootNodeScalars() const {
assert(!VectorizableTree.empty() && "No graph to get the first node from");
return VectorizableTree.front()->Scalars;
}
/// Builds external uses of the vectorized scalars, i.e. the list of
/// vectorized scalars to be extracted, their lanes and their scalar users. \p
/// ExternallyUsedValues contains additional list of external uses to handle
/// vectorization of reductions.
void
buildExternalUses(const ExtraValueToDebugLocsMap &ExternallyUsedValues = {});
/// Clear the internal data structures that are created by 'buildTree'.
void deleteTree() {
VectorizableTree.clear();
ScalarToTreeEntry.clear();
MustGather.clear();
EntryToLastInstruction.clear();
ExternalUses.clear();
for (auto &Iter : BlocksSchedules) {
BlockScheduling *BS = Iter.second.get();
BS->clear();
}
MinBWs.clear();
InstrElementSize.clear();
UserIgnoreList = nullptr;
PostponedGathers.clear();
ValueToGatherNodes.clear();
}
unsigned getTreeSize() const { return VectorizableTree.size(); }
/// Perform LICM and CSE on the newly generated gather sequences.
void optimizeGatherSequence();
/// Checks if the specified gather tree entry \p TE can be represented as a
/// shuffled vector entry + (possibly) permutation with other gathers. It
/// implements the checks only for possibly ordered scalars (Loads,
/// ExtractElement, ExtractValue), which can be part of the graph.
std::optional<OrdersType> findReusedOrderedScalars(const TreeEntry &TE);
/// Sort loads into increasing pointers offsets to allow greater clustering.
std::optional<OrdersType> findPartiallyOrderedLoads(const TreeEntry &TE);
/// Gets reordering data for the given tree entry. If the entry is vectorized
/// - just return ReorderIndices, otherwise check if the scalars can be
/// reordered and return the most optimal order.
/// \return std::nullopt if ordering is not important, empty order, if
/// identity order is important, or the actual order.
/// \param TopToBottom If true, include the order of vectorized stores and
/// insertelement nodes, otherwise skip them.
std::optional<OrdersType> getReorderingData(const TreeEntry &TE,
bool TopToBottom);
/// Reorders the current graph to the most profitable order starting from the
/// root node to the leaf nodes. The best order is chosen only from the nodes
/// of the same size (vectorization factor). Smaller nodes are considered
/// parts of subgraph with smaller VF and they are reordered independently. We
/// can make it because we still need to extend smaller nodes to the wider VF
/// and we can merge reordering shuffles with the widening shuffles.
void reorderTopToBottom();
/// Reorders the current graph to the most profitable order starting from
/// leaves to the root. It allows to rotate small subgraphs and reduce the
/// number of reshuffles if the leaf nodes use the same order. In this case we
/// can merge the orders and just shuffle user node instead of shuffling its
/// operands. Plus, even the leaf nodes have different orders, it allows to
/// sink reordering in the graph closer to the root node and merge it later
/// during analysis.
void reorderBottomToTop(bool IgnoreReorder = false);
/// \return The vector element size in bits to use when vectorizing the
/// expression tree ending at \p V. If V is a store, the size is the width of
/// the stored value. Otherwise, the size is the width of the largest loaded
/// value reaching V. This method is used by the vectorizer to calculate
/// vectorization factors.
unsigned getVectorElementSize(Value *V);
/// Compute the minimum type sizes required to represent the entries in a
/// vectorizable tree.
void computeMinimumValueSizes();
// \returns maximum vector register size as set by TTI or overridden by cl::opt.
unsigned getMaxVecRegSize() const {
return MaxVecRegSize;
}
// \returns minimum vector register size as set by cl::opt.
unsigned getMinVecRegSize() const {
return MinVecRegSize;
}
unsigned getMinVF(unsigned Sz) const {
return std::max(2U, getMinVecRegSize() / Sz);
}
unsigned getMaximumVF(unsigned ElemWidth, unsigned Opcode) const {
unsigned MaxVF = MaxVFOption.getNumOccurrences() ?
MaxVFOption : TTI->getMaximumVF(ElemWidth, Opcode);
return MaxVF ? MaxVF : UINT_MAX;
}
/// Check if homogeneous aggregate is isomorphic to some VectorType.
/// Accepts homogeneous multidimensional aggregate of scalars/vectors like
/// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> },
/// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on.
///
/// \returns number of elements in vector if isomorphism exists, 0 otherwise.
unsigned canMapToVector(Type *T, const DataLayout &DL) const;
/// \returns True if the VectorizableTree is both tiny and not fully
/// vectorizable. We do not vectorize such trees.
bool isTreeTinyAndNotFullyVectorizable(bool ForReduction = false) const;
/// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values
/// can be load combined in the backend. Load combining may not be allowed in
/// the IR optimizer, so we do not want to alter the pattern. For example,
/// partially transforming a scalar bswap() pattern into vector code is
/// effectively impossible for the backend to undo.
/// TODO: If load combining is allowed in the IR optimizer, this analysis
/// may not be necessary.
bool isLoadCombineReductionCandidate(RecurKind RdxKind) const;
/// Assume that a vector of stores of bitwise-or/shifted/zexted loaded values
/// can be load combined in the backend. Load combining may not be allowed in
/// the IR optimizer, so we do not want to alter the pattern. For example,
/// partially transforming a scalar bswap() pattern into vector code is
/// effectively impossible for the backend to undo.
/// TODO: If load combining is allowed in the IR optimizer, this analysis
/// may not be necessary.
bool isLoadCombineCandidate() const;
OptimizationRemarkEmitter *getORE() { return ORE; }
/// This structure holds any data we need about the edges being traversed
/// during buildTree_rec(). We keep track of:
/// (i) the user TreeEntry index, and
/// (ii) the index of the edge.
struct EdgeInfo {
EdgeInfo() = default;
EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx)
: UserTE(UserTE), EdgeIdx(EdgeIdx) {}
/// The user TreeEntry.
TreeEntry *UserTE = nullptr;
/// The operand index of the use.
unsigned EdgeIdx = UINT_MAX;
#ifndef NDEBUG
friend inline raw_ostream &operator<<(raw_ostream &OS,
const BoUpSLP::EdgeInfo &EI) {
EI.dump(OS);
return OS;
}
/// Debug print.
void dump(raw_ostream &OS) const {
OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null")
<< " EdgeIdx:" << EdgeIdx << "}";
}
LLVM_DUMP_METHOD void dump() const { dump(dbgs()); }
#endif
};
/// A helper class used for scoring candidates for two consecutive lanes.
class LookAheadHeuristics {
const TargetLibraryInfo &TLI;
const DataLayout &DL;
ScalarEvolution &SE;
const BoUpSLP &R;
int NumLanes; // Total number of lanes (aka vectorization factor).
int MaxLevel; // The maximum recursion depth for accumulating score.
public:
LookAheadHeuristics(const TargetLibraryInfo &TLI, const DataLayout &DL,
ScalarEvolution &SE, const BoUpSLP &R, int NumLanes,
int MaxLevel)
: TLI(TLI), DL(DL), SE(SE), R(R), NumLanes(NumLanes),
MaxLevel(MaxLevel) {}
// The hard-coded scores listed here are not very important, though it shall
// be higher for better matches to improve the resulting cost. When
// computing the scores of matching one sub-tree with another, we are
// basically counting the number of values that are matching. So even if all
// scores are set to 1, we would still get a decent matching result.
// However, sometimes we have to break ties. For example we may have to
// choose between matching loads vs matching opcodes. This is what these
// scores are helping us with: they provide the order of preference. Also,
// this is important if the scalar is externally used or used in another
// tree entry node in the different lane.
/// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]).
static const int ScoreConsecutiveLoads = 4;
/// The same load multiple times. This should have a better score than
/// `ScoreSplat` because it in x86 for a 2-lane vector we can represent it
/// with `movddup (%reg), xmm0` which has a throughput of 0.5 versus 0.5 for
/// a vector load and 1.0 for a broadcast.
static const int ScoreSplatLoads = 3;
/// Loads from reversed memory addresses, e.g. load(A[i+1]), load(A[i]).
static const int ScoreReversedLoads = 3;
/// A load candidate for masked gather.
static const int ScoreMaskedGatherCandidate = 1;
/// ExtractElementInst from same vector and consecutive indexes.
static const int ScoreConsecutiveExtracts = 4;
/// ExtractElementInst from same vector and reversed indices.
static const int ScoreReversedExtracts = 3;
/// Constants.
static const int ScoreConstants = 2;
/// Instructions with the same opcode.
static const int ScoreSameOpcode = 2;
/// Instructions with alt opcodes (e.g, add + sub).
static const int ScoreAltOpcodes = 1;
/// Identical instructions (a.k.a. splat or broadcast).
static const int ScoreSplat = 1;
/// Matching with an undef is preferable to failing.
static const int ScoreUndef = 1;
/// Score for failing to find a decent match.
static const int ScoreFail = 0;
/// Score if all users are vectorized.
static const int ScoreAllUserVectorized = 1;
/// \returns the score of placing \p V1 and \p V2 in consecutive lanes.
/// \p U1 and \p U2 are the users of \p V1 and \p V2.
/// Also, checks if \p V1 and \p V2 are compatible with instructions in \p
/// MainAltOps.
int getShallowScore(Value *V1, Value *V2, Instruction *U1, Instruction *U2,
ArrayRef<Value *> MainAltOps) const {
if (!isValidElementType(V1->getType()) ||
!isValidElementType(V2->getType()))
return LookAheadHeuristics::ScoreFail;
if (V1 == V2) {
if (isa<LoadInst>(V1)) {
// Retruns true if the users of V1 and V2 won't need to be extracted.
auto AllUsersAreInternal = [U1, U2, this](Value *V1, Value *V2) {
// Bail out if we have too many uses to save compilation time.
static constexpr unsigned Limit = 8;
if (V1->hasNUsesOrMore(Limit) || V2->hasNUsesOrMore(Limit))
return false;
auto AllUsersVectorized = [U1, U2, this](Value *V) {
return llvm::all_of(V->users(), [U1, U2, this](Value *U) {
return U == U1 || U == U2 || R.getTreeEntry(U) != nullptr;
});
};
return AllUsersVectorized(V1) && AllUsersVectorized(V2);
};
// A broadcast of a load can be cheaper on some targets.
if (R.TTI->isLegalBroadcastLoad(V1->getType(),
ElementCount::getFixed(NumLanes)) &&
((int)V1->getNumUses() == NumLanes ||
AllUsersAreInternal(V1, V2)))
return LookAheadHeuristics::ScoreSplatLoads;
}
return LookAheadHeuristics::ScoreSplat;
}
auto *LI1 = dyn_cast<LoadInst>(V1);
auto *LI2 = dyn_cast<LoadInst>(V2);
if (LI1 && LI2) {
if (LI1->getParent() != LI2->getParent() || !LI1->isSimple() ||
!LI2->isSimple())
return LookAheadHeuristics::ScoreFail;
std::optional<int> Dist = getPointersDiff(
LI1->getType(), LI1->getPointerOperand(), LI2->getType(),
LI2->getPointerOperand(), DL, SE, /*StrictCheck=*/true);
if (!Dist || *Dist == 0) {
if (getUnderlyingObject(LI1->getPointerOperand()) ==
getUnderlyingObject(LI2->getPointerOperand()) &&
R.TTI->isLegalMaskedGather(
FixedVectorType::get(LI1->getType(), NumLanes),
LI1->getAlign()))
return LookAheadHeuristics::ScoreMaskedGatherCandidate;
return LookAheadHeuristics::ScoreFail;
}
// The distance is too large - still may be profitable to use masked
// loads/gathers.
if (std::abs(*Dist) > NumLanes / 2)
return LookAheadHeuristics::ScoreMaskedGatherCandidate;
// This still will detect consecutive loads, but we might have "holes"
// in some cases. It is ok for non-power-2 vectorization and may produce
// better results. It should not affect current vectorization.
return (*Dist > 0) ? LookAheadHeuristics::ScoreConsecutiveLoads
: LookAheadHeuristics::ScoreReversedLoads;
}
auto *C1 = dyn_cast<Constant>(V1);
auto *C2 = dyn_cast<Constant>(V2);
if (C1 && C2)
return LookAheadHeuristics::ScoreConstants;
// Extracts from consecutive indexes of the same vector better score as
// the extracts could be optimized away.
Value *EV1;
ConstantInt *Ex1Idx;
if (match(V1, m_ExtractElt(m_Value(EV1), m_ConstantInt(Ex1Idx)))) {
// Undefs are always profitable for extractelements.
// Compiler can easily combine poison and extractelement <non-poison> or
// undef and extractelement <poison>. But combining undef +
// extractelement <non-poison-but-may-produce-poison> requires some
// extra operations.
if (isa<UndefValue>(V2))
return (isa<PoisonValue>(V2) || isUndefVector(EV1).all())
? LookAheadHeuristics::ScoreConsecutiveExtracts
: LookAheadHeuristics::ScoreSameOpcode;
Value *EV2 = nullptr;
ConstantInt *Ex2Idx = nullptr;
if (match(V2,
m_ExtractElt(m_Value(EV2), m_CombineOr(m_ConstantInt(Ex2Idx),
m_Undef())))) {
// Undefs are always profitable for extractelements.
if (!Ex2Idx)
return LookAheadHeuristics::ScoreConsecutiveExtracts;
if (isUndefVector(EV2).all() && EV2->getType() == EV1->getType())
return LookAheadHeuristics::ScoreConsecutiveExtracts;
if (EV2 == EV1) {
int Idx1 = Ex1Idx->getZExtValue();
int Idx2 = Ex2Idx->getZExtValue();
int Dist = Idx2 - Idx1;
// The distance is too large - still may be profitable to use
// shuffles.
if (std::abs(Dist) == 0)
return LookAheadHeuristics::ScoreSplat;
if (std::abs(Dist) > NumLanes / 2)
return LookAheadHeuristics::ScoreSameOpcode;
return (Dist > 0) ? LookAheadHeuristics::ScoreConsecutiveExtracts
: LookAheadHeuristics::ScoreReversedExtracts;
}
return LookAheadHeuristics::ScoreAltOpcodes;
}
return LookAheadHeuristics::ScoreFail;
}
auto *I1 = dyn_cast<Instruction>(V1);
auto *I2 = dyn_cast<Instruction>(V2);
if (I1 && I2) {
if (I1->getParent() != I2->getParent())
return LookAheadHeuristics::ScoreFail;
SmallVector<Value *, 4> Ops(MainAltOps.begin(), MainAltOps.end());
Ops.push_back(I1);
Ops.push_back(I2);
InstructionsState S = getSameOpcode(Ops, TLI);
// Note: Only consider instructions with <= 2 operands to avoid
// complexity explosion.
if (S.getOpcode() &&
(S.MainOp->getNumOperands() <= 2 || !MainAltOps.empty() ||
!S.isAltShuffle()) &&
all_of(Ops, [&S](Value *V) {
return cast<Instruction>(V)->getNumOperands() ==
S.MainOp->getNumOperands();
}))
return S.isAltShuffle() ? LookAheadHeuristics::ScoreAltOpcodes
: LookAheadHeuristics::ScoreSameOpcode;
}
if (isa<UndefValue>(V2))
return LookAheadHeuristics::ScoreUndef;
return LookAheadHeuristics::ScoreFail;
}
/// Go through the operands of \p LHS and \p RHS recursively until
/// MaxLevel, and return the cummulative score. \p U1 and \p U2 are
/// the users of \p LHS and \p RHS (that is \p LHS and \p RHS are operands
/// of \p U1 and \p U2), except at the beginning of the recursion where
/// these are set to nullptr.
///
/// For example:
/// \verbatim
/// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1]
/// \ / \ / \ / \ /
/// + + + +
/// G1 G2 G3 G4
/// \endverbatim
/// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at
/// each level recursively, accumulating the score. It starts from matching
/// the additions at level 0, then moves on to the loads (level 1). The
/// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and
/// {B[0],B[1]} match with LookAheadHeuristics::ScoreConsecutiveLoads, while
/// {A[0],C[0]} has a score of LookAheadHeuristics::ScoreFail.
/// Please note that the order of the operands does not matter, as we
/// evaluate the score of all profitable combinations of operands. In
/// other words the score of G1 and G4 is the same as G1 and G2. This
/// heuristic is based on ideas described in:
/// Look-ahead SLP: Auto-vectorization in the presence of commutative
/// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha,
/// Luís F. W. Góes
int getScoreAtLevelRec(Value *LHS, Value *RHS, Instruction *U1,
Instruction *U2, int CurrLevel,
ArrayRef<Value *> MainAltOps) const {
// Get the shallow score of V1 and V2.
int ShallowScoreAtThisLevel =
getShallowScore(LHS, RHS, U1, U2, MainAltOps);
// If reached MaxLevel,
// or if V1 and V2 are not instructions,
// or if they are SPLAT,
// or if they are not consecutive,
// or if profitable to vectorize loads or extractelements, early return
// the current cost.
auto *I1 = dyn_cast<Instruction>(LHS);
auto *I2 = dyn_cast<Instruction>(RHS);
if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 ||
ShallowScoreAtThisLevel == LookAheadHeuristics::ScoreFail ||
(((isa<LoadInst>(I1) && isa<LoadInst>(I2)) ||
(I1->getNumOperands() > 2 && I2->getNumOperands() > 2) ||
(isa<ExtractElementInst>(I1) && isa<ExtractElementInst>(I2))) &&
ShallowScoreAtThisLevel))
return ShallowScoreAtThisLevel;
assert(I1 && I2 && "Should have early exited.");
// Contains the I2 operand indexes that got matched with I1 operands.
SmallSet<unsigned, 4> Op2Used;
// Recursion towards the operands of I1 and I2. We are trying all possible
// operand pairs, and keeping track of the best score.
for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands();
OpIdx1 != NumOperands1; ++OpIdx1) {
// Try to pair op1I with the best operand of I2.
int MaxTmpScore = 0;
unsigned MaxOpIdx2 = 0;
bool FoundBest = false;
// If I2 is commutative try all combinations.
unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1;
unsigned ToIdx = isCommutative(I2)
? I2->getNumOperands()
: std::min(I2->getNumOperands(), OpIdx1 + 1);
assert(FromIdx <= ToIdx && "Bad index");
for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) {
// Skip operands already paired with OpIdx1.
if (Op2Used.count(OpIdx2))
continue;
// Recursively calculate the cost at each level
int TmpScore =
getScoreAtLevelRec(I1->getOperand(OpIdx1), I2->getOperand(OpIdx2),
I1, I2, CurrLevel + 1, std::nullopt);
// Look for the best score.
if (TmpScore > LookAheadHeuristics::ScoreFail &&
TmpScore > MaxTmpScore) {
MaxTmpScore = TmpScore;
MaxOpIdx2 = OpIdx2;
FoundBest = true;
}
}
if (FoundBest) {
// Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it.
Op2Used.insert(MaxOpIdx2);
ShallowScoreAtThisLevel += MaxTmpScore;
}
}
return ShallowScoreAtThisLevel;
}
};
/// A helper data structure to hold the operands of a vector of instructions.
/// This supports a fixed vector length for all operand vectors.
class VLOperands {
/// For each operand we need (i) the value, and (ii) the opcode that it
/// would be attached to if the expression was in a left-linearized form.
/// This is required to avoid illegal operand reordering.
/// For example:
/// \verbatim
/// 0 Op1
/// |/
/// Op1 Op2 Linearized + Op2
/// \ / ----------> |/
/// - -
///
/// Op1 - Op2 (0 + Op1) - Op2
/// \endverbatim
///
/// Value Op1 is attached to a '+' operation, and Op2 to a '-'.
///
/// Another way to think of this is to track all the operations across the
/// path from the operand all the way to the root of the tree and to
/// calculate the operation that corresponds to this path. For example, the
/// path from Op2 to the root crosses the RHS of the '-', therefore the
/// corresponding operation is a '-' (which matches the one in the
/// linearized tree, as shown above).
///
/// For lack of a better term, we refer to this operation as Accumulated
/// Path Operation (APO).
struct OperandData {
OperandData() = default;
OperandData(Value *V, bool APO, bool IsUsed)
: V(V), APO(APO), IsUsed(IsUsed) {}
/// The operand value.
Value *V = nullptr;
/// TreeEntries only allow a single opcode, or an alternate sequence of
/// them (e.g, +, -). Therefore, we can safely use a boolean value for the
/// APO. It is set to 'true' if 'V' is attached to an inverse operation
/// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise
/// (e.g., Add/Mul)
bool APO = false;
/// Helper data for the reordering function.
bool IsUsed = false;
};
/// During operand reordering, we are trying to select the operand at lane
/// that matches best with the operand at the neighboring lane. Our
/// selection is based on the type of value we are looking for. For example,
/// if the neighboring lane has a load, we need to look for a load that is
/// accessing a consecutive address. These strategies are summarized in the
/// 'ReorderingMode' enumerator.
enum class ReorderingMode {
Load, ///< Matching loads to consecutive memory addresses
Opcode, ///< Matching instructions based on opcode (same or alternate)
Constant, ///< Matching constants
Splat, ///< Matching the same instruction multiple times (broadcast)
Failed, ///< We failed to create a vectorizable group
};
using OperandDataVec = SmallVector<OperandData, 2>;
/// A vector of operand vectors.
SmallVector<OperandDataVec, 4> OpsVec;
const TargetLibraryInfo &TLI;
const DataLayout &DL;
ScalarEvolution &SE;
const BoUpSLP &R;
/// \returns the operand data at \p OpIdx and \p Lane.
OperandData &getData(unsigned OpIdx, unsigned Lane) {
return OpsVec[OpIdx][Lane];
}
/// \returns the operand data at \p OpIdx and \p Lane. Const version.
const OperandData &getData(unsigned OpIdx, unsigned Lane) const {
return OpsVec[OpIdx][Lane];
}
/// Clears the used flag for all entries.
void clearUsed() {
for (unsigned OpIdx = 0, NumOperands = getNumOperands();
OpIdx != NumOperands; ++OpIdx)
for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes;
++Lane)
OpsVec[OpIdx][Lane].IsUsed = false;
}
/// Swap the operand at \p OpIdx1 with that one at \p OpIdx2.
void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) {
std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]);
}
/// \param Lane lane of the operands under analysis.
/// \param OpIdx operand index in \p Lane lane we're looking the best
/// candidate for.
/// \param Idx operand index of the current candidate value.
/// \returns The additional score due to possible broadcasting of the
/// elements in the lane. It is more profitable to have power-of-2 unique
/// elements in the lane, it will be vectorized with higher probability
/// after removing duplicates. Currently the SLP vectorizer supports only
/// vectorization of the power-of-2 number of unique scalars.
int getSplatScore(unsigned Lane, unsigned OpIdx, unsigned Idx) const {
Value *IdxLaneV = getData(Idx, Lane).V;
if (!isa<Instruction>(IdxLaneV) || IdxLaneV == getData(OpIdx, Lane).V)
return 0;
SmallPtrSet<Value *, 4> Uniques;
for (unsigned Ln = 0, E = getNumLanes(); Ln < E; ++Ln) {
if (Ln == Lane)
continue;
Value *OpIdxLnV = getData(OpIdx, Ln).V;
if (!isa<Instruction>(OpIdxLnV))
return 0;
Uniques.insert(OpIdxLnV);
}
int UniquesCount = Uniques.size();
int UniquesCntWithIdxLaneV =
Uniques.contains(IdxLaneV) ? UniquesCount : UniquesCount + 1;
Value *OpIdxLaneV = getData(OpIdx, Lane).V;
int UniquesCntWithOpIdxLaneV =
Uniques.contains(OpIdxLaneV) ? UniquesCount : UniquesCount + 1;
if (UniquesCntWithIdxLaneV == UniquesCntWithOpIdxLaneV)
return 0;
return (PowerOf2Ceil(UniquesCntWithOpIdxLaneV) -
UniquesCntWithOpIdxLaneV) -
(PowerOf2Ceil(UniquesCntWithIdxLaneV) - UniquesCntWithIdxLaneV);
}
/// \param Lane lane of the operands under analysis.
/// \param OpIdx operand index in \p Lane lane we're looking the best
/// candidate for.
/// \param Idx operand index of the current candidate value.
/// \returns The additional score for the scalar which users are all
/// vectorized.
int getExternalUseScore(unsigned Lane, unsigned OpIdx, unsigned Idx) const {
Value *IdxLaneV = getData(Idx, Lane).V;
Value *OpIdxLaneV = getData(OpIdx, Lane).V;
// Do not care about number of uses for vector-like instructions
// (extractelement/extractvalue with constant indices), they are extracts
// themselves and already externally used. Vectorization of such
// instructions does not add extra extractelement instruction, just may
// remove it.
if (isVectorLikeInstWithConstOps(IdxLaneV) &&
isVectorLikeInstWithConstOps(OpIdxLaneV))
return LookAheadHeuristics::ScoreAllUserVectorized;
auto *IdxLaneI = dyn_cast<Instruction>(IdxLaneV);
if (!IdxLaneI || !isa<Instruction>(OpIdxLaneV))
return 0;
return R.areAllUsersVectorized(IdxLaneI, std::nullopt)
? LookAheadHeuristics::ScoreAllUserVectorized
: 0;
}
/// Score scaling factor for fully compatible instructions but with
/// different number of external uses. Allows better selection of the
/// instructions with less external uses.
static const int ScoreScaleFactor = 10;
/// \Returns the look-ahead score, which tells us how much the sub-trees
/// rooted at \p LHS and \p RHS match, the more they match the higher the
/// score. This helps break ties in an informed way when we cannot decide on
/// the order of the operands by just considering the immediate
/// predecessors.
int getLookAheadScore(Value *LHS, Value *RHS, ArrayRef<Value *> MainAltOps,
int Lane, unsigned OpIdx, unsigned Idx,
bool &IsUsed) {
LookAheadHeuristics LookAhead(TLI, DL, SE, R, getNumLanes(),
LookAheadMaxDepth);
// Keep track of the instruction stack as we recurse into the operands
// during the look-ahead score exploration.
int Score =
LookAhead.getScoreAtLevelRec(LHS, RHS, /*U1=*/nullptr, /*U2=*/nullptr,
/*CurrLevel=*/1, MainAltOps);
if (Score) {
int SplatScore = getSplatScore(Lane, OpIdx, Idx);
if (Score <= -SplatScore) {
// Set the minimum score for splat-like sequence to avoid setting
// failed state.
Score = 1;
} else {
Score += SplatScore;
// Scale score to see the difference between different operands
// and similar operands but all vectorized/not all vectorized
// uses. It does not affect actual selection of the best
// compatible operand in general, just allows to select the
// operand with all vectorized uses.
Score *= ScoreScaleFactor;
Score += getExternalUseScore(Lane, OpIdx, Idx);
IsUsed = true;
}
}
return Score;
}
/// Best defined scores per lanes between the passes. Used to choose the
/// best operand (with the highest score) between the passes.
/// The key - {Operand Index, Lane}.
/// The value - the best score between the passes for the lane and the
/// operand.
SmallDenseMap<std::pair<unsigned, unsigned>, unsigned, 8>
BestScoresPerLanes;
// Search all operands in Ops[*][Lane] for the one that matches best
// Ops[OpIdx][LastLane] and return its opreand index.
// If no good match can be found, return std::nullopt.
std::optional<unsigned>
getBestOperand(unsigned OpIdx, int Lane, int LastLane,
ArrayRef<ReorderingMode> ReorderingModes,
ArrayRef<Value *> MainAltOps) {
unsigned NumOperands = getNumOperands();
// The operand of the previous lane at OpIdx.
Value *OpLastLane = getData(OpIdx, LastLane).V;
// Our strategy mode for OpIdx.
ReorderingMode RMode = ReorderingModes[OpIdx];
if (RMode == ReorderingMode::Failed)
return std::nullopt;
// The linearized opcode of the operand at OpIdx, Lane.
bool OpIdxAPO = getData(OpIdx, Lane).APO;
// The best operand index and its score.
// Sometimes we have more than one option (e.g., Opcode and Undefs), so we
// are using the score to differentiate between the two.
struct BestOpData {
std::optional<unsigned> Idx;
unsigned Score = 0;
} BestOp;
BestOp.Score =
BestScoresPerLanes.try_emplace(std::make_pair(OpIdx, Lane), 0)
.first->second;
// Track if the operand must be marked as used. If the operand is set to
// Score 1 explicitly (because of non power-of-2 unique scalars, we may
// want to reestimate the operands again on the following iterations).
bool IsUsed =
RMode == ReorderingMode::Splat || RMode == ReorderingMode::Constant;
// Iterate through all unused operands and look for the best.
for (unsigned Idx = 0; Idx != NumOperands; ++Idx) {
// Get the operand at Idx and Lane.
OperandData &OpData = getData(Idx, Lane);
Value *Op = OpData.V;
bool OpAPO = OpData.APO;
// Skip already selected operands.
if (OpData.IsUsed)
continue;
// Skip if we are trying to move the operand to a position with a
// different opcode in the linearized tree form. This would break the
// semantics.
if (OpAPO != OpIdxAPO)
continue;
// Look for an operand that matches the current mode.
switch (RMode) {
case ReorderingMode::Load:
case ReorderingMode::Constant:
case ReorderingMode::Opcode: {
bool LeftToRight = Lane > LastLane;
Value *OpLeft = (LeftToRight) ? OpLastLane : Op;
Value *OpRight = (LeftToRight) ? Op : OpLastLane;
int Score = getLookAheadScore(OpLeft, OpRight, MainAltOps, Lane,
OpIdx, Idx, IsUsed);
if (Score > static_cast<int>(BestOp.Score)) {
BestOp.Idx = Idx;
BestOp.Score = Score;
BestScoresPerLanes[std::make_pair(OpIdx, Lane)] = Score;
}
break;
}
case ReorderingMode::Splat:
if (Op == OpLastLane)
BestOp.Idx = Idx;
break;
case ReorderingMode::Failed:
llvm_unreachable("Not expected Failed reordering mode.");
}
}
if (BestOp.Idx) {
getData(*BestOp.Idx, Lane).IsUsed = IsUsed;
return BestOp.Idx;
}
// If we could not find a good match return std::nullopt.
return std::nullopt;
}
/// Helper for reorderOperandVecs.
/// \returns the lane that we should start reordering from. This is the one
/// which has the least number of operands that can freely move about or
/// less profitable because it already has the most optimal set of operands.
unsigned getBestLaneToStartReordering() const {
unsigned Min = UINT_MAX;
unsigned SameOpNumber = 0;
// std::pair<unsigned, unsigned> is used to implement a simple voting
// algorithm and choose the lane with the least number of operands that
// can freely move about or less profitable because it already has the
// most optimal set of operands. The first unsigned is a counter for
// voting, the second unsigned is the counter of lanes with instructions
// with same/alternate opcodes and same parent basic block.
MapVector<unsigned, std::pair<unsigned, unsigned>> HashMap;
// Try to be closer to the original results, if we have multiple lanes
// with same cost. If 2 lanes have the same cost, use the one with the
// lowest index.
for (int I = getNumLanes(); I > 0; --I) {
unsigned Lane = I - 1;
OperandsOrderData NumFreeOpsHash =
getMaxNumOperandsThatCanBeReordered(Lane);
// Compare the number of operands that can move and choose the one with
// the least number.
if (NumFreeOpsHash.NumOfAPOs < Min) {
Min = NumFreeOpsHash.NumOfAPOs;
SameOpNumber = NumFreeOpsHash.NumOpsWithSameOpcodeParent;
HashMap.clear();
HashMap[NumFreeOpsHash.Hash] = std::make_pair(1, Lane);
} else if (NumFreeOpsHash.NumOfAPOs == Min &&
NumFreeOpsHash.NumOpsWithSameOpcodeParent < SameOpNumber) {
// Select the most optimal lane in terms of number of operands that
// should be moved around.
SameOpNumber = NumFreeOpsHash.NumOpsWithSameOpcodeParent;
HashMap[NumFreeOpsHash.Hash] = std::make_pair(1, Lane);
} else if (NumFreeOpsHash.NumOfAPOs == Min &&
NumFreeOpsHash.NumOpsWithSameOpcodeParent == SameOpNumber) {
auto It = HashMap.find(NumFreeOpsHash.Hash);
if (It == HashMap.end())
HashMap[NumFreeOpsHash.Hash] = std::make_pair(1, Lane);
else
++It->second.first;
}
}
// Select the lane with the minimum counter.
unsigned BestLane = 0;
unsigned CntMin = UINT_MAX;
for (const auto &Data : reverse(HashMap)) {
if (Data.second.first < CntMin) {
CntMin = Data.second.first;
BestLane = Data.second.second;
}
}
return BestLane;
}
/// Data structure that helps to reorder operands.
struct OperandsOrderData {
/// The best number of operands with the same APOs, which can be
/// reordered.
unsigned NumOfAPOs = UINT_MAX;
/// Number of operands with the same/alternate instruction opcode and
/// parent.
unsigned NumOpsWithSameOpcodeParent = 0;
/// Hash for the actual operands ordering.
/// Used to count operands, actually their position id and opcode
/// value. It is used in the voting mechanism to find the lane with the
/// least number of operands that can freely move about or less profitable
/// because it already has the most optimal set of operands. Can be
/// replaced with SmallVector<unsigned> instead but hash code is faster
/// and requires less memory.
unsigned Hash = 0;
};
/// \returns the maximum number of operands that are allowed to be reordered
/// for \p Lane and the number of compatible instructions(with the same
/// parent/opcode). This is used as a heuristic for selecting the first lane
/// to start operand reordering.
OperandsOrderData getMaxNumOperandsThatCanBeReordered(unsigned Lane) const {
unsigned CntTrue = 0;
unsigned NumOperands = getNumOperands();
// Operands with the same APO can be reordered. We therefore need to count
// how many of them we have for each APO, like this: Cnt[APO] = x.
// Since we only have two APOs, namely true and false, we can avoid using
// a map. Instead we can simply count the number of operands that
// correspond to one of them (in this case the 'true' APO), and calculate
// the other by subtracting it from the total number of operands.
// Operands with the same instruction opcode and parent are more
// profitable since we don't need to move them in many cases, with a high
// probability such lane already can be vectorized effectively.
bool AllUndefs = true;
unsigned NumOpsWithSameOpcodeParent = 0;
Instruction *OpcodeI = nullptr;
BasicBlock *Parent = nullptr;
unsigned Hash = 0;
for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
const OperandData &OpData = getData(OpIdx, Lane);
if (OpData.APO)
++CntTrue;
// Use Boyer-Moore majority voting for finding the majority opcode and
// the number of times it occurs.
if (auto *I = dyn_cast<Instruction>(OpData.V)) {
if (!OpcodeI || !getSameOpcode({OpcodeI, I}, TLI).getOpcode() ||
I->getParent() != Parent) {
if (NumOpsWithSameOpcodeParent == 0) {
NumOpsWithSameOpcodeParent = 1;
OpcodeI = I;
Parent = I->getParent();
} else {
--NumOpsWithSameOpcodeParent;
}
} else {
++NumOpsWithSameOpcodeParent;
}
}
Hash = hash_combine(
Hash, hash_value((OpIdx + 1) * (OpData.V->getValueID() + 1)));
AllUndefs = AllUndefs && isa<UndefValue>(OpData.V);
}
if (AllUndefs)
return {};
OperandsOrderData Data;
Data.NumOfAPOs = std::max(CntTrue, NumOperands - CntTrue);
Data.NumOpsWithSameOpcodeParent = NumOpsWithSameOpcodeParent;
Data.Hash = Hash;
return Data;
}
/// Go through the instructions in VL and append their operands.
void appendOperandsOfVL(ArrayRef<Value *> VL) {
assert(!VL.empty() && "Bad VL");
assert((empty() || VL.size() == getNumLanes()) &&
"Expected same number of lanes");
assert(isa<Instruction>(VL[0]) && "Expected instruction");
unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands();
OpsVec.resize(NumOperands);
unsigned NumLanes = VL.size();
for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
OpsVec[OpIdx].resize(NumLanes);
for (unsigned Lane = 0; Lane != NumLanes; ++Lane) {
assert(isa<Instruction>(VL[Lane]) && "Expected instruction");
// Our tree has just 3 nodes: the root and two operands.
// It is therefore trivial to get the APO. We only need to check the
// opcode of VL[Lane] and whether the operand at OpIdx is the LHS or
// RHS operand. The LHS operand of both add and sub is never attached
// to an inversese operation in the linearized form, therefore its APO
// is false. The RHS is true only if VL[Lane] is an inverse operation.
// Since operand reordering is performed on groups of commutative
// operations or alternating sequences (e.g., +, -), we can safely
// tell the inverse operations by checking commutativity.
bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane]));
bool APO = (OpIdx == 0) ? false : IsInverseOperation;
OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx),
APO, false};
}
}
}
/// \returns the number of operands.
unsigned getNumOperands() const { return OpsVec.size(); }
/// \returns the number of lanes.
unsigned getNumLanes() const { return OpsVec[0].size(); }
/// \returns the operand value at \p OpIdx and \p Lane.
Value *getValue(unsigned OpIdx, unsigned Lane) const {
return getData(OpIdx, Lane).V;
}
/// \returns true if the data structure is empty.
bool empty() const { return OpsVec.empty(); }
/// Clears the data.
void clear() { OpsVec.clear(); }
/// \Returns true if there are enough operands identical to \p Op to fill
/// the whole vector.
/// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow.
bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) {
bool OpAPO = getData(OpIdx, Lane).APO;
for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) {
if (Ln == Lane)
continue;
// This is set to true if we found a candidate for broadcast at Lane.
bool FoundCandidate = false;
for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) {
OperandData &Data = getData(OpI, Ln);
if (Data.APO != OpAPO || Data.IsUsed)
continue;
if (Data.V == Op) {
FoundCandidate = true;
Data.IsUsed = true;
break;
}
}
if (!FoundCandidate)
return false;
}
return true;
}
public:
/// Initialize with all the operands of the instruction vector \p RootVL.
VLOperands(ArrayRef<Value *> RootVL, const TargetLibraryInfo &TLI,
const DataLayout &DL, ScalarEvolution &SE, const BoUpSLP &R)
: TLI(TLI), DL(DL), SE(SE), R(R) {
// Append all the operands of RootVL.
appendOperandsOfVL(RootVL);
}
/// \Returns a value vector with the operands across all lanes for the
/// opearnd at \p OpIdx.
ValueList getVL(unsigned OpIdx) const {
ValueList OpVL(OpsVec[OpIdx].size());
assert(OpsVec[OpIdx].size() == getNumLanes() &&
"Expected same num of lanes across all operands");
for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane)
OpVL[Lane] = OpsVec[OpIdx][Lane].V;
return OpVL;
}
// Performs operand reordering for 2 or more operands.
// The original operands are in OrigOps[OpIdx][Lane].
// The reordered operands are returned in 'SortedOps[OpIdx][Lane]'.
void reorder() {
unsigned NumOperands = getNumOperands();
unsigned NumLanes = getNumLanes();
// Each operand has its own mode. We are using this mode to help us select
// the instructions for each lane, so that they match best with the ones
// we have selected so far.
SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands);
// This is a greedy single-pass algorithm. We are going over each lane
// once and deciding on the best order right away with no back-tracking.
// However, in order to increase its effectiveness, we start with the lane
// that has operands that can move the least. For example, given the
// following lanes:
// Lane 0 : A[0] = B[0] + C[0] // Visited 3rd
// Lane 1 : A[1] = C[1] - B[1] // Visited 1st
// Lane 2 : A[2] = B[2] + C[2] // Visited 2nd
// Lane 3 : A[3] = C[3] - B[3] // Visited 4th
// we will start at Lane 1, since the operands of the subtraction cannot
// be reordered. Then we will visit the rest of the lanes in a circular
// fashion. That is, Lanes 2, then Lane 0, and finally Lane 3.
// Find the first lane that we will start our search from.
unsigned FirstLane = getBestLaneToStartReordering();
// Initialize the modes.
for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
Value *OpLane0 = getValue(OpIdx, FirstLane);
// Keep track if we have instructions with all the same opcode on one
// side.
if (isa<LoadInst>(OpLane0))
ReorderingModes[OpIdx] = ReorderingMode::Load;
else if (isa<Instruction>(OpLane0)) {
// Check if OpLane0 should be broadcast.
if (shouldBroadcast(OpLane0, OpIdx, FirstLane))
ReorderingModes[OpIdx] = ReorderingMode::Splat;
else
ReorderingModes[OpIdx] = ReorderingMode::Opcode;
}
else if (isa<Constant>(OpLane0))
ReorderingModes[OpIdx] = ReorderingMode::Constant;
else if (isa<Argument>(OpLane0))
// Our best hope is a Splat. It may save some cost in some cases.
ReorderingModes[OpIdx] = ReorderingMode::Splat;
else
// NOTE: This should be unreachable.
ReorderingModes[OpIdx] = ReorderingMode::Failed;
}
// Check that we don't have same operands. No need to reorder if operands
// are just perfect diamond or shuffled diamond match. Do not do it only
// for possible broadcasts or non-power of 2 number of scalars (just for
// now).
auto &&SkipReordering = [this]() {
SmallPtrSet<Value *, 4> UniqueValues;
ArrayRef<OperandData> Op0 = OpsVec.front();
for (const OperandData &Data : Op0)
UniqueValues.insert(Data.V);
for (ArrayRef<OperandData> Op : drop_begin(OpsVec, 1)) {
if (any_of(Op, [&UniqueValues](const OperandData &Data) {
return !UniqueValues.contains(Data.V);
}))
return false;
}
// TODO: Check if we can remove a check for non-power-2 number of
// scalars after full support of non-power-2 vectorization.
return UniqueValues.size() != 2 && isPowerOf2_32(UniqueValues.size());
};
// If the initial strategy fails for any of the operand indexes, then we
// perform reordering again in a second pass. This helps avoid assigning
// high priority to the failed strategy, and should improve reordering for
// the non-failed operand indexes.
for (int Pass = 0; Pass != 2; ++Pass) {
// Check if no need to reorder operands since they're are perfect or
// shuffled diamond match.
// Need to to do it to avoid extra external use cost counting for
// shuffled matches, which may cause regressions.
if (SkipReordering())
break;
// Skip the second pass if the first pass did not fail.
bool StrategyFailed = false;
// Mark all operand data as free to use.
clearUsed();
// We keep the original operand order for the FirstLane, so reorder the
// rest of the lanes. We are visiting the nodes in a circular fashion,
// using FirstLane as the center point and increasing the radius
// distance.
SmallVector<SmallVector<Value *, 2>> MainAltOps(NumOperands);
for (unsigned I = 0; I < NumOperands; ++I)
MainAltOps[I].push_back(getData(I, FirstLane).V);
for (unsigned Distance = 1; Distance != NumLanes; ++Distance) {
// Visit the lane on the right and then the lane on the left.
for (int Direction : {+1, -1}) {
int Lane = FirstLane + Direction * Distance;
if (Lane < 0 || Lane >= (int)NumLanes)
continue;
int LastLane = Lane - Direction;
assert(LastLane >= 0 && LastLane < (int)NumLanes &&
"Out of bounds");
// Look for a good match for each operand.
for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) {
// Search for the operand that matches SortedOps[OpIdx][Lane-1].
std::optional<unsigned> BestIdx = getBestOperand(
OpIdx, Lane, LastLane, ReorderingModes, MainAltOps[OpIdx]);
// By not selecting a value, we allow the operands that follow to
// select a better matching value. We will get a non-null value in
// the next run of getBestOperand().
if (BestIdx) {
// Swap the current operand with the one returned by
// getBestOperand().
swap(OpIdx, *BestIdx, Lane);
} else {
// We failed to find a best operand, set mode to 'Failed'.
ReorderingModes[OpIdx] = ReorderingMode::Failed;
// Enable the second pass.
StrategyFailed = true;
}
// Try to get the alternate opcode and follow it during analysis.
if (MainAltOps[OpIdx].size() != 2) {
OperandData &AltOp = getData(OpIdx, Lane);
InstructionsState OpS =
getSameOpcode({MainAltOps[OpIdx].front(), AltOp.V}, TLI);
if (OpS.getOpcode() && OpS.isAltShuffle())
MainAltOps[OpIdx].push_back(AltOp.V);
}
}
}
}
// Skip second pass if the strategy did not fail.
if (!StrategyFailed)
break;
}
}
#if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP)
LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) {
switch (RMode) {
case ReorderingMode::Load:
return "Load";
case ReorderingMode::Opcode:
return "Opcode";
case ReorderingMode::Constant:
return "Constant";
case ReorderingMode::Splat:
return "Splat";
case ReorderingMode::Failed:
return "Failed";
}
llvm_unreachable("Unimplemented Reordering Type");
}
LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode,
raw_ostream &OS) {
return OS << getModeStr(RMode);
}
/// Debug print.
LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) {
printMode(RMode, dbgs());
}
friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) {
return printMode(RMode, OS);
}
LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const {
const unsigned Indent = 2;
unsigned Cnt = 0;
for (const OperandDataVec &OpDataVec : OpsVec) {
OS << "Operand " << Cnt++ << "\n";
for (const OperandData &OpData : OpDataVec) {
OS.indent(Indent) << "{";
if (Value *V = OpData.V)
OS << *V;
else
OS << "null";
OS << ", APO:" << OpData.APO << "}\n";
}
OS << "\n";
}
return OS;
}
/// Debug print.
LLVM_DUMP_METHOD void dump() const { print(dbgs()); }
#endif
};
/// Evaluate each pair in \p Candidates and return index into \p Candidates
/// for a pair which have highest score deemed to have best chance to form
/// root of profitable tree to vectorize. Return std::nullopt if no candidate
/// scored above the LookAheadHeuristics::ScoreFail. \param Limit Lower limit
/// of the cost, considered to be good enough score.
std::optional<int>
findBestRootPair(ArrayRef<std::pair<Value *, Value *>> Candidates,
int Limit = LookAheadHeuristics::ScoreFail) {
LookAheadHeuristics LookAhead(*TLI, *DL, *SE, *this, /*NumLanes=*/2,
RootLookAheadMaxDepth);
int BestScore = Limit;
std::optional<int> Index;
for (int I : seq<int>(0, Candidates.size())) {
int Score = LookAhead.getScoreAtLevelRec(Candidates[I].first,
Candidates[I].second,
/*U1=*/nullptr, /*U2=*/nullptr,
/*Level=*/1, std::nullopt);
if (Score > BestScore) {
BestScore = Score;
Index = I;
}
}
return Index;
}
/// Checks if the instruction is marked for deletion.
bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); }
/// Removes an instruction from its block and eventually deletes it.
/// It's like Instruction::eraseFromParent() except that the actual deletion
/// is delayed until BoUpSLP is destructed.
void eraseInstruction(Instruction *I) {
DeletedInstructions.insert(I);
}
/// Checks if the instruction was already analyzed for being possible
/// reduction root.
bool isAnalyzedReductionRoot(Instruction *I) const {
return AnalyzedReductionsRoots.count(I);
}
/// Register given instruction as already analyzed for being possible
/// reduction root.
void analyzedReductionRoot(Instruction *I) {
AnalyzedReductionsRoots.insert(I);
}
/// Checks if the provided list of reduced values was checked already for
/// vectorization.
bool areAnalyzedReductionVals(ArrayRef<Value *> VL) const {
return AnalyzedReductionVals.contains(hash_value(VL));
}
/// Adds the list of reduced values to list of already checked values for the
/// vectorization.
void analyzedReductionVals(ArrayRef<Value *> VL) {
AnalyzedReductionVals.insert(hash_value(VL));
}
/// Clear the list of the analyzed reduction root instructions.
void clearReductionData() {
AnalyzedReductionsRoots.clear();
AnalyzedReductionVals.clear();
}
/// Checks if the given value is gathered in one of the nodes.
bool isAnyGathered(const SmallDenseSet<Value *> &Vals) const {
return any_of(MustGather, [&](Value *V) { return Vals.contains(V); });
}
/// Check if the value is vectorized in the tree.
bool isVectorized(Value *V) const { return getTreeEntry(V); }
~BoUpSLP();
private:
/// Check if the operands on the edges \p Edges of the \p UserTE allows
/// reordering (i.e. the operands can be reordered because they have only one
/// user and reordarable).
/// \param ReorderableGathers List of all gather nodes that require reordering
/// (e.g., gather of extractlements or partially vectorizable loads).
/// \param GatherOps List of gather operand nodes for \p UserTE that require
/// reordering, subset of \p NonVectorized.
bool
canReorderOperands(TreeEntry *UserTE,
SmallVectorImpl<std::pair<unsigned, TreeEntry *>> &Edges,
ArrayRef<TreeEntry *> ReorderableGathers,
SmallVectorImpl<TreeEntry *> &GatherOps);
/// Checks if the given \p TE is a gather node with clustered reused scalars
/// and reorders it per given \p Mask.
void reorderNodeWithReuses(TreeEntry &TE, ArrayRef<int> Mask) const;
/// Returns vectorized operand \p OpIdx of the node \p UserTE from the graph,
/// if any. If it is not vectorized (gather node), returns nullptr.
TreeEntry *getVectorizedOperand(TreeEntry *UserTE, unsigned OpIdx) {
ArrayRef<Value *> VL = UserTE->getOperand(OpIdx);
TreeEntry *TE = nullptr;
const auto *It = find_if(VL, [this, &TE](Value *V) {
TE = getTreeEntry(V);
return TE;
});
if (It != VL.end() && TE->isSame(VL))
return TE;
return nullptr;
}
/// Returns vectorized operand \p OpIdx of the node \p UserTE from the graph,
/// if any. If it is not vectorized (gather node), returns nullptr.
const TreeEntry *getVectorizedOperand(const TreeEntry *UserTE,
unsigned OpIdx) const {
return const_cast<BoUpSLP *>(this)->getVectorizedOperand(
const_cast<TreeEntry *>(UserTE), OpIdx);
}
/// Checks if all users of \p I are the part of the vectorization tree.
bool areAllUsersVectorized(Instruction *I,
ArrayRef<Value *> VectorizedVals) const;
/// Return information about the vector formed for the specified index
/// of a vector of (the same) instruction.
TargetTransformInfo::OperandValueInfo getOperandInfo(ArrayRef<Value *> VL,
unsigned OpIdx);
/// \returns the cost of the vectorizable entry.
InstructionCost getEntryCost(const TreeEntry *E,
ArrayRef<Value *> VectorizedVals,
SmallPtrSetImpl<Value *> &CheckedExtracts);
/// This is the recursive part of buildTree.
void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth,
const EdgeInfo &EI);
/// \returns true if the ExtractElement/ExtractValue instructions in \p VL can
/// be vectorized to use the original vector (or aggregate "bitcast" to a
/// vector) and sets \p CurrentOrder to the identity permutation; otherwise
/// returns false, setting \p CurrentOrder to either an empty vector or a
/// non-identity permutation that allows to reuse extract instructions.
bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue,
SmallVectorImpl<unsigned> &CurrentOrder) const;
/// Vectorize a single entry in the tree.
Value *vectorizeTree(TreeEntry *E);
/// Vectorize a single entry in the tree, the \p Idx-th operand of the entry
/// \p E.
Value *vectorizeOperand(TreeEntry *E, unsigned NodeIdx);
/// Create a new vector from a list of scalar values. Produces a sequence
/// which exploits values reused across lanes, and arranges the inserts
/// for ease of later optimization.
template <typename BVTy, typename ResTy, typename... Args>
ResTy processBuildVector(const TreeEntry *E, Args &...Params);
/// Create a new vector from a list of scalar values. Produces a sequence
/// which exploits values reused across lanes, and arranges the inserts
/// for ease of later optimization.
Value *createBuildVector(const TreeEntry *E);
/// Returns the instruction in the bundle, which can be used as a base point
/// for scheduling. Usually it is the last instruction in the bundle, except
/// for the case when all operands are external (in this case, it is the first
/// instruction in the list).
Instruction &getLastInstructionInBundle(const TreeEntry *E);
/// Checks if the gathered \p VL can be represented as shuffle(s) of previous
/// tree entries.
/// \param TE Tree entry checked for permutation.
/// \param VL List of scalars (a subset of the TE scalar), checked for
/// permutations.
/// \returns ShuffleKind, if gathered values can be represented as shuffles of
/// previous tree entries. \p Mask is filled with the shuffle mask.
std::optional<TargetTransformInfo::ShuffleKind>
isGatherShuffledEntry(const TreeEntry *TE, ArrayRef<Value *> VL,
SmallVectorImpl<int> &Mask,
SmallVectorImpl<const TreeEntry *> &Entries);
/// \returns the scalarization cost for this list of values. Assuming that
/// this subtree gets vectorized, we may need to extract the values from the
/// roots. This method calculates the cost of extracting the values.
/// \param ForPoisonSrc true if initial vector is poison, false otherwise.
InstructionCost getGatherCost(ArrayRef<Value *> VL, bool ForPoisonSrc) const;
/// Set the Builder insert point to one after the last instruction in
/// the bundle
void setInsertPointAfterBundle(const TreeEntry *E);
/// \returns a vector from a collection of scalars in \p VL. if \p Root is not
/// specified, the starting vector value is poison.
Value *gather(ArrayRef<Value *> VL, Value *Root);
/// \returns whether the VectorizableTree is fully vectorizable and will
/// be beneficial even the tree height is tiny.
bool isFullyVectorizableTinyTree(bool ForReduction) const;
/// Reorder commutative or alt operands to get better probability of
/// generating vectorized code.
static void reorderInputsAccordingToOpcode(
ArrayRef<Value *> VL, SmallVectorImpl<Value *> &Left,
SmallVectorImpl<Value *> &Right, const TargetLibraryInfo &TLI,
const DataLayout &DL, ScalarEvolution &SE, const BoUpSLP &R);
/// Helper for `findExternalStoreUsersReorderIndices()`. It iterates over the
/// users of \p TE and collects the stores. It returns the map from the store
/// pointers to the collected stores.
DenseMap<Value *, SmallVector<StoreInst *, 4>>
collectUserStores(const BoUpSLP::TreeEntry *TE) const;
/// Helper for `findExternalStoreUsersReorderIndices()`. It checks if the
/// stores in \p StoresVec can form a vector instruction. If so it returns true
/// and populates \p ReorderIndices with the shuffle indices of the the stores
/// when compared to the sorted vector.
bool canFormVector(const SmallVector<StoreInst *, 4> &StoresVec,
OrdersType &ReorderIndices) const;
/// Iterates through the users of \p TE, looking for scalar stores that can be
/// potentially vectorized in a future SLP-tree. If found, it keeps track of
/// their order and builds an order index vector for each store bundle. It
/// returns all these order vectors found.
/// We run this after the tree has formed, otherwise we may come across user
/// instructions that are not yet in the tree.
SmallVector<OrdersType, 1>
findExternalStoreUsersReorderIndices(TreeEntry *TE) const;
struct TreeEntry {
using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>;
TreeEntry(VecTreeTy &Container) : Container(Container) {}
/// \returns true if the scalars in VL are equal to this entry.
bool isSame(ArrayRef<Value *> VL) const {
auto &&IsSame = [VL](ArrayRef<Value *> Scalars, ArrayRef<int> Mask) {
if (Mask.size() != VL.size() && VL.size() == Scalars.size())
return std::equal(VL.begin(), VL.end(), Scalars.begin());
return VL.size() == Mask.size() &&
std::equal(VL.begin(), VL.end(), Mask.begin(),
[Scalars](Value *V, int Idx) {
return (isa<UndefValue>(V) &&
Idx == PoisonMaskElem) ||
(Idx != PoisonMaskElem && V == Scalars[Idx]);
});
};
if (!ReorderIndices.empty()) {
// TODO: implement matching if the nodes are just reordered, still can
// treat the vector as the same if the list of scalars matches VL
// directly, without reordering.
SmallVector<int> Mask;
inversePermutation(ReorderIndices, Mask);
if (VL.size() == Scalars.size())
return IsSame(Scalars, Mask);
if (VL.size() == ReuseShuffleIndices.size()) {
::addMask(Mask, ReuseShuffleIndices);
return IsSame(Scalars, Mask);
}
return false;
}
return IsSame(Scalars, ReuseShuffleIndices);
}
bool isOperandGatherNode(const EdgeInfo &UserEI) const {
return State == TreeEntry::NeedToGather &&
UserTreeIndices.front().EdgeIdx == UserEI.EdgeIdx &&
UserTreeIndices.front().UserTE == UserEI.UserTE;
}
/// \returns true if current entry has same operands as \p TE.
bool hasEqualOperands(const TreeEntry &TE) const {
if (TE.getNumOperands() != getNumOperands())
return false;
SmallBitVector Used(getNumOperands());
for (unsigned I = 0, E = getNumOperands(); I < E; ++I) {
unsigned PrevCount = Used.count();
for (unsigned K = 0; K < E; ++K) {
if (Used.test(K))
continue;
if (getOperand(K) == TE.getOperand(I)) {
Used.set(K);
break;
}
}
// Check if we actually found the matching operand.
if (PrevCount == Used.count())
return false;
}
return true;
}
/// \return Final vectorization factor for the node. Defined by the total
/// number of vectorized scalars, including those, used several times in the
/// entry and counted in the \a ReuseShuffleIndices, if any.
unsigned getVectorFactor() const {
if (!ReuseShuffleIndices.empty())
return ReuseShuffleIndices.size();
return Scalars.size();
};
/// A vector of scalars.
ValueList Scalars;
/// The Scalars are vectorized into this value. It is initialized to Null.
WeakTrackingVH VectorizedValue = nullptr;
/// Do we need to gather this sequence or vectorize it
/// (either with vector instruction or with scatter/gather
/// intrinsics for store/load)?
enum EntryState { Vectorize, ScatterVectorize, NeedToGather };
EntryState State;
/// Does this sequence require some shuffling?
SmallVector<int, 4> ReuseShuffleIndices;
/// Does this entry require reordering?
SmallVector<unsigned, 4> ReorderIndices;
/// Points back to the VectorizableTree.
///
/// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has
/// to be a pointer and needs to be able to initialize the child iterator.
/// Thus we need a reference back to the container to translate the indices
/// to entries.
VecTreeTy &Container;
/// The TreeEntry index containing the user of this entry. We can actually
/// have multiple users so the data structure is not truly a tree.
SmallVector<EdgeInfo, 1> UserTreeIndices;
/// The index of this treeEntry in VectorizableTree.
int Idx = -1;
private:
/// The operands of each instruction in each lane Operands[op_index][lane].
/// Note: This helps avoid the replication of the code that performs the
/// reordering of operands during buildTree_rec() and vectorizeTree().
SmallVector<ValueList, 2> Operands;
/// The main/alternate instruction.
Instruction *MainOp = nullptr;
Instruction *AltOp = nullptr;
public:
/// Set this bundle's \p OpIdx'th operand to \p OpVL.
void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) {
if (Operands.size() < OpIdx + 1)
Operands.resize(OpIdx + 1);
assert(Operands[OpIdx].empty() && "Already resized?");
assert(OpVL.size() <= Scalars.size() &&
"Number of operands is greater than the number of scalars.");
Operands[OpIdx].resize(OpVL.size());
copy(OpVL, Operands[OpIdx].begin());
}
/// Set the operands of this bundle in their original order.
void setOperandsInOrder() {
assert(Operands.empty() && "Already initialized?");
auto *I0 = cast<Instruction>(Scalars[0]);
Operands.resize(I0->getNumOperands());
unsigned NumLanes = Scalars.size();
for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands();
OpIdx != NumOperands; ++OpIdx) {
Operands[OpIdx].resize(NumLanes);
for (unsigned Lane = 0; Lane != NumLanes; ++Lane) {
auto *I = cast<Instruction>(Scalars[Lane]);
assert(I->getNumOperands() == NumOperands &&
"Expected same number of operands");
Operands[OpIdx][Lane] = I->getOperand(OpIdx);
}
}
}
/// Reorders operands of the node to the given mask \p Mask.
void reorderOperands(ArrayRef<int> Mask) {
for (ValueList &Operand : Operands)
reorderScalars(Operand, Mask);
}
/// \returns the \p OpIdx operand of this TreeEntry.
ValueList &getOperand(unsigned OpIdx) {
assert(OpIdx < Operands.size() && "Off bounds");
return Operands[OpIdx];
}
/// \returns the \p OpIdx operand of this TreeEntry.
ArrayRef<Value *> getOperand(unsigned OpIdx) const {
assert(OpIdx < Operands.size() && "Off bounds");
return Operands[OpIdx];
}
/// \returns the number of operands.
unsigned getNumOperands() const { return Operands.size(); }
/// \return the single \p OpIdx operand.
Value *getSingleOperand(unsigned OpIdx) const {
assert(OpIdx < Operands.size() && "Off bounds");
assert(!Operands[OpIdx].empty() && "No operand available");
return Operands[OpIdx][0];
}
/// Some of the instructions in the list have alternate opcodes.
bool isAltShuffle() const { return MainOp != AltOp; }
bool isOpcodeOrAlt(Instruction *I) const {
unsigned CheckedOpcode = I->getOpcode();
return (getOpcode() == CheckedOpcode ||
getAltOpcode() == CheckedOpcode);
}
/// Chooses the correct key for scheduling data. If \p Op has the same (or
/// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is
/// \p OpValue.
Value *isOneOf(Value *Op) const {
auto *I = dyn_cast<Instruction>(Op);
if (I && isOpcodeOrAlt(I))
return Op;
return MainOp;
}
void setOperations(const InstructionsState &S) {
MainOp = S.MainOp;
AltOp = S.AltOp;
}
Instruction *getMainOp() const {
return MainOp;
}
Instruction *getAltOp() const {
return AltOp;
}
/// The main/alternate opcodes for the list of instructions.
unsigned getOpcode() const {
return MainOp ? MainOp->getOpcode() : 0;
}
unsigned getAltOpcode() const {
return AltOp ? AltOp->getOpcode() : 0;
}
/// When ReuseReorderShuffleIndices is empty it just returns position of \p
/// V within vector of Scalars. Otherwise, try to remap on its reuse index.
int findLaneForValue(Value *V) const {
unsigned FoundLane = std::distance(Scalars.begin(), find(Scalars, V));
assert(FoundLane < Scalars.size() && "Couldn't find extract lane");
if (!ReorderIndices.empty())
FoundLane = ReorderIndices[FoundLane];
assert(FoundLane < Scalars.size() && "Couldn't find extract lane");
if (!ReuseShuffleIndices.empty()) {
FoundLane = std::distance(ReuseShuffleIndices.begin(),
find(ReuseShuffleIndices, FoundLane));
}
return FoundLane;
}
#ifndef NDEBUG
/// Debug printer.
LLVM_DUMP_METHOD void dump() const {
dbgs() << Idx << ".\n";
for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) {
dbgs() << "Operand " << OpI << ":\n";
for (const Value *V : Operands[OpI])
dbgs().indent(2) << *V << "\n";
}
dbgs() << "Scalars: \n";
for (Value *V : Scalars)
dbgs().indent(2) << *V << "\n";
dbgs() << "State: ";
switch (State) {
case Vectorize:
dbgs() << "Vectorize\n";
break;
case ScatterVectorize:
dbgs() << "ScatterVectorize\n";
break;
case NeedToGather:
dbgs() << "NeedToGather\n";
break;
}
dbgs() << "MainOp: ";
if (MainOp)
dbgs() << *MainOp << "\n";
else
dbgs() << "NULL\n";
dbgs() << "AltOp: ";
if (AltOp)
dbgs() << *AltOp << "\n";
else
dbgs() << "NULL\n";
dbgs() << "VectorizedValue: ";
if (VectorizedValue)
dbgs() << *VectorizedValue << "\n";
else
dbgs() << "NULL\n";
dbgs() << "ReuseShuffleIndices: ";
if (ReuseShuffleIndices.empty())
dbgs() << "Empty";
else
for (int ReuseIdx : ReuseShuffleIndices)
dbgs() << ReuseIdx << ", ";
dbgs() << "\n";
dbgs() << "ReorderIndices: ";
for (unsigned ReorderIdx : ReorderIndices)
dbgs() << ReorderIdx << ", ";
dbgs() << "\n";
dbgs() << "UserTreeIndices: ";
for (const auto &EInfo : UserTreeIndices)
dbgs() << EInfo << ", ";
dbgs() << "\n";
}
#endif
};
#ifndef NDEBUG
void dumpTreeCosts(const TreeEntry *E, InstructionCost ReuseShuffleCost,
InstructionCost VecCost, InstructionCost ScalarCost,
StringRef Banner) const {
dbgs() << "SLP: " << Banner << ":\n";
E->dump();
dbgs() << "SLP: Costs:\n";
dbgs() << "SLP: ReuseShuffleCost = " << ReuseShuffleCost << "\n";
dbgs() << "SLP: VectorCost = " << VecCost << "\n";
dbgs() << "SLP: ScalarCost = " << ScalarCost << "\n";
dbgs() << "SLP: ReuseShuffleCost + VecCost - ScalarCost = "
<< ReuseShuffleCost + VecCost - ScalarCost << "\n";
}
#endif
/// Create a new VectorizableTree entry.
TreeEntry *newTreeEntry(ArrayRef<Value *> VL,
std::optional<ScheduleData *> Bundle,
const InstructionsState &S,
const EdgeInfo &UserTreeIdx,
ArrayRef<int> ReuseShuffleIndices = std::nullopt,
ArrayRef<unsigned> ReorderIndices = std::nullopt) {
TreeEntry::EntryState EntryState =
Bundle ? TreeEntry::Vectorize : TreeEntry::NeedToGather;
return newTreeEntry(VL, EntryState, Bundle, S, UserTreeIdx,
ReuseShuffleIndices, ReorderIndices);
}
TreeEntry *newTreeEntry(ArrayRef<Value *> VL,
TreeEntry::EntryState EntryState,
std::optional<ScheduleData *> Bundle,
const InstructionsState &S,
const EdgeInfo &UserTreeIdx,
ArrayRef<int> ReuseShuffleIndices = std::nullopt,
ArrayRef<unsigned> ReorderIndices = std::nullopt) {
assert(((!Bundle && EntryState == TreeEntry::NeedToGather) ||
(Bundle && EntryState != TreeEntry::NeedToGather)) &&
"Need to vectorize gather entry?");
VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree));
TreeEntry *Last = VectorizableTree.back().get();
Last->Idx = VectorizableTree.size() - 1;
Last->State = EntryState;
Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(),
ReuseShuffleIndices.end());
if (ReorderIndices.empty()) {
Last->Scalars.assign(VL.begin(), VL.end());
Last->setOperations(S);
} else {
// Reorder scalars and build final mask.
Last->Scalars.assign(VL.size(), nullptr);
transform(ReorderIndices, Last->Scalars.begin(),
[VL](unsigned Idx) -> Value * {
if (Idx >= VL.size())
return UndefValue::get(VL.front()->getType());
return VL[Idx];
});
InstructionsState S = getSameOpcode(Last->Scalars, *TLI);
Last->setOperations(S);
Last->ReorderIndices.append(ReorderIndices.begin(), ReorderIndices.end());
}
if (Last->State != TreeEntry::NeedToGather) {
for (Value *V : VL) {
assert(!getTreeEntry(V) && "Scalar already in tree!");
ScalarToTreeEntry[V] = Last;
}
// Update the scheduler bundle to point to this TreeEntry.
ScheduleData *BundleMember = *Bundle;
assert((BundleMember || isa<PHINode>(S.MainOp) ||
isVectorLikeInstWithConstOps(S.MainOp) ||
doesNotNeedToSchedule(VL)) &&
"Bundle and VL out of sync");
if (BundleMember) {
for (Value *V : VL) {
if (doesNotNeedToBeScheduled(V))
continue;
assert(BundleMember && "Unexpected end of bundle.");
BundleMember->TE = Last;
BundleMember = BundleMember->NextInBundle;
}
}
assert(!BundleMember && "Bundle and VL out of sync");
} else {
MustGather.insert(VL.begin(), VL.end());
}
if (UserTreeIdx.UserTE)
Last->UserTreeIndices.push_back(UserTreeIdx);
return Last;
}
/// -- Vectorization State --
/// Holds all of the tree entries.
TreeEntry::VecTreeTy VectorizableTree;
#ifndef NDEBUG
/// Debug printer.
LLVM_DUMP_METHOD void dumpVectorizableTree() const {
for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) {
VectorizableTree[Id]->dump();
dbgs() << "\n";
}
}
#endif
TreeEntry *getTreeEntry(Value *V) { return ScalarToTreeEntry.lookup(V); }
const TreeEntry *getTreeEntry(Value *V) const {
return ScalarToTreeEntry.lookup(V);
}
/// Maps a specific scalar to its tree entry.
SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry;
/// Maps a value to the proposed vectorizable size.
SmallDenseMap<Value *, unsigned> InstrElementSize;
/// A list of scalars that we found that we need to keep as scalars.
ValueSet MustGather;
/// A map between the vectorized entries and the last instructions in the
/// bundles. The bundles are built in use order, not in the def order of the
/// instructions. So, we cannot rely directly on the last instruction in the
/// bundle being the last instruction in the program order during
/// vectorization process since the basic blocks are affected, need to
/// pre-gather them before.
DenseMap<const TreeEntry *, Instruction *> EntryToLastInstruction;
/// List of gather nodes, depending on other gather/vector nodes, which should
/// be emitted after the vector instruction emission process to correctly
/// handle order of the vector instructions and shuffles.
SetVector<const TreeEntry *> PostponedGathers;
using ValueToGatherNodesMap =
DenseMap<Value *, SmallPtrSet<const TreeEntry *, 4>>;
ValueToGatherNodesMap ValueToGatherNodes;
/// This POD struct describes one external user in the vectorized tree.
struct ExternalUser {
ExternalUser(Value *S, llvm::User *U, int L)
: Scalar(S), User(U), Lane(L) {}
// Which scalar in our function.
Value *Scalar;
// Which user that uses the scalar.
llvm::User *User;
// Which lane does the scalar belong to.
int Lane;
};
using UserList = SmallVector<ExternalUser, 16>;
/// Checks if two instructions may access the same memory.
///
/// \p Loc1 is the location of \p Inst1. It is passed explicitly because it
/// is invariant in the calling loop.
bool isAliased(const MemoryLocation &Loc1, Instruction *Inst1,
Instruction *Inst2) {
// First check if the result is already in the cache.
AliasCacheKey key = std::make_pair(Inst1, Inst2);
std::optional<bool> &result = AliasCache[key];
if (result) {
return *result;
}
bool aliased = true;
if (Loc1.Ptr && isSimple(Inst1))
aliased = isModOrRefSet(BatchAA.getModRefInfo(Inst2, Loc1));
// Store the result in the cache.
result = aliased;
return aliased;
}
using AliasCacheKey = std::pair<Instruction *, Instruction *>;
/// Cache for alias results.
/// TODO: consider moving this to the AliasAnalysis itself.
DenseMap<AliasCacheKey, std::optional<bool>> AliasCache;
// Cache for pointerMayBeCaptured calls inside AA. This is preserved
// globally through SLP because we don't perform any action which
// invalidates capture results.
BatchAAResults BatchAA;
/// Temporary store for deleted instructions. Instructions will be deleted
/// eventually when the BoUpSLP is destructed. The deferral is required to
/// ensure that there are no incorrect collisions in the AliasCache, which
/// can happen if a new instruction is allocated at the same address as a
/// previously deleted instruction.
DenseSet<Instruction *> DeletedInstructions;
/// Set of the instruction, being analyzed already for reductions.
SmallPtrSet<Instruction *, 16> AnalyzedReductionsRoots;
/// Set of hashes for the list of reduction values already being analyzed.
DenseSet<size_t> AnalyzedReductionVals;
/// A list of values that need to extracted out of the tree.
/// This list holds pairs of (Internal Scalar : External User). External User
/// can be nullptr, it means that this Internal Scalar will be used later,
/// after vectorization.
UserList ExternalUses;
/// Values used only by @llvm.assume calls.
SmallPtrSet<const Value *, 32> EphValues;
/// Holds all of the instructions that we gathered, shuffle instructions and
/// extractelements.
SetVector<Instruction *> GatherShuffleExtractSeq;
/// A list of blocks that we are going to CSE.
SetVector<BasicBlock *> CSEBlocks;
/// Contains all scheduling relevant data for an instruction.
/// A ScheduleData either represents a single instruction or a member of an
/// instruction bundle (= a group of instructions which is combined into a
/// vector instruction).
struct ScheduleData {
// The initial value for the dependency counters. It means that the
// dependencies are not calculated yet.
enum { InvalidDeps = -1 };
ScheduleData() = default;
void init(int BlockSchedulingRegionID, Value *OpVal) {
FirstInBundle = this;
NextInBundle = nullptr;
NextLoadStore = nullptr;
IsScheduled = false;
SchedulingRegionID = BlockSchedulingRegionID;
clearDependencies();
OpValue = OpVal;
TE = nullptr;
}
/// Verify basic self consistency properties
void verify() {
if (hasValidDependencies()) {
assert(UnscheduledDeps <= Dependencies && "invariant");
} else {
assert(UnscheduledDeps == Dependencies && "invariant");
}
if (IsScheduled) {
assert(isSchedulingEntity() &&
"unexpected scheduled state");
for (const ScheduleData *BundleMember = this; BundleMember;
BundleMember = BundleMember->NextInBundle) {
assert(BundleMember->hasValidDependencies() &&
BundleMember->UnscheduledDeps == 0 &&
"unexpected scheduled state");
assert((BundleMember == this || !BundleMember->IsScheduled) &&
"only bundle is marked scheduled");
}
}
assert(Inst->getParent() == FirstInBundle->Inst->getParent() &&
"all bundle members must be in same basic block");
}
/// Returns true if the dependency information has been calculated.
/// Note that depenendency validity can vary between instructions within
/// a single bundle.
bool hasValidDependencies() const { return Dependencies != InvalidDeps; }
/// Returns true for single instructions and for bundle representatives
/// (= the head of a bundle).
bool isSchedulingEntity() const { return FirstInBundle == this; }
/// Returns true if it represents an instruction bundle and not only a
/// single instruction.
bool isPartOfBundle() const {
return NextInBundle != nullptr || FirstInBundle != this || TE;
}
/// Returns true if it is ready for scheduling, i.e. it has no more
/// unscheduled depending instructions/bundles.
bool isReady() const {
assert(isSchedulingEntity() &&
"can't consider non-scheduling entity for ready list");
return unscheduledDepsInBundle() == 0 && !IsScheduled;
}
/// Modifies the number of unscheduled dependencies for this instruction,
/// and returns the number of remaining dependencies for the containing
/// bundle.
int incrementUnscheduledDeps(int Incr) {
assert(hasValidDependencies() &&
"increment of unscheduled deps would be meaningless");
UnscheduledDeps += Incr;
return FirstInBundle->unscheduledDepsInBundle();
}
/// Sets the number of unscheduled dependencies to the number of
/// dependencies.
void resetUnscheduledDeps() {
UnscheduledDeps = Dependencies;
}
/// Clears all dependency information.
void clearDependencies() {
Dependencies = InvalidDeps;
resetUnscheduledDeps();
MemoryDependencies.clear();
ControlDependencies.clear();
}
int unscheduledDepsInBundle() const {
assert(isSchedulingEntity() && "only meaningful on the bundle");
int Sum = 0;
for (const ScheduleData *BundleMember = this; BundleMember;
BundleMember = BundleMember->NextInBundle) {
if (BundleMember->UnscheduledDeps == InvalidDeps)
return InvalidDeps;
Sum += BundleMember->UnscheduledDeps;
}
return Sum;
}
void dump(raw_ostream &os) const {
if (!isSchedulingEntity()) {
os << "/ " << *Inst;
} else if (NextInBundle) {
os << '[' << *Inst;
ScheduleData *SD = NextInBundle;
while (SD) {
os << ';' << *SD->Inst;
SD = SD->NextInBundle;
}
os << ']';
} else {
os << *Inst;
}
}
Instruction *Inst = nullptr;
/// Opcode of the current instruction in the schedule data.
Value *OpValue = nullptr;
/// The TreeEntry that this instruction corresponds to.
TreeEntry *TE = nullptr;
/// Points to the head in an instruction bundle (and always to this for
/// single instructions).
ScheduleData *FirstInBundle = nullptr;
/// Single linked list of all instructions in a bundle. Null if it is a
/// single instruction.
ScheduleData *NextInBundle = nullptr;
/// Single linked list of all memory instructions (e.g. load, store, call)
/// in the block - until the end of the scheduling region.
ScheduleData *NextLoadStore = nullptr;
/// The dependent memory instructions.
/// This list is derived on demand in calculateDependencies().
SmallVector<ScheduleData *, 4> MemoryDependencies;
/// List of instructions which this instruction could be control dependent
/// on. Allowing such nodes to be scheduled below this one could introduce
/// a runtime fault which didn't exist in the original program.
/// ex: this is a load or udiv following a readonly call which inf loops
SmallVector<ScheduleData *, 4> ControlDependencies;
/// This ScheduleData is in the current scheduling region if this matches
/// the current SchedulingRegionID of BlockScheduling.
int SchedulingRegionID = 0;
/// Used for getting a "good" final ordering of instructions.
int SchedulingPriority = 0;
/// The number of dependencies. Constitutes of the number of users of the
/// instruction plus the number of dependent memory instructions (if any).
/// This value is calculated on demand.
/// If InvalidDeps, the number of dependencies is not calculated yet.
int Dependencies = InvalidDeps;
/// The number of dependencies minus the number of dependencies of scheduled
/// instructions. As soon as this is zero, the instruction/bundle gets ready
/// for scheduling.
/// Note that this is negative as long as Dependencies is not calculated.
int UnscheduledDeps = InvalidDeps;
/// True if this instruction is scheduled (or considered as scheduled in the
/// dry-run).
bool IsScheduled = false;
};
#ifndef NDEBUG
friend inline raw_ostream &operator<<(raw_ostream &os,
const BoUpSLP::ScheduleData &SD) {
SD.dump(os);
return os;
}
#endif
friend struct GraphTraits<BoUpSLP *>;
friend struct DOTGraphTraits<BoUpSLP *>;
/// Contains all scheduling data for a basic block.
/// It does not schedules instructions, which are not memory read/write
/// instructions and their operands are either constants, or arguments, or
/// phis, or instructions from others blocks, or their users are phis or from
/// the other blocks. The resulting vector instructions can be placed at the
/// beginning of the basic block without scheduling (if operands does not need
/// to be scheduled) or at the end of the block (if users are outside of the
/// block). It allows to save some compile time and memory used by the
/// compiler.
/// ScheduleData is assigned for each instruction in between the boundaries of
/// the tree entry, even for those, which are not part of the graph. It is
/// required to correctly follow the dependencies between the instructions and
/// their correct scheduling. The ScheduleData is not allocated for the
/// instructions, which do not require scheduling, like phis, nodes with
/// extractelements/insertelements only or nodes with instructions, with
/// uses/operands outside of the block.
struct BlockScheduling {
BlockScheduling(BasicBlock *BB)
: BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {}
void clear() {
ReadyInsts.clear();
ScheduleStart = nullptr;
ScheduleEnd = nullptr;
FirstLoadStoreInRegion = nullptr;
LastLoadStoreInRegion = nullptr;
RegionHasStackSave = false;
// Reduce the maximum schedule region size by the size of the
// previous scheduling run.
ScheduleRegionSizeLimit -= ScheduleRegionSize;
if (ScheduleRegionSizeLimit < MinScheduleRegionSize)
ScheduleRegionSizeLimit = MinScheduleRegionSize;
ScheduleRegionSize = 0;
// Make a new scheduling region, i.e. all existing ScheduleData is not
// in the new region yet.
++SchedulingRegionID;
}
ScheduleData *getScheduleData(Instruction *I) {
if (BB != I->getParent())
// Avoid lookup if can't possibly be in map.
return nullptr;
ScheduleData *SD = ScheduleDataMap.lookup(I);
if (SD && isInSchedulingRegion(SD))
return SD;
return nullptr;
}
ScheduleData *getScheduleData(Value *V) {
if (auto *I = dyn_cast<Instruction>(V))
return getScheduleData(I);
return nullptr;
}
ScheduleData *getScheduleData(Value *V, Value *Key) {
if (V == Key)
return getScheduleData(V);
auto I = ExtraScheduleDataMap.find(V);
if (I != ExtraScheduleDataMap.end()) {
ScheduleData *SD = I->second.lookup(Key);
if (SD && isInSchedulingRegion(SD))
return SD;
}
return nullptr;
}
bool isInSchedulingRegion(ScheduleData *SD) const {
return SD->SchedulingRegionID == SchedulingRegionID;
}
/// Marks an instruction as scheduled and puts all dependent ready
/// instructions into the ready-list.
template <typename ReadyListType>
void schedule(ScheduleData *SD, ReadyListType &ReadyList) {
SD->IsScheduled = true;
LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n");
for (ScheduleData *BundleMember = SD; BundleMember;
BundleMember = BundleMember->NextInBundle) {
if (BundleMember->Inst != BundleMember->OpValue)
continue;
// Handle the def-use chain dependencies.
// Decrement the unscheduled counter and insert to ready list if ready.
auto &&DecrUnsched = [this, &ReadyList](Instruction *I) {
doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) {
if (OpDef && OpDef->hasValidDependencies() &&
OpDef->incrementUnscheduledDeps(-1) == 0) {
// There are no more unscheduled dependencies after
// decrementing, so we can put the dependent instruction
// into the ready list.
ScheduleData *DepBundle = OpDef->FirstInBundle;
assert(!DepBundle->IsScheduled &&
"already scheduled bundle gets ready");
ReadyList.insert(DepBundle);
LLVM_DEBUG(dbgs()
<< "SLP: gets ready (def): " << *DepBundle << "\n");
}
});
};
// If BundleMember is a vector bundle, its operands may have been
// reordered during buildTree(). We therefore need to get its operands
// through the TreeEntry.
if (TreeEntry *TE = BundleMember->TE) {
// Need to search for the lane since the tree entry can be reordered.
int Lane = std::distance(TE->Scalars.begin(),
find(TE->Scalars, BundleMember->Inst));
assert(Lane >= 0 && "Lane not set");
// Since vectorization tree is being built recursively this assertion
// ensures that the tree entry has all operands set before reaching
// this code. Couple of exceptions known at the moment are extracts
// where their second (immediate) operand is not added. Since
// immediates do not affect scheduler behavior this is considered
// okay.
auto *In = BundleMember->Inst;
assert(In &&
(isa<ExtractValueInst, ExtractElementInst>(In) ||
In->getNumOperands() == TE->getNumOperands()) &&
"Missed TreeEntry operands?");
(void)In; // fake use to avoid build failure when assertions disabled
for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands();
OpIdx != NumOperands; ++OpIdx)
if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane]))
DecrUnsched(I);
} else {
// If BundleMember is a stand-alone instruction, no operand reordering
// has taken place, so we directly access its operands.
for (Use &U : BundleMember->Inst->operands())
if (auto *I = dyn_cast<Instruction>(U.get()))
DecrUnsched(I);
}
// Handle the memory dependencies.
for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) {
if (MemoryDepSD->hasValidDependencies() &&
MemoryDepSD->incrementUnscheduledDeps(-1) == 0) {
// There are no more unscheduled dependencies after decrementing,
// so we can put the dependent instruction into the ready list.
ScheduleData *DepBundle = MemoryDepSD->FirstInBundle;
assert(!DepBundle->IsScheduled &&
"already scheduled bundle gets ready");
ReadyList.insert(DepBundle);
LLVM_DEBUG(dbgs()
<< "SLP: gets ready (mem): " << *DepBundle << "\n");
}
}
// Handle the control dependencies.
for (ScheduleData *DepSD : BundleMember->ControlDependencies) {
if (DepSD->incrementUnscheduledDeps(-1) == 0) {
// There are no more unscheduled dependencies after decrementing,
// so we can put the dependent instruction into the ready list.
ScheduleData *DepBundle = DepSD->FirstInBundle;
assert(!DepBundle->IsScheduled &&
"already scheduled bundle gets ready");
ReadyList.insert(DepBundle);
LLVM_DEBUG(dbgs()
<< "SLP: gets ready (ctl): " << *DepBundle << "\n");
}
}
}
}
/// Verify basic self consistency properties of the data structure.
void verify() {
if (!ScheduleStart)
return;
assert(ScheduleStart->getParent() == ScheduleEnd->getParent() &&
ScheduleStart->comesBefore(ScheduleEnd) &&
"Not a valid scheduling region?");
for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) {
auto *SD = getScheduleData(I);
if (!SD)
continue;
assert(isInSchedulingRegion(SD) &&
"primary schedule data not in window?");
assert(isInSchedulingRegion(SD->FirstInBundle) &&
"entire bundle in window!");
(void)SD;
doForAllOpcodes(I, [](ScheduleData *SD) { SD->verify(); });
}
for (auto *SD : ReadyInsts) {
assert(SD->isSchedulingEntity() && SD->isReady() &&
"item in ready list not ready?");
(void)SD;
}
}
void doForAllOpcodes(Value *V,
function_ref<void(ScheduleData *SD)> Action) {
if (ScheduleData *SD = getScheduleData(V))
Action(SD);
auto I = ExtraScheduleDataMap.find(V);
if (I != ExtraScheduleDataMap.end())
for (auto &P : I->second)
if (isInSchedulingRegion(P.second))
Action(P.second);
}
/// Put all instructions into the ReadyList which are ready for scheduling.
template <typename ReadyListType>
void initialFillReadyList(ReadyListType &ReadyList) {
for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) {
doForAllOpcodes(I, [&](ScheduleData *SD) {
if (SD->isSchedulingEntity() && SD->hasValidDependencies() &&
SD->isReady()) {
ReadyList.insert(SD);
LLVM_DEBUG(dbgs()
<< "SLP: initially in ready list: " << *SD << "\n");
}
});
}
}
/// Build a bundle from the ScheduleData nodes corresponding to the
/// scalar instruction for each lane.
ScheduleData *buildBundle(ArrayRef<Value *> VL);
/// Checks if a bundle of instructions can be scheduled, i.e. has no
/// cyclic dependencies. This is only a dry-run, no instructions are
/// actually moved at this stage.
/// \returns the scheduling bundle. The returned Optional value is not
/// std::nullopt if \p VL is allowed to be scheduled.
std::optional<ScheduleData *>
tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP,
const InstructionsState &S);
/// Un-bundles a group of instructions.
void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue);
/// Allocates schedule data chunk.
ScheduleData *allocateScheduleDataChunks();
/// Extends the scheduling region so that V is inside the region.
/// \returns true if the region size is within the limit.
bool extendSchedulingRegion(Value *V, const InstructionsState &S);
/// Initialize the ScheduleData structures for new instructions in the
/// scheduling region.
void initScheduleData(Instruction *FromI, Instruction *ToI,
ScheduleData *PrevLoadStore,
ScheduleData *NextLoadStore);
/// Updates the dependency information of a bundle and of all instructions/
/// bundles which depend on the original bundle.
void calculateDependencies(ScheduleData *SD, bool InsertInReadyList,
BoUpSLP *SLP);
/// Sets all instruction in the scheduling region to un-scheduled.
void resetSchedule();
BasicBlock *BB;
/// Simple memory allocation for ScheduleData.
std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks;
/// The size of a ScheduleData array in ScheduleDataChunks.
int ChunkSize;
/// The allocator position in the current chunk, which is the last entry
/// of ScheduleDataChunks.
int ChunkPos;
/// Attaches ScheduleData to Instruction.
/// Note that the mapping survives during all vectorization iterations, i.e.
/// ScheduleData structures are recycled.
DenseMap<Instruction *, ScheduleData *> ScheduleDataMap;
/// Attaches ScheduleData to Instruction with the leading key.
DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>>
ExtraScheduleDataMap;
/// The ready-list for scheduling (only used for the dry-run).
SetVector<ScheduleData *> ReadyInsts;
/// The first instruction of the scheduling region.
Instruction *ScheduleStart = nullptr;
/// The first instruction _after_ the scheduling region.
Instruction *ScheduleEnd = nullptr;
/// The first memory accessing instruction in the scheduling region
/// (can be null).
ScheduleData *FirstLoadStoreInRegion = nullptr;
/// The last memory accessing instruction in the scheduling region
/// (can be null).
ScheduleData *LastLoadStoreInRegion = nullptr;
/// Is there an llvm.stacksave or llvm.stackrestore in the scheduling
/// region? Used to optimize the dependence calculation for the
/// common case where there isn't.
bool RegionHasStackSave = false;
/// The current size of the scheduling region.
int ScheduleRegionSize = 0;
/// The maximum size allowed for the scheduling region.
int ScheduleRegionSizeLimit = ScheduleRegionSizeBudget;
/// The ID of the scheduling region. For a new vectorization iteration this
/// is incremented which "removes" all ScheduleData from the region.
/// Make sure that the initial SchedulingRegionID is greater than the
/// initial SchedulingRegionID in ScheduleData (which is 0).
int SchedulingRegionID = 1;
};
/// Attaches the BlockScheduling structures to basic blocks.
MapVector<BasicBlock *, std::unique_ptr<BlockScheduling>> BlocksSchedules;
/// Performs the "real" scheduling. Done before vectorization is actually
/// performed in a basic block.
void scheduleBlock(BlockScheduling *BS);
/// List of users to ignore during scheduling and that don't need extracting.
const SmallDenseSet<Value *> *UserIgnoreList = nullptr;
/// A DenseMapInfo implementation for holding DenseMaps and DenseSets of
/// sorted SmallVectors of unsigned.
struct OrdersTypeDenseMapInfo {
static OrdersType getEmptyKey() {
OrdersType V;
V.push_back(~1U);
return V;
}
static OrdersType getTombstoneKey() {
OrdersType V;
V.push_back(~2U);
return V;
}
static unsigned getHashValue(const OrdersType &V) {
return static_cast<unsigned>(hash_combine_range(V.begin(), V.end()));
}
static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) {
return LHS == RHS;
}
};
// Analysis and block reference.
Function *F;
ScalarEvolution *SE;
TargetTransformInfo *TTI;
TargetLibraryInfo *TLI;
LoopInfo *LI;
DominatorTree *DT;
AssumptionCache *AC;
DemandedBits *DB;
const DataLayout *DL;
OptimizationRemarkEmitter *ORE;
unsigned MaxVecRegSize; // This is set by TTI or overridden by cl::opt.
unsigned MinVecRegSize; // Set by cl::opt (default: 128).
/// Instruction builder to construct the vectorized tree.
IRBuilder<> Builder;
/// A map of scalar integer values to the smallest bit width with which they
/// can legally be represented. The values map to (width, signed) pairs,
/// where "width" indicates the minimum bit width and "signed" is True if the
/// value must be signed-extended, rather than zero-extended, back to its
/// original width.
MapVector<Value *, std::pair<uint64_t, bool>> MinBWs;
};
} // end namespace slpvectorizer
template <> struct GraphTraits<BoUpSLP *> {
using TreeEntry = BoUpSLP::TreeEntry;
/// NodeRef has to be a pointer per the GraphWriter.
using NodeRef = TreeEntry *;
using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy;
/// Add the VectorizableTree to the index iterator to be able to return
/// TreeEntry pointers.
struct ChildIteratorType
: public iterator_adaptor_base<
ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> {
ContainerTy &VectorizableTree;
ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W,
ContainerTy &VT)
: ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {}
NodeRef operator*() { return I->UserTE; }
};
static NodeRef getEntryNode(BoUpSLP &R) {
return R.VectorizableTree[0].get();
}
static ChildIteratorType child_begin(NodeRef N) {
return {N->UserTreeIndices.begin(), N->Container};
}
static ChildIteratorType child_end(NodeRef N) {
return {N->UserTreeIndices.end(), N->Container};
}
/// For the node iterator we just need to turn the TreeEntry iterator into a
/// TreeEntry* iterator so that it dereferences to NodeRef.
class nodes_iterator {
using ItTy = ContainerTy::iterator;
ItTy It;
public:
nodes_iterator(const ItTy &It2) : It(It2) {}
NodeRef operator*() { return It->get(); }
nodes_iterator operator++() {
++It;
return *this;
}
bool operator!=(const nodes_iterator &N2) const { return N2.It != It; }
};
static nodes_iterator nodes_begin(BoUpSLP *R) {
return nodes_iterator(R->VectorizableTree.begin());
}
static nodes_iterator nodes_end(BoUpSLP *R) {
return nodes_iterator(R->VectorizableTree.end());
}
static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); }
};
template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits {
using TreeEntry = BoUpSLP::TreeEntry;
DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {}
std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) {
std::string Str;
raw_string_ostream OS(Str);
OS << Entry->Idx << ".\n";
if (isSplat(Entry->Scalars))
OS << "<splat> ";
for (auto *V : Entry->Scalars) {
OS << *V;
if (llvm::any_of(R->ExternalUses, [&](const BoUpSLP::ExternalUser &EU) {
return EU.Scalar == V;
}))
OS << " <extract>";
OS << "\n";
}
return Str;
}
static std::string getNodeAttributes(const TreeEntry *Entry,
const BoUpSLP *) {
if (Entry->State == TreeEntry::NeedToGather)
return "color=red";
if (Entry->State == TreeEntry::ScatterVectorize)
return "color=blue";
return "";
}
};
} // end namespace llvm
BoUpSLP::~BoUpSLP() {
SmallVector<WeakTrackingVH> DeadInsts;
for (auto *I : DeletedInstructions) {
for (Use &U : I->operands()) {
auto *Op = dyn_cast<Instruction>(U.get());
if (Op && !DeletedInstructions.count(Op) && Op->hasOneUser() &&
wouldInstructionBeTriviallyDead(Op, TLI))
DeadInsts.emplace_back(Op);
}
I->dropAllReferences();
}
for (auto *I : DeletedInstructions) {
assert(I->use_empty() &&
"trying to erase instruction with users.");
I->eraseFromParent();
}
// Cleanup any dead scalar code feeding the vectorized instructions
RecursivelyDeleteTriviallyDeadInstructions(DeadInsts, TLI);
#ifdef EXPENSIVE_CHECKS
// If we could guarantee that this call is not extremely slow, we could
// remove the ifdef limitation (see PR47712).
assert(!verifyFunction(*F, &dbgs()));
#endif
}
/// Reorders the given \p Reuses mask according to the given \p Mask. \p Reuses
/// contains original mask for the scalars reused in the node. Procedure
/// transform this mask in accordance with the given \p Mask.
static void reorderReuses(SmallVectorImpl<int> &Reuses, ArrayRef<int> Mask) {
assert(!Mask.empty() && Reuses.size() == Mask.size() &&
"Expected non-empty mask.");
SmallVector<int> Prev(Reuses.begin(), Reuses.end());
Prev.swap(Reuses);
for (unsigned I = 0, E = Prev.size(); I < E; ++I)
if (Mask[I] != PoisonMaskElem)
Reuses[Mask[I]] = Prev[I];
}
/// Reorders the given \p Order according to the given \p Mask. \p Order - is
/// the original order of the scalars. Procedure transforms the provided order
/// in accordance with the given \p Mask. If the resulting \p Order is just an
/// identity order, \p Order is cleared.
static void reorderOrder(SmallVectorImpl<unsigned> &Order, ArrayRef<int> Mask) {
assert(!Mask.empty() && "Expected non-empty mask.");
SmallVector<int> MaskOrder;
if (Order.empty()) {
MaskOrder.resize(Mask.size());
std::iota(MaskOrder.begin(), MaskOrder.end(), 0);
} else {
inversePermutation(Order, MaskOrder);
}
reorderReuses(MaskOrder, Mask);
if (ShuffleVectorInst::isIdentityMask(MaskOrder)) {
Order.clear();
return;
}
Order.assign(Mask.size(), Mask.size());
for (unsigned I = 0, E = Mask.size(); I < E; ++I)
if (MaskOrder[I] != PoisonMaskElem)
Order[MaskOrder[I]] = I;
fixupOrderingIndices(Order);
}
std::optional<BoUpSLP::OrdersType>
BoUpSLP::findReusedOrderedScalars(const BoUpSLP::TreeEntry &TE) {
assert(TE.State == TreeEntry::NeedToGather && "Expected gather node only.");
unsigned NumScalars = TE.Scalars.size();
OrdersType CurrentOrder(NumScalars, NumScalars);
SmallVector<int> Positions;
SmallBitVector UsedPositions(NumScalars);
const TreeEntry *STE = nullptr;
// Try to find all gathered scalars that are gets vectorized in other
// vectorize node. Here we can have only one single tree vector node to
// correctly identify order of the gathered scalars.
for (unsigned I = 0; I < NumScalars; ++I) {
Value *V = TE.Scalars[I];
if (!isa<LoadInst, ExtractElementInst, ExtractValueInst>(V))
continue;
if (const auto *LocalSTE = getTreeEntry(V)) {
if (!STE)
STE = LocalSTE;
else if (STE != LocalSTE)
// Take the order only from the single vector node.
return std::nullopt;
unsigned Lane =
std::distance(STE->Scalars.begin(), find(STE->Scalars, V));
if (Lane >= NumScalars)
return std::nullopt;
if (CurrentOrder[Lane] != NumScalars) {
if (Lane != I)
continue;
UsedPositions.reset(CurrentOrder[Lane]);
}
// The partial identity (where only some elements of the gather node are
// in the identity order) is good.
CurrentOrder[Lane] = I;
UsedPositions.set(I);
}
}
// Need to keep the order if we have a vector entry and at least 2 scalars or
// the vectorized entry has just 2 scalars.
if (STE && (UsedPositions.count() > 1 || STE->Scalars.size() == 2)) {
auto &&IsIdentityOrder = [NumScalars](ArrayRef<unsigned> CurrentOrder) {
for (unsigned I = 0; I < NumScalars; ++I)
if (CurrentOrder[I] != I && CurrentOrder[I] != NumScalars)
return false;
return true;
};
if (IsIdentityOrder(CurrentOrder))
return OrdersType();
auto *It = CurrentOrder.begin();
for (unsigned I = 0; I < NumScalars;) {
if (UsedPositions.test(I)) {
++I;
continue;
}
if (*It == NumScalars) {
*It = I;
++I;
}
++It;
}
return std::move(CurrentOrder);
}
return std::nullopt;
}
namespace {
/// Tracks the state we can represent the loads in the given sequence.
enum class LoadsState { Gather, Vectorize, ScatterVectorize };
} // anonymous namespace
static bool arePointersCompatible(Value *Ptr1, Value *Ptr2,
const TargetLibraryInfo &TLI,
bool CompareOpcodes = true) {
if (getUnderlyingObject(Ptr1) != getUnderlyingObject(Ptr2))
return false;
auto *GEP1 = dyn_cast<GetElementPtrInst>(Ptr1);
if (!GEP1)
return false;
auto *GEP2 = dyn_cast<GetElementPtrInst>(Ptr2);
if (!GEP2)
return false;
return GEP1->getNumOperands() == 2 && GEP2->getNumOperands() == 2 &&
((isConstant(GEP1->getOperand(1)) &&
isConstant(GEP2->getOperand(1))) ||
!CompareOpcodes ||
getSameOpcode({GEP1->getOperand(1), GEP2->getOperand(1)}, TLI)
.getOpcode());
}
/// Checks if the given array of loads can be represented as a vectorized,
/// scatter or just simple gather.
static LoadsState canVectorizeLoads(ArrayRef<Value *> VL, const Value *VL0,
const TargetTransformInfo &TTI,
const DataLayout &DL, ScalarEvolution &SE,
LoopInfo &LI, const TargetLibraryInfo &TLI,
SmallVectorImpl<unsigned> &Order,
SmallVectorImpl<Value *> &PointerOps) {
// Check that a vectorized load would load the same memory as a scalar
// load. For example, we don't want to vectorize loads that are smaller
// than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM
// treats loading/storing it as an i8 struct. If we vectorize loads/stores
// from such a struct, we read/write packed bits disagreeing with the
// unvectorized version.
Type *ScalarTy = VL0->getType();
if (DL.getTypeSizeInBits(ScalarTy) != DL.getTypeAllocSizeInBits(ScalarTy))
return LoadsState::Gather;
// Make sure all loads in the bundle are simple - we can't vectorize
// atomic or volatile loads.
PointerOps.clear();
PointerOps.resize(VL.size());
auto *POIter = PointerOps.begin();
for (Value *V : VL) {
auto *L = cast<LoadInst>(V);
if (!L->isSimple())
return LoadsState::Gather;
*POIter = L->getPointerOperand();
++POIter;
}
Order.clear();
// Check the order of pointer operands or that all pointers are the same.
bool IsSorted = sortPtrAccesses(PointerOps, ScalarTy, DL, SE, Order);
if (IsSorted || all_of(PointerOps, [&](Value *P) {
return arePointersCompatible(P, PointerOps.front(), TLI);
})) {
if (IsSorted) {
Value *Ptr0;
Value *PtrN;
if (Order.empty()) {
Ptr0 = PointerOps.front();
PtrN = PointerOps.back();
} else {
Ptr0 = PointerOps[Order.front()];
PtrN = PointerOps[Order.back()];
}
std::optional<int> Diff =
getPointersDiff(ScalarTy, Ptr0, ScalarTy, PtrN, DL, SE);
// Check that the sorted loads are consecutive.
if (static_cast<unsigned>(*Diff) == VL.size() - 1)
return LoadsState::Vectorize;
}
// TODO: need to improve analysis of the pointers, if not all of them are
// GEPs or have > 2 operands, we end up with a gather node, which just
// increases the cost.
Loop *L = LI.getLoopFor(cast<LoadInst>(VL0)->getParent());
bool ProfitableGatherPointers =
static_cast<unsigned>(count_if(PointerOps, [L](Value *V) {
return L && L->isLoopInvariant(V);
})) <= VL.size() / 2 && VL.size() > 2;
if (ProfitableGatherPointers || all_of(PointerOps, [IsSorted](Value *P) {
auto *GEP = dyn_cast<GetElementPtrInst>(P);
return (IsSorted && !GEP && doesNotNeedToBeScheduled(P)) ||
(GEP && GEP->getNumOperands() == 2);
})) {
Align CommonAlignment = cast<LoadInst>(VL0)->getAlign();
for (Value *V : VL)
CommonAlignment =
std::min(CommonAlignment, cast<LoadInst>(V)->getAlign());
auto *VecTy = FixedVectorType::get(ScalarTy, VL.size());
if (TTI.isLegalMaskedGather(VecTy, CommonAlignment) &&
!TTI.forceScalarizeMaskedGather(VecTy, CommonAlignment))
return LoadsState::ScatterVectorize;
}
}
return LoadsState::Gather;
}
static bool clusterSortPtrAccesses(ArrayRef<Value *> VL, Type *ElemTy,
const DataLayout &DL, ScalarEvolution &SE,
SmallVectorImpl<unsigned> &SortedIndices) {
assert(llvm::all_of(
VL, [](const Value *V) { return V->getType()->isPointerTy(); }) &&
"Expected list of pointer operands.");
// Map from bases to a vector of (Ptr, Offset, OrigIdx), which we insert each
// Ptr into, sort and return the sorted indices with values next to one
// another.
MapVector<Value *, SmallVector<std::tuple<Value *, int, unsigned>>> Bases;
Bases[VL[0]].push_back(std::make_tuple(VL[0], 0U, 0U));
unsigned Cnt = 1;
for (Value *Ptr : VL.drop_front()) {
bool Found = any_of(Bases, [&](auto &Base) {
std::optional<int> Diff =
getPointersDiff(ElemTy, Base.first, ElemTy, Ptr, DL, SE,
/*StrictCheck=*/true);
if (!Diff)
return false;
Base.second.emplace_back(Ptr, *Diff, Cnt++);
return true;
});
if (!Found) {
// If we haven't found enough to usefully cluster, return early.
if (Bases.size() > VL.size() / 2 - 1)
return false;
// Not found already - add a new Base
Bases[Ptr].emplace_back(Ptr, 0, Cnt++);
}
}
// For each of the bases sort the pointers by Offset and check if any of the
// base become consecutively allocated.
bool AnyConsecutive = false;
for (auto &Base : Bases) {
auto &Vec = Base.second;
if (Vec.size() > 1) {
llvm::stable_sort(Vec, [](const std::tuple<Value *, int, unsigned> &X,
const std::tuple<Value *, int, unsigned> &Y) {
return std::get<1>(X) < std::get<1>(Y);
});
int InitialOffset = std::get<1>(Vec[0]);
AnyConsecutive |= all_of(enumerate(Vec), [InitialOffset](const auto &P) {
return std::get<1>(P.value()) == int(P.index()) + InitialOffset;
});
}
}
// Fill SortedIndices array only if it looks worth-while to sort the ptrs.
SortedIndices.clear();
if (!AnyConsecutive)
return false;
for (auto &Base : Bases) {
for (auto &T : Base.second)
SortedIndices.push_back(std::get<2>(T));
}
assert(SortedIndices.size() == VL.size() &&
"Expected SortedIndices to be the size of VL");
return true;
}
std::optional<BoUpSLP::OrdersType>
BoUpSLP::findPartiallyOrderedLoads(const BoUpSLP::TreeEntry &TE) {
assert(TE.State == TreeEntry::NeedToGather && "Expected gather node only.");
Type *ScalarTy = TE.Scalars[0]->getType();
SmallVector<Value *> Ptrs;
Ptrs.reserve(TE.Scalars.size());
for (Value *V : TE.Scalars) {
auto *L = dyn_cast<LoadInst>(V);
if (!L || !L->isSimple())
return std::nullopt;
Ptrs.push_back(L->getPointerOperand());
}
BoUpSLP::OrdersType Order;
if (clusterSortPtrAccesses(Ptrs, ScalarTy, *DL, *SE, Order))
return std::move(Order);
return std::nullopt;
}
/// Check if two insertelement instructions are from the same buildvector.
static bool areTwoInsertFromSameBuildVector(
InsertElementInst *VU, InsertElementInst *V,
function_ref<Value *(InsertElementInst *)> GetBaseOperand) {
// Instructions must be from the same basic blocks.
if (VU->getParent() != V->getParent())
return false;
// Checks if 2 insertelements are from the same buildvector.
if (VU->getType() != V->getType())
return false;
// Multiple used inserts are separate nodes.
if (!VU->hasOneUse() && !V->hasOneUse())
return false;
auto *IE1 = VU;
auto *IE2 = V;
std::optional<unsigned> Idx1 = getInsertIndex(IE1);
std::optional<unsigned> Idx2 = getInsertIndex(IE2);
if (Idx1 == std::nullopt || Idx2 == std::nullopt)
return false;
// Go through the vector operand of insertelement instructions trying to find
// either VU as the original vector for IE2 or V as the original vector for
// IE1.
SmallSet<int, 8> ReusedIdx;
bool IsReusedIdx = false;
do {
if (IE2 == VU && !IE1)
return VU->hasOneUse();
if (IE1 == V && !IE2)
return V->hasOneUse();
if (IE1 && IE1 != V) {
IsReusedIdx |=
!ReusedIdx.insert(getInsertIndex(IE1).value_or(*Idx2)).second;
if ((IE1 != VU && !IE1->hasOneUse()) || IsReusedIdx)
IE1 = nullptr;
else
IE1 = dyn_cast_or_null<InsertElementInst>(GetBaseOperand(IE1));
}
if (IE2 && IE2 != VU) {
IsReusedIdx |=
!ReusedIdx.insert(getInsertIndex(IE2).value_or(*Idx1)).second;
if ((IE2 != V && !IE2->hasOneUse()) || IsReusedIdx)
IE2 = nullptr;
else
IE2 = dyn_cast_or_null<InsertElementInst>(GetBaseOperand(IE2));
}
} while (!IsReusedIdx && (IE1 || IE2));
return false;
}
std::optional<BoUpSLP::OrdersType>
BoUpSLP::getReorderingData(const TreeEntry &TE, bool TopToBottom) {
// No need to reorder if need to shuffle reuses, still need to shuffle the
// node.
if (!TE.ReuseShuffleIndices.empty()) {
// Check if reuse shuffle indices can be improved by reordering.
// For this, check that reuse mask is "clustered", i.e. each scalar values
// is used once in each submask of size <number_of_scalars>.
// Example: 4 scalar values.
// ReuseShuffleIndices mask: 0, 1, 2, 3, 3, 2, 0, 1 - clustered.
// 0, 1, 2, 3, 3, 3, 1, 0 - not clustered, because
// element 3 is used twice in the second submask.
unsigned Sz = TE.Scalars.size();
if (!ShuffleVectorInst::isOneUseSingleSourceMask(TE.ReuseShuffleIndices,
Sz))
return std::nullopt;
unsigned VF = TE.getVectorFactor();
// Try build correct order for extractelement instructions.
SmallVector<int> ReusedMask(TE.ReuseShuffleIndices.begin(),
TE.ReuseShuffleIndices.end());
if (TE.getOpcode() == Instruction::ExtractElement && !TE.isAltShuffle() &&
all_of(TE.Scalars, [Sz](Value *V) {
std::optional<unsigned> Idx = getExtractIndex(cast<Instruction>(V));
return Idx && *Idx < Sz;
})) {
SmallVector<int> ReorderMask(Sz, PoisonMaskElem);
if (TE.ReorderIndices.empty())
std::iota(ReorderMask.begin(), ReorderMask.end(), 0);
else
inversePermutation(TE.ReorderIndices, ReorderMask);
for (unsigned I = 0; I < VF; ++I) {
int &Idx = ReusedMask[I];
if (Idx == PoisonMaskElem)
continue;
Value *V = TE.Scalars[ReorderMask[Idx]];
std::optional<unsigned> EI = getExtractIndex(cast<Instruction>(V));
Idx = std::distance(ReorderMask.begin(), find(ReorderMask, *EI));
}
}
// Build the order of the VF size, need to reorder reuses shuffles, they are
// always of VF size.
OrdersType ResOrder(VF);
std::iota(ResOrder.begin(), ResOrder.end(), 0);
auto *It = ResOrder.begin();
for (unsigned K = 0; K < VF; K += Sz) {
OrdersType CurrentOrder(TE.ReorderIndices);
SmallVector<int> SubMask{ArrayRef(ReusedMask).slice(K, Sz)};
if (SubMask.front() == PoisonMaskElem)
std::iota(SubMask.begin(), SubMask.end(), 0);
reorderOrder(CurrentOrder, SubMask);
transform(CurrentOrder, It, [K](unsigned Pos) { return Pos + K; });
std::advance(It, Sz);
}
if (all_of(enumerate(ResOrder),
[](const auto &Data) { return Data.index() == Data.value(); }))
return std::nullopt; // No need to reorder.
return std::move(ResOrder);
}
if (TE.State == TreeEntry::Vectorize &&
(isa<LoadInst, ExtractElementInst, ExtractValueInst>(TE.getMainOp()) ||
(TopToBottom && isa<StoreInst, InsertElementInst>(TE.getMainOp()))) &&
!TE.isAltShuffle())
return TE.ReorderIndices;
if (TE.State == TreeEntry::Vectorize && TE.getOpcode() == Instruction::PHI) {
auto PHICompare = [](llvm::Value *V1, llvm::Value *V2) {
if (!V1->hasOneUse() || !V2->hasOneUse())
return false;
auto *FirstUserOfPhi1 = cast<Instruction>(*V1->user_begin());
auto *FirstUserOfPhi2 = cast<Instruction>(*V2->user_begin());
if (auto *IE1 = dyn_cast<InsertElementInst>(FirstUserOfPhi1))
if (auto *IE2 = dyn_cast<InsertElementInst>(FirstUserOfPhi2)) {
if (!areTwoInsertFromSameBuildVector(
IE1, IE2,
[](InsertElementInst *II) { return II->getOperand(0); }))
return false;
std::optional<unsigned> Idx1 = getInsertIndex(IE1);
std::optional<unsigned> Idx2 = getInsertIndex(IE2);
if (Idx1 == std::nullopt || Idx2 == std::nullopt)
return false;
return *Idx1 < *Idx2;
}
if (auto *EE1 = dyn_cast<ExtractElementInst>(FirstUserOfPhi1))
if (auto *EE2 = dyn_cast<ExtractElementInst>(FirstUserOfPhi2)) {
if (EE1->getOperand(0) != EE2->getOperand(0))
return false;
std::optional<unsigned> Idx1 = getExtractIndex(EE1);
std::optional<unsigned> Idx2 = getExtractIndex(EE2);
if (Idx1 == std::nullopt || Idx2 == std::nullopt)
return false;
return *Idx1 < *Idx2;
}
return false;
};
auto IsIdentityOrder = [](const OrdersType &Order) {
for (unsigned Idx : seq<unsigned>(0, Order.size()))
if (Idx != Order[Idx])
return false;
return true;
};
if (!TE.ReorderIndices.empty())
return TE.ReorderIndices;
DenseMap<Value *, unsigned> PhiToId;
SmallVector<Value *, 4> Phis;
OrdersType ResOrder(TE.Scalars.size());
for (unsigned Id = 0, Sz = TE.Scalars.size(); Id < Sz; ++Id) {
PhiToId[TE.Scalars[Id]] = Id;
Phis.push_back(TE.Scalars[Id]);
}
llvm::stable_sort(Phis, PHICompare);
for (unsigned Id = 0, Sz = Phis.size(); Id < Sz; ++Id)
ResOrder[Id] = PhiToId[Phis[Id]];
if (IsIdentityOrder(ResOrder))
return std::nullopt; // No need to reorder.
return std::move(ResOrder);
}
if (TE.State == TreeEntry::NeedToGather) {
// TODO: add analysis of other gather nodes with extractelement
// instructions and other values/instructions, not only undefs.
if (((TE.getOpcode() == Instruction::ExtractElement &&
!TE.isAltShuffle()) ||
(all_of(TE.Scalars,
[](Value *V) {
return isa<UndefValue, ExtractElementInst>(V);
}) &&
any_of(TE.Scalars,
[](Value *V) { return isa<ExtractElementInst>(V); }))) &&
all_of(TE.Scalars,
[](Value *V) {
auto *EE = dyn_cast<ExtractElementInst>(V);
return !EE || isa<FixedVectorType>(EE->getVectorOperandType());
}) &&
allSameType(TE.Scalars)) {
// Check that gather of extractelements can be represented as
// just a shuffle of a single vector.
OrdersType CurrentOrder;
bool Reuse = canReuseExtract(TE.Scalars, TE.getMainOp(), CurrentOrder);
if (Reuse || !CurrentOrder.empty()) {
if (!CurrentOrder.empty())
fixupOrderingIndices(CurrentOrder);
return std::move(CurrentOrder);
}
}
// If the gather node is <undef, v, .., poison> and
// insertelement poison, v, 0 [+ permute]
// is cheaper than
// insertelement poison, v, n - try to reorder.
// If rotating the whole graph, exclude the permute cost, the whole graph
// might be transformed.
int Sz = TE.Scalars.size();
if (isSplat(TE.Scalars) && !allConstant(TE.Scalars) &&
count_if(TE.Scalars, UndefValue::classof) == Sz - 1) {
const auto *It =
find_if(TE.Scalars, [](Value *V) { return !isConstant(V); });
if (It == TE.Scalars.begin())
return OrdersType();
auto *Ty = FixedVectorType::get(TE.Scalars.front()->getType(), Sz);
if (It != TE.Scalars.end()) {
OrdersType Order(Sz, Sz);
unsigned Idx = std::distance(TE.Scalars.begin(), It);
Order[Idx] = 0;
fixupOrderingIndices(Order);
SmallVector<int> Mask;
inversePermutation(Order, Mask);
InstructionCost PermuteCost =
TopToBottom
? 0
: TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, Ty, Mask);
InstructionCost InsertFirstCost = TTI->getVectorInstrCost(
Instruction::InsertElement, Ty, TTI::TCK_RecipThroughput, 0,
PoisonValue::get(Ty), *It);
InstructionCost InsertIdxCost = TTI->getVectorInstrCost(
Instruction::InsertElement, Ty, TTI::TCK_RecipThroughput, Idx,
PoisonValue::get(Ty), *It);
if (InsertFirstCost + PermuteCost < InsertIdxCost)
return std::move(Order);
}
}
if (std::optional<OrdersType> CurrentOrder = findReusedOrderedScalars(TE))
return CurrentOrder;
if (TE.Scalars.size() >= 4)
if (std::optional<OrdersType> Order = findPartiallyOrderedLoads(TE))
return Order;
}
return std::nullopt;
}
/// Checks if the given mask is a "clustered" mask with the same clusters of
/// size \p Sz, which are not identity submasks.
static bool isRepeatedNonIdentityClusteredMask(ArrayRef<int> Mask,
unsigned Sz) {
ArrayRef<int> FirstCluster = Mask.slice(0, Sz);
if (ShuffleVectorInst::isIdentityMask(FirstCluster))
return false;
for (unsigned I = Sz, E = Mask.size(); I < E; I += Sz) {
ArrayRef<int> Cluster = Mask.slice(I, Sz);
if (Cluster != FirstCluster)
return false;
}
return true;
}
void BoUpSLP::reorderNodeWithReuses(TreeEntry &TE, ArrayRef<int> Mask) const {
// Reorder reuses mask.
reorderReuses(TE.ReuseShuffleIndices, Mask);
const unsigned Sz = TE.Scalars.size();
// For vectorized and non-clustered reused no need to do anything else.
if (TE.State != TreeEntry::NeedToGather ||
!ShuffleVectorInst::isOneUseSingleSourceMask(TE.ReuseShuffleIndices,
Sz) ||
!isRepeatedNonIdentityClusteredMask(TE.ReuseShuffleIndices, Sz))
return;
SmallVector<int> NewMask;
inversePermutation(TE.ReorderIndices, NewMask);
addMask(NewMask, TE.ReuseShuffleIndices);
// Clear reorder since it is going to be applied to the new mask.
TE.ReorderIndices.clear();
// Try to improve gathered nodes with clustered reuses, if possible.
ArrayRef<int> Slice = ArrayRef(NewMask).slice(0, Sz);
SmallVector<unsigned> NewOrder(Slice.begin(), Slice.end());
inversePermutation(NewOrder, NewMask);
reorderScalars(TE.Scalars, NewMask);
// Fill the reuses mask with the identity submasks.
for (auto *It = TE.ReuseShuffleIndices.begin(),
*End = TE.ReuseShuffleIndices.end();
It != End; std::advance(It, Sz))
std::iota(It, std::next(It, Sz), 0);
}
void BoUpSLP::reorderTopToBottom() {
// Maps VF to the graph nodes.
DenseMap<unsigned, SetVector<TreeEntry *>> VFToOrderedEntries;
// ExtractElement gather nodes which can be vectorized and need to handle
// their ordering.
DenseMap<const TreeEntry *, OrdersType> GathersToOrders;
// Phi nodes can have preferred ordering based on their result users
DenseMap<const TreeEntry *, OrdersType> PhisToOrders;
// AltShuffles can also have a preferred ordering that leads to fewer
// instructions, e.g., the addsub instruction in x86.
DenseMap<const TreeEntry *, OrdersType> AltShufflesToOrders;
// Maps a TreeEntry to the reorder indices of external users.
DenseMap<const TreeEntry *, SmallVector<OrdersType, 1>>
ExternalUserReorderMap;
// FIXME: Workaround for syntax error reported by MSVC buildbots.
TargetTransformInfo &TTIRef = *TTI;
// Find all reorderable nodes with the given VF.
// Currently the are vectorized stores,loads,extracts + some gathering of
// extracts.
for_each(VectorizableTree, [this, &TTIRef, &VFToOrderedEntries,
&GathersToOrders, &ExternalUserReorderMap,
&AltShufflesToOrders, &PhisToOrders](
const std::unique_ptr<TreeEntry> &TE) {
// Look for external users that will probably be vectorized.
SmallVector<OrdersType, 1> ExternalUserReorderIndices =
findExternalStoreUsersReorderIndices(TE.get());
if (!ExternalUserReorderIndices.empty()) {
VFToOrderedEntries[TE->getVectorFactor()].insert(TE.get());
ExternalUserReorderMap.try_emplace(TE.get(),
std::move(ExternalUserReorderIndices));
}
// Patterns like [fadd,fsub] can be combined into a single instruction in
// x86. Reordering them into [fsub,fadd] blocks this pattern. So we need
// to take into account their order when looking for the most used order.
if (TE->isAltShuffle()) {
VectorType *VecTy =
FixedVectorType::get(TE->Scalars[0]->getType(), TE->Scalars.size());
unsigned Opcode0 = TE->getOpcode();
unsigned Opcode1 = TE->getAltOpcode();
// The opcode mask selects between the two opcodes.
SmallBitVector OpcodeMask(TE->Scalars.size(), false);
for (unsigned Lane : seq<unsigned>(0, TE->Scalars.size()))
if (cast<Instruction>(TE->Scalars[Lane])->getOpcode() == Opcode1)
OpcodeMask.set(Lane);
// If this pattern is supported by the target then we consider the order.
if (TTIRef.isLegalAltInstr(VecTy, Opcode0, Opcode1, OpcodeMask)) {
VFToOrderedEntries[TE->getVectorFactor()].insert(TE.get());
AltShufflesToOrders.try_emplace(TE.get(), OrdersType());
}
// TODO: Check the reverse order too.
}
if (std::optional<OrdersType> CurrentOrder =
getReorderingData(*TE, /*TopToBottom=*/true)) {
// Do not include ordering for nodes used in the alt opcode vectorization,
// better to reorder them during bottom-to-top stage. If follow the order
// here, it causes reordering of the whole graph though actually it is
// profitable just to reorder the subgraph that starts from the alternate
// opcode vectorization node. Such nodes already end-up with the shuffle
// instruction and it is just enough to change this shuffle rather than
// rotate the scalars for the whole graph.
unsigned Cnt = 0;
const TreeEntry *UserTE = TE.get();
while (UserTE && Cnt < RecursionMaxDepth) {
if (UserTE->UserTreeIndices.size() != 1)
break;
if (all_of(UserTE->UserTreeIndices, [](const EdgeInfo &EI) {
return EI.UserTE->State == TreeEntry::Vectorize &&
EI.UserTE->isAltShuffle() && EI.UserTE->Idx != 0;
}))
return;
UserTE = UserTE->UserTreeIndices.back().UserTE;
++Cnt;
}
VFToOrderedEntries[TE->getVectorFactor()].insert(TE.get());
if (TE->State != TreeEntry::Vectorize || !TE->ReuseShuffleIndices.empty())
GathersToOrders.try_emplace(TE.get(), *CurrentOrder);
if (TE->State == TreeEntry::Vectorize &&
TE->getOpcode() == Instruction::PHI)
PhisToOrders.try_emplace(TE.get(), *CurrentOrder);
}
});
// Reorder the graph nodes according to their vectorization factor.
for (unsigned VF = VectorizableTree.front()->getVectorFactor(); VF > 1;
VF /= 2) {
auto It = VFToOrderedEntries.find(VF);
if (It == VFToOrderedEntries.end())
continue;
// Try to find the most profitable order. We just are looking for the most
// used order and reorder scalar elements in the nodes according to this
// mostly used order.
ArrayRef<TreeEntry *> OrderedEntries = It->second.getArrayRef();
// All operands are reordered and used only in this node - propagate the
// most used order to the user node.
MapVector<OrdersType, unsigned,
DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo>>
OrdersUses;
SmallPtrSet<const TreeEntry *, 4> VisitedOps;
for (const TreeEntry *OpTE : OrderedEntries) {
// No need to reorder this nodes, still need to extend and to use shuffle,
// just need to merge reordering shuffle and the reuse shuffle.
if (!OpTE->ReuseShuffleIndices.empty() && !GathersToOrders.count(OpTE))
continue;
// Count number of orders uses.
const auto &Order = [OpTE, &GathersToOrders, &AltShufflesToOrders,
&PhisToOrders]() -> const OrdersType & {
if (OpTE->State == TreeEntry::NeedToGather ||
!OpTE->ReuseShuffleIndices.empty()) {
auto It = GathersToOrders.find(OpTE);
if (It != GathersToOrders.end())
return It->second;
}
if (OpTE->isAltShuffle()) {
auto It = AltShufflesToOrders.find(OpTE);
if (It != AltShufflesToOrders.end())
return It->second;
}
if (OpTE->State == TreeEntry::Vectorize &&
OpTE->getOpcode() == Instruction::PHI) {
auto It = PhisToOrders.find(OpTE);
if (It != PhisToOrders.end())
return It->second;
}
return OpTE->ReorderIndices;
}();
// First consider the order of the external scalar users.
auto It = ExternalUserReorderMap.find(OpTE);
if (It != ExternalUserReorderMap.end()) {
const auto &ExternalUserReorderIndices = It->second;
// If the OpTE vector factor != number of scalars - use natural order,
// it is an attempt to reorder node with reused scalars but with
// external uses.
if (OpTE->getVectorFactor() != OpTE->Scalars.size()) {
OrdersUses.insert(std::make_pair(OrdersType(), 0)).first->second +=
ExternalUserReorderIndices.size();
} else {
for (const OrdersType &ExtOrder : ExternalUserReorderIndices)
++OrdersUses.insert(std::make_pair(ExtOrder, 0)).first->second;
}
// No other useful reorder data in this entry.
if (Order.empty())
continue;
}
// Stores actually store the mask, not the order, need to invert.
if (OpTE->State == TreeEntry::Vectorize && !OpTE->isAltShuffle() &&
OpTE->getOpcode() == Instruction::Store && !Order.empty()) {
SmallVector<int> Mask;
inversePermutation(Order, Mask);
unsigned E = Order.size();
OrdersType CurrentOrder(E, E);
transform(Mask, CurrentOrder.begin(), [E](int Idx) {
return Idx == PoisonMaskElem ? E : static_cast<unsigned>(Idx);
});
fixupOrderingIndices(CurrentOrder);
++OrdersUses.insert(std::make_pair(CurrentOrder, 0)).first->second;
} else {
++OrdersUses.insert(std::make_pair(Order, 0)).first->second;
}
}
// Set order of the user node.
if (OrdersUses.empty())
continue;
// Choose the most used order.
ArrayRef<unsigned> BestOrder = OrdersUses.front().first;
unsigned Cnt = OrdersUses.front().second;
for (const auto &Pair : drop_begin(OrdersUses)) {
if (Cnt < Pair.second || (Cnt == Pair.second && Pair.first.empty())) {
BestOrder = Pair.first;
Cnt = Pair.second;
}
}
// Set order of the user node.
if (BestOrder.empty())
continue;
SmallVector<int> Mask;
inversePermutation(BestOrder, Mask);
SmallVector<int> MaskOrder(BestOrder.size(), PoisonMaskElem);
unsigned E = BestOrder.size();
transform(BestOrder, MaskOrder.begin(), [E](unsigned I) {
return I < E ? static_cast<int>(I) : PoisonMaskElem;
});
// Do an actual reordering, if profitable.
for (std::unique_ptr<TreeEntry> &TE : VectorizableTree) {
// Just do the reordering for the nodes with the given VF.
if (TE->Scalars.size() != VF) {
if (TE->ReuseShuffleIndices.size() == VF) {
// Need to reorder the reuses masks of the operands with smaller VF to
// be able to find the match between the graph nodes and scalar
// operands of the given node during vectorization/cost estimation.
assert(all_of(TE->UserTreeIndices,
[VF, &TE](const EdgeInfo &EI) {
return EI.UserTE->Scalars.size() == VF ||
EI.UserTE->Scalars.size() ==
TE->Scalars.size();
}) &&
"All users must be of VF size.");
// Update ordering of the operands with the smaller VF than the given
// one.
reorderNodeWithReuses(*TE, Mask);
}
continue;
}
if (TE->State == TreeEntry::Vectorize &&
isa<ExtractElementInst, ExtractValueInst, LoadInst, StoreInst,
InsertElementInst>(TE->getMainOp()) &&
!TE->isAltShuffle()) {
// Build correct orders for extract{element,value}, loads and
// stores.
reorderOrder(TE->ReorderIndices, Mask);
if (isa<InsertElementInst, StoreInst>(TE->getMainOp()))
TE->reorderOperands(Mask);
} else {
// Reorder the node and its operands.
TE->reorderOperands(Mask);
assert(TE->ReorderIndices.empty() &&
"Expected empty reorder sequence.");
reorderScalars(TE->Scalars, Mask);
}
if (!TE->ReuseShuffleIndices.empty()) {
// Apply reversed order to keep the original ordering of the reused
// elements to avoid extra reorder indices shuffling.
OrdersType CurrentOrder;
reorderOrder(CurrentOrder, MaskOrder);
SmallVector<int> NewReuses;
inversePermutation(CurrentOrder, NewReuses);
addMask(NewReuses, TE->ReuseShuffleIndices);
TE->ReuseShuffleIndices.swap(NewReuses);
}
}
}
}
bool BoUpSLP::canReorderOperands(
TreeEntry *UserTE, SmallVectorImpl<std::pair<unsigned, TreeEntry *>> &Edges,
ArrayRef<TreeEntry *> ReorderableGathers,
SmallVectorImpl<TreeEntry *> &GatherOps) {
for (unsigned I = 0, E = UserTE->getNumOperands(); I < E; ++I) {
if (any_of(Edges, [I](const std::pair<unsigned, TreeEntry *> &OpData) {
return OpData.first == I &&
OpData.second->State == TreeEntry::Vectorize;
}))
continue;
if (TreeEntry *TE = getVectorizedOperand(UserTE, I)) {
// Do not reorder if operand node is used by many user nodes.
if (any_of(TE->UserTreeIndices,
[UserTE](const EdgeInfo &EI) { return EI.UserTE != UserTE; }))
return false;
// Add the node to the list of the ordered nodes with the identity
// order.
Edges.emplace_back(I, TE);
// Add ScatterVectorize nodes to the list of operands, where just
// reordering of the scalars is required. Similar to the gathers, so
// simply add to the list of gathered ops.
// If there are reused scalars, process this node as a regular vectorize
// node, just reorder reuses mask.
if (TE->State != TreeEntry::Vectorize && TE->ReuseShuffleIndices.empty())
GatherOps.push_back(TE);
continue;
}
TreeEntry *Gather = nullptr;
if (count_if(ReorderableGathers,
[&Gather, UserTE, I](TreeEntry *TE) {
assert(TE->State != TreeEntry::Vectorize &&
"Only non-vectorized nodes are expected.");
if (any_of(TE->UserTreeIndices,
[UserTE, I](const EdgeInfo &EI) {
return EI.UserTE == UserTE && EI.EdgeIdx == I;
})) {
assert(TE->isSame(UserTE->getOperand(I)) &&
"Operand entry does not match operands.");
Gather = TE;
return true;
}
return false;
}) > 1 &&
!allConstant(UserTE->getOperand(I)))
return false;
if (Gather)
GatherOps.push_back(Gather);
}
return true;
}
void BoUpSLP::reorderBottomToTop(bool IgnoreReorder) {
SetVector<TreeEntry *> OrderedEntries;
DenseMap<const TreeEntry *, OrdersType> GathersToOrders;
// Find all reorderable leaf nodes with the given VF.
// Currently the are vectorized loads,extracts without alternate operands +
// some gathering of extracts.
SmallVector<TreeEntry *> NonVectorized;
for_each(VectorizableTree, [this, &OrderedEntries, &GathersToOrders,
&NonVectorized](
const std::unique_ptr<TreeEntry> &TE) {
if (TE->State != TreeEntry::Vectorize)
NonVectorized.push_back(TE.get());
if (std::optional<OrdersType> CurrentOrder =
getReorderingData(*TE, /*TopToBottom=*/false)) {
OrderedEntries.insert(TE.get());
if (TE->State != TreeEntry::Vectorize || !TE->ReuseShuffleIndices.empty())
GathersToOrders.try_emplace(TE.get(), *CurrentOrder);
}
});
// 1. Propagate order to the graph nodes, which use only reordered nodes.
// I.e., if the node has operands, that are reordered, try to make at least
// one operand order in the natural order and reorder others + reorder the
// user node itself.
SmallPtrSet<const TreeEntry *, 4> Visited;
while (!OrderedEntries.empty()) {
// 1. Filter out only reordered nodes.
// 2. If the entry has multiple uses - skip it and jump to the next node.
DenseMap<TreeEntry *, SmallVector<std::pair<unsigned, TreeEntry *>>> Users;
SmallVector<TreeEntry *> Filtered;
for (TreeEntry *TE : OrderedEntries) {
if (!(TE->State == TreeEntry::Vectorize ||
(TE->State == TreeEntry::NeedToGather &&
GathersToOrders.count(TE))) ||
TE->UserTreeIndices.empty() || !TE->ReuseShuffleIndices.empty() ||
!all_of(drop_begin(TE->UserTreeIndices),
[TE](const EdgeInfo &EI) {
return EI.UserTE == TE->UserTreeIndices.front().UserTE;
}) ||
!Visited.insert(TE).second) {
Filtered.push_back(TE);
continue;
}
// Build a map between user nodes and their operands order to speedup
// search. The graph currently does not provide this dependency directly.
for (EdgeInfo &EI : TE->UserTreeIndices) {
TreeEntry *UserTE = EI.UserTE;
auto It = Users.find(UserTE);
if (It == Users.end())
It = Users.insert({UserTE, {}}).first;
It->second.emplace_back(EI.EdgeIdx, TE);
}
}
// Erase filtered entries.
for_each(Filtered,
[&OrderedEntries](TreeEntry *TE) { OrderedEntries.remove(TE); });
SmallVector<
std::pair<TreeEntry *, SmallVector<std::pair<unsigned, TreeEntry *>>>>
UsersVec(Users.begin(), Users.end());
sort(UsersVec, [](const auto &Data1, const auto &Data2) {
return Data1.first->Idx > Data2.first->Idx;
});
for (auto &Data : UsersVec) {
// Check that operands are used only in the User node.
SmallVector<TreeEntry *> GatherOps;
if (!canReorderOperands(Data.first, Data.second, NonVectorized,
GatherOps)) {
for_each(Data.second,
[&OrderedEntries](const std::pair<unsigned, TreeEntry *> &Op) {
OrderedEntries.remove(Op.second);
});
continue;
}
// All operands are reordered and used only in this node - propagate the
// most used order to the user node.
MapVector<OrdersType, unsigned,
DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo>>
OrdersUses;
// Do the analysis for each tree entry only once, otherwise the order of
// the same node my be considered several times, though might be not
// profitable.
SmallPtrSet<const TreeEntry *, 4> VisitedOps;
SmallPtrSet<const TreeEntry *, 4> VisitedUsers;
for (const auto &Op : Data.second) {
TreeEntry *OpTE = Op.second;
if (!VisitedOps.insert(OpTE).second)
continue;
if (!OpTE->ReuseShuffleIndices.empty() && !GathersToOrders.count(OpTE))
continue;
const auto &Order = [OpTE, &GathersToOrders]() -> const OrdersType & {
if (OpTE->State == TreeEntry::NeedToGather ||
!OpTE->ReuseShuffleIndices.empty())
return GathersToOrders.find(OpTE)->second;
return OpTE->ReorderIndices;
}();
unsigned NumOps = count_if(
Data.second, [OpTE](const std::pair<unsigned, TreeEntry *> &P) {
return P.second == OpTE;
});
// Stores actually store the mask, not the order, need to invert.
if (OpTE->State == TreeEntry::Vectorize && !OpTE->isAltShuffle() &&
OpTE->getOpcode() == Instruction::Store && !Order.empty()) {
SmallVector<int> Mask;
inversePermutation(Order, Mask);
unsigned E = Order.size();
OrdersType CurrentOrder(E, E);
transform(Mask, CurrentOrder.begin(), [E](int Idx) {
return Idx == PoisonMaskElem ? E : static_cast<unsigned>(Idx);
});
fixupOrderingIndices(CurrentOrder);
OrdersUses.insert(std::make_pair(CurrentOrder, 0)).first->second +=
NumOps;
} else {
OrdersUses.insert(std::make_pair(Order, 0)).first->second += NumOps;
}
auto Res = OrdersUses.insert(std::make_pair(OrdersType(), 0));
const auto &&AllowsReordering = [IgnoreReorder, &GathersToOrders](
const TreeEntry *TE) {
if (!TE->ReorderIndices.empty() || !TE->ReuseShuffleIndices.empty() ||
(TE->State == TreeEntry::Vectorize && TE->isAltShuffle()) ||
(IgnoreReorder && TE->Idx == 0))
return true;
if (TE->State == TreeEntry::NeedToGather) {
auto It = GathersToOrders.find(TE);
if (It != GathersToOrders.end())
return !It->second.empty();
return true;
}
return false;
};
for (const EdgeInfo &EI : OpTE->UserTreeIndices) {
TreeEntry *UserTE = EI.UserTE;
if (!VisitedUsers.insert(UserTE).second)
continue;
// May reorder user node if it requires reordering, has reused
// scalars, is an alternate op vectorize node or its op nodes require
// reordering.
if (AllowsReordering(UserTE))
continue;
// Check if users allow reordering.
// Currently look up just 1 level of operands to avoid increase of
// the compile time.
// Profitable to reorder if definitely more operands allow
// reordering rather than those with natural order.
ArrayRef<std::pair<unsigned, TreeEntry *>> Ops = Users[UserTE];
if (static_cast<unsigned>(count_if(
Ops, [UserTE, &AllowsReordering](
const std::pair<unsigned, TreeEntry *> &Op) {
return AllowsReordering(Op.second) &&
all_of(Op.second->UserTreeIndices,
[UserTE](const EdgeInfo &EI) {
return EI.UserTE == UserTE;
});
})) <= Ops.size() / 2)
++Res.first->second;
}
}
// If no orders - skip current nodes and jump to the next one, if any.
if (OrdersUses.empty()) {
for_each(Data.second,
[&OrderedEntries](const std::pair<unsigned, TreeEntry *> &Op) {
OrderedEntries.remove(Op.second);
});
continue;
}
// Choose the best order.
ArrayRef<unsigned> BestOrder = OrdersUses.front().first;
unsigned Cnt = OrdersUses.front().second;
for (const auto &Pair : drop_begin(OrdersUses)) {
if (Cnt < Pair.second || (Cnt == Pair.second && Pair.first.empty())) {
BestOrder = Pair.first;
Cnt = Pair.second;
}
}
// Set order of the user node (reordering of operands and user nodes).
if (BestOrder.empty()) {
for_each(Data.second,
[&OrderedEntries](const std::pair<unsigned, TreeEntry *> &Op) {
OrderedEntries.remove(Op.second);
});
continue;
}
// Erase operands from OrderedEntries list and adjust their orders.
VisitedOps.clear();
SmallVector<int> Mask;
inversePermutation(BestOrder, Mask);
SmallVector<int> MaskOrder(BestOrder.size(), PoisonMaskElem);
unsigned E = BestOrder.size();
transform(BestOrder, MaskOrder.begin(), [E](unsigned I) {
return I < E ? static_cast<int>(I) : PoisonMaskElem;
});
for (const std::pair<unsigned, TreeEntry *> &Op : Data.second) {
TreeEntry *TE = Op.second;
OrderedEntries.remove(TE);
if (!VisitedOps.insert(TE).second)
continue;
if (TE->ReuseShuffleIndices.size() == BestOrder.size()) {
reorderNodeWithReuses(*TE, Mask);
continue;
}
// Gathers are processed separately.
if (TE->State != TreeEntry::Vectorize)
continue;
assert((BestOrder.size() == TE->ReorderIndices.size() ||
TE->ReorderIndices.empty()) &&
"Non-matching sizes of user/operand entries.");
reorderOrder(TE->ReorderIndices, Mask);
if (IgnoreReorder && TE == VectorizableTree.front().get())
IgnoreReorder = false;
}
// For gathers just need to reorder its scalars.
for (TreeEntry *Gather : GatherOps) {
assert(Gather->ReorderIndices.empty() &&
"Unexpected reordering of gathers.");
if (!Gather->ReuseShuffleIndices.empty()) {
// Just reorder reuses indices.
reorderReuses(Gather->ReuseShuffleIndices, Mask);
continue;
}
reorderScalars(Gather->Scalars, Mask);
OrderedEntries.remove(Gather);
}
// Reorder operands of the user node and set the ordering for the user
// node itself.
if (Data.first->State != TreeEntry::Vectorize ||
!isa<ExtractElementInst, ExtractValueInst, LoadInst>(
Data.first->getMainOp()) ||
Data.first->isAltShuffle())
Data.first->reorderOperands(Mask);
if (!isa<InsertElementInst, StoreInst>(Data.first->getMainOp()) ||
Data.first->isAltShuffle()) {
reorderScalars(Data.first->Scalars, Mask);
reorderOrder(Data.first->ReorderIndices, MaskOrder);
if (Data.first->ReuseShuffleIndices.empty() &&
!Data.first->ReorderIndices.empty() &&
!Data.first->isAltShuffle()) {
// Insert user node to the list to try to sink reordering deeper in
// the graph.
OrderedEntries.insert(Data.first);
}
} else {
reorderOrder(Data.first->ReorderIndices, Mask);
}
}
}
// If the reordering is unnecessary, just remove the reorder.
if (IgnoreReorder && !VectorizableTree.front()->ReorderIndices.empty() &&
VectorizableTree.front()->ReuseShuffleIndices.empty())
VectorizableTree.front()->ReorderIndices.clear();
}
void BoUpSLP::buildExternalUses(
const ExtraValueToDebugLocsMap &ExternallyUsedValues) {
// Collect the values that we need to extract from the tree.
for (auto &TEPtr : VectorizableTree) {
TreeEntry *Entry = TEPtr.get();
// No need to handle users of gathered values.
if (Entry->State == TreeEntry::NeedToGather)
continue;
// For each lane:
for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) {
Value *Scalar = Entry->Scalars[Lane];
int FoundLane = Entry->findLaneForValue(Scalar);
// Check if the scalar is externally used as an extra arg.
auto ExtI = ExternallyUsedValues.find(Scalar);
if (ExtI != ExternallyUsedValues.end()) {
LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane "
<< Lane << " from " << *Scalar << ".\n");
ExternalUses.emplace_back(Scalar, nullptr, FoundLane);
}
for (User *U : Scalar->users()) {
LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n");
Instruction *UserInst = dyn_cast<Instruction>(U);
if (!UserInst)
continue;
if (isDeleted(UserInst))
continue;
// Skip in-tree scalars that become vectors
if (TreeEntry *UseEntry = getTreeEntry(U)) {
Value *UseScalar = UseEntry->Scalars[0];
// Some in-tree scalars will remain as scalar in vectorized
// instructions. If that is the case, the one in Lane 0 will
// be used.
if (UseScalar != U ||
UseEntry->State == TreeEntry::ScatterVectorize ||
!InTreeUserNeedToExtract(Scalar, UserInst, TLI)) {
LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U
<< ".\n");
assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state");
continue;
}
}
// Ignore users in the user ignore list.
if (UserIgnoreList && UserIgnoreList->contains(UserInst))
continue;
LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane "
<< Lane << " from " << *Scalar << ".\n");
ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane));
}
}
}
}
DenseMap<Value *, SmallVector<StoreInst *, 4>>
BoUpSLP::collectUserStores(const BoUpSLP::TreeEntry *TE) const {
DenseMap<Value *, SmallVector<StoreInst *, 4>> PtrToStoresMap;
for (unsigned Lane : seq<unsigned>(0, TE->Scalars.size())) {
Value *V = TE->Scalars[Lane];
// To save compilation time we don't visit if we have too many users.
static constexpr unsigned UsersLimit = 4;
if (V->hasNUsesOrMore(UsersLimit))
break;
// Collect stores per pointer object.
for (User *U : V->users()) {
auto *SI = dyn_cast<StoreInst>(U);
if (SI == nullptr || !SI->isSimple() ||
!isValidElementType(SI->getValueOperand()->getType()))
continue;
// Skip entry if already
if (getTreeEntry(U))
continue;
Value *Ptr = getUnderlyingObject(SI->getPointerOperand());
auto &StoresVec = PtrToStoresMap[Ptr];
// For now just keep one store per pointer object per lane.
// TODO: Extend this to support multiple stores per pointer per lane
if (StoresVec.size() > Lane)
continue;
// Skip if in different BBs.
if (!StoresVec.empty() &&
SI->getParent() != StoresVec.back()->getParent())
continue;
// Make sure that the stores are of the same type.
if (!StoresVec.empty() &&
SI->getValueOperand()->getType() !=
StoresVec.back()->getValueOperand()->getType())
continue;
StoresVec.push_back(SI);
}
}
return PtrToStoresMap;
}
bool BoUpSLP::canFormVector(const SmallVector<StoreInst *, 4> &StoresVec,
OrdersType &ReorderIndices) const {
// We check whether the stores in StoreVec can form a vector by sorting them
// and checking whether they are consecutive.
// To avoid calling getPointersDiff() while sorting we create a vector of
// pairs {store, offset from first} and sort this instead.
SmallVector<std::pair<StoreInst *, int>, 4> StoreOffsetVec(StoresVec.size());
StoreInst *S0 = StoresVec[0];
StoreOffsetVec[0] = {S0, 0};
Type *S0Ty = S0->getValueOperand()->getType();
Value *S0Ptr = S0->getPointerOperand();
for (unsigned Idx : seq<unsigned>(1, StoresVec.size())) {
StoreInst *SI = StoresVec[Idx];
std::optional<int> Diff =
getPointersDiff(S0Ty, S0Ptr, SI->getValueOperand()->getType(),
SI->getPointerOperand(), *DL, *SE,
/*StrictCheck=*/true);
// We failed to compare the pointers so just abandon this StoresVec.
if (!Diff)
return false;
StoreOffsetVec[Idx] = {StoresVec[Idx], *Diff};
}
// Sort the vector based on the pointers. We create a copy because we may
// need the original later for calculating the reorder (shuffle) indices.
stable_sort(StoreOffsetVec, [](const std::pair<StoreInst *, int> &Pair1,
const std::pair<StoreInst *, int> &Pair2) {
int Offset1 = Pair1.second;
int Offset2 = Pair2.second;
return Offset1 < Offset2;
});
// Check if the stores are consecutive by checking if their difference is 1.
for (unsigned Idx : seq<unsigned>(1, StoreOffsetVec.size()))
if (StoreOffsetVec[Idx].second != StoreOffsetVec[Idx-1].second + 1)
return false;
// Calculate the shuffle indices according to their offset against the sorted
// StoreOffsetVec.
ReorderIndices.reserve(StoresVec.size());
for (StoreInst *SI : StoresVec) {
unsigned Idx = find_if(StoreOffsetVec,
[SI](const std::pair<StoreInst *, int> &Pair) {
return Pair.first == SI;
}) -
StoreOffsetVec.begin();
ReorderIndices.push_back(Idx);
}
// Identity order (e.g., {0,1,2,3}) is modeled as an empty OrdersType in
// reorderTopToBottom() and reorderBottomToTop(), so we are following the
// same convention here.
auto IsIdentityOrder = [](const OrdersType &Order) {
for (unsigned Idx : seq<unsigned>(0, Order.size()))
if (Idx != Order[Idx])
return false;
return true;
};
if (IsIdentityOrder(ReorderIndices))
ReorderIndices.clear();
return true;
}
#ifndef NDEBUG
LLVM_DUMP_METHOD static void dumpOrder(const BoUpSLP::OrdersType &Order) {
for (unsigned Idx : Order)
dbgs() << Idx << ", ";
dbgs() << "\n";
}
#endif
SmallVector<BoUpSLP::OrdersType, 1>
BoUpSLP::findExternalStoreUsersReorderIndices(TreeEntry *TE) const {
unsigned NumLanes = TE->Scalars.size();
DenseMap<Value *, SmallVector<StoreInst *, 4>> PtrToStoresMap =
collectUserStores(TE);
// Holds the reorder indices for each candidate store vector that is a user of
// the current TreeEntry.
SmallVector<OrdersType, 1> ExternalReorderIndices;
// Now inspect the stores collected per pointer and look for vectorization
// candidates. For each candidate calculate the reorder index vector and push
// it into `ExternalReorderIndices`
for (const auto &Pair : PtrToStoresMap) {
auto &StoresVec = Pair.second;
// If we have fewer than NumLanes stores, then we can't form a vector.
if (StoresVec.size() != NumLanes)
continue;
// If the stores are not consecutive then abandon this StoresVec.
OrdersType ReorderIndices;
if (!canFormVector(StoresVec, ReorderIndices))
continue;
// We now know that the scalars in StoresVec can form a vector instruction,
// so set the reorder indices.
ExternalReorderIndices.push_back(ReorderIndices);
}
return ExternalReorderIndices;
}
void BoUpSLP::buildTree(ArrayRef<Value *> Roots,
const SmallDenseSet<Value *> &UserIgnoreLst) {
deleteTree();
UserIgnoreList = &UserIgnoreLst;
if (!allSameType(Roots))
return;
buildTree_rec(Roots, 0, EdgeInfo());
}
void BoUpSLP::buildTree(ArrayRef<Value *> Roots) {
deleteTree();
if (!allSameType(Roots))
return;
buildTree_rec(Roots, 0, EdgeInfo());
}
/// \return true if the specified list of values has only one instruction that
/// requires scheduling, false otherwise.
#ifndef NDEBUG
static bool needToScheduleSingleInstruction(ArrayRef<Value *> VL) {
Value *NeedsScheduling = nullptr;
for (Value *V : VL) {
if (doesNotNeedToBeScheduled(V))
continue;
if (!NeedsScheduling) {
NeedsScheduling = V;
continue;
}
return false;
}
return NeedsScheduling;
}
#endif
/// Generates key/subkey pair for the given value to provide effective sorting
/// of the values and better detection of the vectorizable values sequences. The
/// keys/subkeys can be used for better sorting of the values themselves (keys)
/// and in values subgroups (subkeys).
static std::pair<size_t, size_t> generateKeySubkey(
Value *V, const TargetLibraryInfo *TLI,
function_ref<hash_code(size_t, LoadInst *)> LoadsSubkeyGenerator,
bool AllowAlternate) {
hash_code Key = hash_value(V->getValueID() + 2);
hash_code SubKey = hash_value(0);
// Sort the loads by the distance between the pointers.
if (auto *LI = dyn_cast<LoadInst>(V)) {
Key = hash_combine(LI->getType(), hash_value(Instruction::Load), Key);
if (LI->isSimple())
SubKey = hash_value(LoadsSubkeyGenerator(Key, LI));
else
Key = SubKey = hash_value(LI);
} else if (isVectorLikeInstWithConstOps(V)) {
// Sort extracts by the vector operands.
if (isa<ExtractElementInst, UndefValue>(V))
Key = hash_value(Value::UndefValueVal + 1);
if (auto *EI = dyn_cast<ExtractElementInst>(V)) {
if (!isUndefVector(EI->getVectorOperand()).all() &&
!isa<UndefValue>(EI->getIndexOperand()))
SubKey = hash_value(EI->getVectorOperand());
}
} else if (auto *I = dyn_cast<Instruction>(V)) {
// Sort other instructions just by the opcodes except for CMPInst.
// For CMP also sort by the predicate kind.
if ((isa<BinaryOperator, CastInst>(I)) &&
isValidForAlternation(I->getOpcode())) {
if (AllowAlternate)
Key = hash_value(isa<BinaryOperator>(I) ? 1 : 0);
else
Key = hash_combine(hash_value(I->getOpcode()), Key);
SubKey = hash_combine(
hash_value(I->getOpcode()), hash_value(I->getType()),
hash_value(isa<BinaryOperator>(I)
? I->getType()
: cast<CastInst>(I)->getOperand(0)->getType()));
// For casts, look through the only operand to improve compile time.
if (isa<CastInst>(I)) {
std::pair<size_t, size_t> OpVals =
generateKeySubkey(I->getOperand(0), TLI, LoadsSubkeyGenerator,
/*AllowAlternate=*/true);
Key = hash_combine(OpVals.first, Key);
SubKey = hash_combine(OpVals.first, SubKey);
}
} else if (auto *CI = dyn_cast<CmpInst>(I)) {
CmpInst::Predicate Pred = CI->getPredicate();
if (CI->isCommutative())
Pred = std::min(Pred, CmpInst::getInversePredicate(Pred));
CmpInst::Predicate SwapPred = CmpInst::getSwappedPredicate(Pred);
SubKey = hash_combine(hash_value(I->getOpcode()), hash_value(Pred),
hash_value(SwapPred),
hash_value(CI->getOperand(0)->getType()));
} else if (auto *Call = dyn_cast<CallInst>(I)) {
Intrinsic::ID ID = getVectorIntrinsicIDForCall(Call, TLI);
if (isTriviallyVectorizable(ID)) {
SubKey = hash_combine(hash_value(I->getOpcode()), hash_value(ID));
} else if (!VFDatabase(*Call).getMappings(*Call).empty()) {
SubKey = hash_combine(hash_value(I->getOpcode()),
hash_value(Call->getCalledFunction()));
} else {
Key = hash_combine(hash_value(Call), Key);
SubKey = hash_combine(hash_value(I->getOpcode()), hash_value(Call));
}
for (const CallBase::BundleOpInfo &Op : Call->bundle_op_infos())
SubKey = hash_combine(hash_value(Op.Begin), hash_value(Op.End),
hash_value(Op.Tag), SubKey);
} else if (auto *Gep = dyn_cast<GetElementPtrInst>(I)) {
if (Gep->getNumOperands() == 2 && isa<ConstantInt>(Gep->getOperand(1)))
SubKey = hash_value(Gep->getPointerOperand());
else
SubKey = hash_value(Gep);
} else if (BinaryOperator::isIntDivRem(I->getOpcode()) &&
!isa<ConstantInt>(I->getOperand(1))) {
// Do not try to vectorize instructions with potentially high cost.
SubKey = hash_value(I);
} else {
SubKey = hash_value(I->getOpcode());
}
Key = hash_combine(hash_value(I->getParent()), Key);
}
return std::make_pair(Key, SubKey);
}
/// Checks if the specified instruction \p I is an alternate operation for
/// the given \p MainOp and \p AltOp instructions.
static bool isAlternateInstruction(const Instruction *I,
const Instruction *MainOp,
const Instruction *AltOp,
const TargetLibraryInfo &TLI);
void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth,
const EdgeInfo &UserTreeIdx) {
assert((allConstant(VL) || allSameType(VL)) && "Invalid types!");
SmallVector<int> ReuseShuffleIndicies;
SmallVector<Value *> UniqueValues;
auto &&TryToFindDuplicates = [&VL, &ReuseShuffleIndicies, &UniqueValues,
&UserTreeIdx,
this](const InstructionsState &S) {
// Check that every instruction appears once in this bundle.
DenseMap<Value *, unsigned> UniquePositions(VL.size());
for (Value *V : VL) {
if (isConstant(V)) {
ReuseShuffleIndicies.emplace_back(
isa<UndefValue>(V) ? PoisonMaskElem : UniqueValues.size());
UniqueValues.emplace_back(V);
continue;
}
auto Res = UniquePositions.try_emplace(V, UniqueValues.size());
ReuseShuffleIndicies.emplace_back(Res.first->second);
if (Res.second)
UniqueValues.emplace_back(V);
}
size_t NumUniqueScalarValues = UniqueValues.size();
if (NumUniqueScalarValues == VL.size()) {
ReuseShuffleIndicies.clear();
} else {
LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n");
if (NumUniqueScalarValues <= 1 ||
(UniquePositions.size() == 1 && all_of(UniqueValues,
[](Value *V) {
return isa<UndefValue>(V) ||
!isConstant(V);
})) ||
!llvm::has_single_bit<uint32_t>(NumUniqueScalarValues)) {
LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx);
return false;
}
VL = UniqueValues;
}
return true;
};
InstructionsState S = getSameOpcode(VL, *TLI);
// Gather if we hit the RecursionMaxDepth, unless this is a load (or z/sext of
// a load), in which case peek through to include it in the tree, without
// ballooning over-budget.
if (Depth >= RecursionMaxDepth &&
!(S.MainOp && isa<Instruction>(S.MainOp) && S.MainOp == S.AltOp &&
VL.size() >= 4 &&
(match(S.MainOp, m_Load(m_Value())) || all_of(VL, [&S](const Value *I) {
return match(I,
m_OneUse(m_ZExtOrSExt(m_OneUse(m_Load(m_Value()))))) &&
cast<Instruction>(I)->getOpcode() ==
cast<Instruction>(S.MainOp)->getOpcode();
})))) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n");
if (TryToFindDuplicates(S))
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
// Don't handle scalable vectors
if (S.getOpcode() == Instruction::ExtractElement &&
isa<ScalableVectorType>(
cast<ExtractElementInst>(S.OpValue)->getVectorOperandType())) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to scalable vector type.\n");
if (TryToFindDuplicates(S))
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
// Don't handle vectors.
if (S.OpValue->getType()->isVectorTy() &&
!isa<InsertElementInst>(S.OpValue)) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx);
return;
}
if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue))
if (SI->getValueOperand()->getType()->isVectorTy()) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx);
return;
}
// If all of the operands are identical or constant we have a simple solution.
// If we deal with insert/extract instructions, they all must have constant
// indices, otherwise we should gather them, not try to vectorize.
// If alternate op node with 2 elements with gathered operands - do not
// vectorize.
auto &&NotProfitableForVectorization = [&S, this,
Depth](ArrayRef<Value *> VL) {
if (!S.getOpcode() || !S.isAltShuffle() || VL.size() > 2)
return false;
if (VectorizableTree.size() < MinTreeSize)
return false;
if (Depth >= RecursionMaxDepth - 1)
return true;
// Check if all operands are extracts, part of vector node or can build a
// regular vectorize node.
SmallVector<unsigned, 2> InstsCount(VL.size(), 0);
for (Value *V : VL) {
auto *I = cast<Instruction>(V);
InstsCount.push_back(count_if(I->operand_values(), [](Value *Op) {
return isa<Instruction>(Op) || isVectorLikeInstWithConstOps(Op);
}));
}
bool IsCommutative = isCommutative(S.MainOp) || isCommutative(S.AltOp);
if ((IsCommutative &&
std::accumulate(InstsCount.begin(), InstsCount.end(), 0) < 2) ||
(!IsCommutative &&
all_of(InstsCount, [](unsigned ICnt) { return ICnt < 2; })))
return true;
assert(VL.size() == 2 && "Expected only 2 alternate op instructions.");
SmallVector<SmallVector<std::pair<Value *, Value *>>> Candidates;
auto *I1 = cast<Instruction>(VL.front());
auto *I2 = cast<Instruction>(VL.back());
for (int Op = 0, E = S.MainOp->getNumOperands(); Op < E; ++Op)
Candidates.emplace_back().emplace_back(I1->getOperand(Op),
I2->getOperand(Op));
if (static_cast<unsigned>(count_if(
Candidates, [this](ArrayRef<std::pair<Value *, Value *>> Cand) {
return findBestRootPair(Cand, LookAheadHeuristics::ScoreSplat);
})) >= S.MainOp->getNumOperands() / 2)
return false;
if (S.MainOp->getNumOperands() > 2)
return true;
if (IsCommutative) {
// Check permuted operands.
Candidates.clear();
for (int Op = 0, E = S.MainOp->getNumOperands(); Op < E; ++Op)
Candidates.emplace_back().emplace_back(I1->getOperand(Op),
I2->getOperand((Op + 1) % E));
if (any_of(
Candidates, [this](ArrayRef<std::pair<Value *, Value *>> Cand) {
return findBestRootPair(Cand, LookAheadHeuristics::ScoreSplat);
}))
return false;
}
return true;
};
SmallVector<unsigned> SortedIndices;
BasicBlock *BB = nullptr;
bool IsScatterVectorizeUserTE =
UserTreeIdx.UserTE &&
UserTreeIdx.UserTE->State == TreeEntry::ScatterVectorize;
bool AreAllSameInsts =
(S.getOpcode() && allSameBlock(VL)) ||
(S.OpValue->getType()->isPointerTy() && IsScatterVectorizeUserTE &&
VL.size() > 2 &&
all_of(VL,
[&BB](Value *V) {
auto *I = dyn_cast<GetElementPtrInst>(V);
if (!I)
return doesNotNeedToBeScheduled(V);
if (!BB)
BB = I->getParent();
return BB == I->getParent() && I->getNumOperands() == 2;
}) &&
BB &&
sortPtrAccesses(VL, UserTreeIdx.UserTE->getMainOp()->getType(), *DL, *SE,
SortedIndices));
if (!AreAllSameInsts || allConstant(VL) || isSplat(VL) ||
(isa<InsertElementInst, ExtractValueInst, ExtractElementInst>(
S.OpValue) &&
!all_of(VL, isVectorLikeInstWithConstOps)) ||
NotProfitableForVectorization(VL)) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O, small shuffle. \n");
if (TryToFindDuplicates(S))
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
// We now know that this is a vector of instructions of the same type from
// the same block.
// Don't vectorize ephemeral values.
if (!EphValues.empty()) {
for (Value *V : VL) {
if (EphValues.count(V)) {
LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V
<< ") is ephemeral.\n");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx);
return;
}
}
}
// Check if this is a duplicate of another entry.
if (TreeEntry *E = getTreeEntry(S.OpValue)) {
LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n");
if (!E->isSame(VL)) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n");
if (TryToFindDuplicates(S))
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
// Record the reuse of the tree node. FIXME, currently this is only used to
// properly draw the graph rather than for the actual vectorization.
E->UserTreeIndices.push_back(UserTreeIdx);
LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue
<< ".\n");
return;
}
// Check that none of the instructions in the bundle are already in the tree.
for (Value *V : VL) {
if (!IsScatterVectorizeUserTE && !isa<Instruction>(V))
continue;
if (getTreeEntry(V)) {
LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V
<< ") is already in tree.\n");
if (TryToFindDuplicates(S))
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
}
// The reduction nodes (stored in UserIgnoreList) also should stay scalar.
if (UserIgnoreList && !UserIgnoreList->empty()) {
for (Value *V : VL) {
if (UserIgnoreList && UserIgnoreList->contains(V)) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n");
if (TryToFindDuplicates(S))
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
}
}
// Special processing for sorted pointers for ScatterVectorize node with
// constant indeces only.
if (AreAllSameInsts && UserTreeIdx.UserTE &&
UserTreeIdx.UserTE->State == TreeEntry::ScatterVectorize &&
!(S.getOpcode() && allSameBlock(VL))) {
assert(S.OpValue->getType()->isPointerTy() &&
count_if(VL, [](Value *V) { return isa<GetElementPtrInst>(V); }) >=
2 &&
"Expected pointers only.");
// Reset S to make it GetElementPtr kind of node.
const auto *It = find_if(VL, [](Value *V) { return isa<GetElementPtrInst>(V); });
assert(It != VL.end() && "Expected at least one GEP.");
S = getSameOpcode(*It, *TLI);
}
// Check that all of the users of the scalars that we want to vectorize are
// schedulable.
auto *VL0 = cast<Instruction>(S.OpValue);
BB = VL0->getParent();
if (!DT->isReachableFromEntry(BB)) {
// Don't go into unreachable blocks. They may contain instructions with
// dependency cycles which confuse the final scheduling.
LLVM_DEBUG(dbgs() << "SLP: bundle in unreachable block.\n");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx);
return;
}
// Don't go into catchswitch blocks, which can happen with PHIs.
// Such blocks can only have PHIs and the catchswitch. There is no
// place to insert a shuffle if we need to, so just avoid that issue.
if (isa<CatchSwitchInst>(BB->getTerminator())) {
LLVM_DEBUG(dbgs() << "SLP: bundle in catchswitch block.\n");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx);
return;
}
// Check that every instruction appears once in this bundle.
if (!TryToFindDuplicates(S))
return;
auto &BSRef = BlocksSchedules[BB];
if (!BSRef)
BSRef = std::make_unique<BlockScheduling>(BB);
BlockScheduling &BS = *BSRef;
std::optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S);
#ifdef EXPENSIVE_CHECKS
// Make sure we didn't break any internal invariants
BS.verify();
#endif
if (!Bundle) {
LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n");
assert((!BS.getScheduleData(VL0) ||
!BS.getScheduleData(VL0)->isPartOfBundle()) &&
"tryScheduleBundle should cancelScheduling on failure");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n");
unsigned ShuffleOrOp = S.isAltShuffle() ?
(unsigned) Instruction::ShuffleVector : S.getOpcode();
switch (ShuffleOrOp) {
case Instruction::PHI: {
auto *PH = cast<PHINode>(VL0);
// Check for terminator values (e.g. invoke).
for (Value *V : VL)
for (Value *Incoming : cast<PHINode>(V)->incoming_values()) {
Instruction *Term = dyn_cast<Instruction>(Incoming);
if (Term && Term->isTerminator()) {
LLVM_DEBUG(dbgs()
<< "SLP: Need to swizzle PHINodes (terminator use).\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
}
TreeEntry *TE =
newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n");
// Keeps the reordered operands to avoid code duplication.
SmallVector<ValueList, 2> OperandsVec;
for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) {
if (!DT->isReachableFromEntry(PH->getIncomingBlock(I))) {
ValueList Operands(VL.size(), PoisonValue::get(PH->getType()));
TE->setOperand(I, Operands);
OperandsVec.push_back(Operands);
continue;
}
ValueList Operands;
// Prepare the operand vector.
for (Value *V : VL)
Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock(
PH->getIncomingBlock(I)));
TE->setOperand(I, Operands);
OperandsVec.push_back(Operands);
}
for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx)
buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx});
return;
}
case Instruction::ExtractValue:
case Instruction::ExtractElement: {
OrdersType CurrentOrder;
bool Reuse = canReuseExtract(VL, VL0, CurrentOrder);
if (Reuse) {
LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n");
newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
// This is a special case, as it does not gather, but at the same time
// we are not extending buildTree_rec() towards the operands.
ValueList Op0;
Op0.assign(VL.size(), VL0->getOperand(0));
VectorizableTree.back()->setOperand(0, Op0);
return;
}
if (!CurrentOrder.empty()) {
LLVM_DEBUG({
dbgs() << "SLP: Reusing or shuffling of reordered extract sequence "
"with order";
for (unsigned Idx : CurrentOrder)
dbgs() << " " << Idx;
dbgs() << "\n";
});
fixupOrderingIndices(CurrentOrder);
// Insert new order with initial value 0, if it does not exist,
// otherwise return the iterator to the existing one.
newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies, CurrentOrder);
// This is a special case, as it does not gather, but at the same time
// we are not extending buildTree_rec() towards the operands.
ValueList Op0;
Op0.assign(VL.size(), VL0->getOperand(0));
VectorizableTree.back()->setOperand(0, Op0);
return;
}
LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
BS.cancelScheduling(VL, VL0);
return;
}
case Instruction::InsertElement: {
assert(ReuseShuffleIndicies.empty() && "All inserts should be unique");
// Check that we have a buildvector and not a shuffle of 2 or more
// different vectors.
ValueSet SourceVectors;
for (Value *V : VL) {
SourceVectors.insert(cast<Instruction>(V)->getOperand(0));
assert(getInsertIndex(V) != std::nullopt &&
"Non-constant or undef index?");
}
if (count_if(VL, [&SourceVectors](Value *V) {
return !SourceVectors.contains(V);
}) >= 2) {
// Found 2nd source vector - cancel.
LLVM_DEBUG(dbgs() << "SLP: Gather of insertelement vectors with "
"different source vectors.\n");
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx);
BS.cancelScheduling(VL, VL0);
return;
}
auto OrdCompare = [](const std::pair<int, int> &P1,
const std::pair<int, int> &P2) {
return P1.first > P2.first;
};
PriorityQueue<std::pair<int, int>, SmallVector<std::pair<int, int>>,
decltype(OrdCompare)>
Indices(OrdCompare);
for (int I = 0, E = VL.size(); I < E; ++I) {
unsigned Idx = *getInsertIndex(VL[I]);
Indices.emplace(Idx, I);
}
OrdersType CurrentOrder(VL.size(), VL.size());
bool IsIdentity = true;
for (int I = 0, E = VL.size(); I < E; ++I) {
CurrentOrder[Indices.top().second] = I;
IsIdentity &= Indices.top().second == I;
Indices.pop();
}
if (IsIdentity)
CurrentOrder.clear();
TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
std::nullopt, CurrentOrder);
LLVM_DEBUG(dbgs() << "SLP: added inserts bundle.\n");
constexpr int NumOps = 2;
ValueList VectorOperands[NumOps];
for (int I = 0; I < NumOps; ++I) {
for (Value *V : VL)
VectorOperands[I].push_back(cast<Instruction>(V)->getOperand(I));
TE->setOperand(I, VectorOperands[I]);
}
buildTree_rec(VectorOperands[NumOps - 1], Depth + 1, {TE, NumOps - 1});
return;
}
case Instruction::Load: {
// Check that a vectorized load would load the same memory as a scalar
// load. For example, we don't want to vectorize loads that are smaller
// than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM
// treats loading/storing it as an i8 struct. If we vectorize loads/stores
// from such a struct, we read/write packed bits disagreeing with the
// unvectorized version.
SmallVector<Value *> PointerOps;
OrdersType CurrentOrder;
TreeEntry *TE = nullptr;
switch (canVectorizeLoads(VL, VL0, *TTI, *DL, *SE, *LI, *TLI,
CurrentOrder, PointerOps)) {
case LoadsState::Vectorize:
if (CurrentOrder.empty()) {
// Original loads are consecutive and does not require reordering.
TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n");
} else {
fixupOrderingIndices(CurrentOrder);
// Need to reorder.
TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies, CurrentOrder);
LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n");
}
TE->setOperandsInOrder();
break;
case LoadsState::ScatterVectorize:
// Vectorizing non-consecutive loads with `llvm.masked.gather`.
TE = newTreeEntry(VL, TreeEntry::ScatterVectorize, Bundle, S,
UserTreeIdx, ReuseShuffleIndicies);
TE->setOperandsInOrder();
buildTree_rec(PointerOps, Depth + 1, {TE, 0});
LLVM_DEBUG(dbgs() << "SLP: added a vector of non-consecutive loads.\n");
break;
case LoadsState::Gather:
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
#ifndef NDEBUG
Type *ScalarTy = VL0->getType();
if (DL->getTypeSizeInBits(ScalarTy) !=
DL->getTypeAllocSizeInBits(ScalarTy))
LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n");
else if (any_of(VL, [](Value *V) {
return !cast<LoadInst>(V)->isSimple();
}))
LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n");
else
LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n");
#endif // NDEBUG
break;
}
return;
}
case Instruction::ZExt:
case Instruction::SExt:
case Instruction::FPToUI:
case Instruction::FPToSI:
case Instruction::FPExt:
case Instruction::PtrToInt:
case Instruction::IntToPtr:
case Instruction::SIToFP:
case Instruction::UIToFP:
case Instruction::Trunc:
case Instruction::FPTrunc:
case Instruction::BitCast: {
Type *SrcTy = VL0->getOperand(0)->getType();
for (Value *V : VL) {
Type *Ty = cast<Instruction>(V)->getOperand(0)->getType();
if (Ty != SrcTy || !isValidElementType(Ty)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs()
<< "SLP: Gathering casts with different src types.\n");
return;
}
}
TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n");
TE->setOperandsInOrder();
for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *V : VL)
Operands.push_back(cast<Instruction>(V)->getOperand(i));
buildTree_rec(Operands, Depth + 1, {TE, i});
}
return;
}
case Instruction::ICmp:
case Instruction::FCmp: {
// Check that all of the compares have the same predicate.
CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate();
CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0);
Type *ComparedTy = VL0->getOperand(0)->getType();
for (Value *V : VL) {
CmpInst *Cmp = cast<CmpInst>(V);
if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) ||
Cmp->getOperand(0)->getType() != ComparedTy) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs()
<< "SLP: Gathering cmp with different predicate.\n");
return;
}
}
TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n");
ValueList Left, Right;
if (cast<CmpInst>(VL0)->isCommutative()) {
// Commutative predicate - collect + sort operands of the instructions
// so that each side is more likely to have the same opcode.
assert(P0 == SwapP0 && "Commutative Predicate mismatch");
reorderInputsAccordingToOpcode(VL, Left, Right, *TLI, *DL, *SE, *this);
} else {
// Collect operands - commute if it uses the swapped predicate.
for (Value *V : VL) {
auto *Cmp = cast<CmpInst>(V);
Value *LHS = Cmp->getOperand(0);
Value *RHS = Cmp->getOperand(1);
if (Cmp->getPredicate() != P0)
std::swap(LHS, RHS);
Left.push_back(LHS);
Right.push_back(RHS);
}
}
TE->setOperand(0, Left);
TE->setOperand(1, Right);
buildTree_rec(Left, Depth + 1, {TE, 0});
buildTree_rec(Right, Depth + 1, {TE, 1});
return;
}
case Instruction::Select:
case Instruction::FNeg:
case Instruction::Add:
case Instruction::FAdd:
case Instruction::Sub:
case Instruction::FSub:
case Instruction::Mul:
case Instruction::FMul:
case Instruction::UDiv:
case Instruction::SDiv:
case Instruction::FDiv:
case Instruction::URem:
case Instruction::SRem:
case Instruction::FRem:
case Instruction::Shl:
case Instruction::LShr:
case Instruction::AShr:
case Instruction::And:
case Instruction::Or:
case Instruction::Xor: {
TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n");
// Sort operands of the instructions so that each side is more likely to
// have the same opcode.
if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) {
ValueList Left, Right;
reorderInputsAccordingToOpcode(VL, Left, Right, *TLI, *DL, *SE, *this);
TE->setOperand(0, Left);
TE->setOperand(1, Right);
buildTree_rec(Left, Depth + 1, {TE, 0});
buildTree_rec(Right, Depth + 1, {TE, 1});
return;
}
TE->setOperandsInOrder();
for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *V : VL)
Operands.push_back(cast<Instruction>(V)->getOperand(i));
buildTree_rec(Operands, Depth + 1, {TE, i});
}
return;
}
case Instruction::GetElementPtr: {
// We don't combine GEPs with complicated (nested) indexing.
for (Value *V : VL) {
auto *I = dyn_cast<GetElementPtrInst>(V);
if (!I)
continue;
if (I->getNumOperands() != 2) {
LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
}
// We can't combine several GEPs into one vector if they operate on
// different types.
Type *Ty0 = cast<GEPOperator>(VL0)->getSourceElementType();
for (Value *V : VL) {
auto *GEP = dyn_cast<GEPOperator>(V);
if (!GEP)
continue;
Type *CurTy = GEP->getSourceElementType();
if (Ty0 != CurTy) {
LLVM_DEBUG(dbgs()
<< "SLP: not-vectorizable GEP (different types).\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
}
// We don't combine GEPs with non-constant indexes.
Type *Ty1 = VL0->getOperand(1)->getType();
for (Value *V : VL) {
auto *I = dyn_cast<GetElementPtrInst>(V);
if (!I)
continue;
auto *Op = I->getOperand(1);
if ((!IsScatterVectorizeUserTE && !isa<ConstantInt>(Op)) ||
(Op->getType() != Ty1 &&
((IsScatterVectorizeUserTE && !isa<ConstantInt>(Op)) ||
Op->getType()->getScalarSizeInBits() >
DL->getIndexSizeInBits(
V->getType()->getPointerAddressSpace())))) {
LLVM_DEBUG(dbgs()
<< "SLP: not-vectorizable GEP (non-constant indexes).\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
return;
}
}
TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n");
SmallVector<ValueList, 2> Operands(2);
// Prepare the operand vector for pointer operands.
for (Value *V : VL) {
auto *GEP = dyn_cast<GetElementPtrInst>(V);
if (!GEP) {
Operands.front().push_back(V);
continue;
}
Operands.front().push_back(GEP->getPointerOperand());
}
TE->setOperand(0, Operands.front());
// Need to cast all indices to the same type before vectorization to
// avoid crash.
// Required to be able to find correct matches between different gather
// nodes and reuse the vectorized values rather than trying to gather them
// again.
int IndexIdx = 1;
Type *VL0Ty = VL0->getOperand(IndexIdx)->getType();
Type *Ty = all_of(VL,
[VL0Ty, IndexIdx](Value *V) {
auto *GEP = dyn_cast<GetElementPtrInst>(V);
if (!GEP)
return true;
return VL0Ty == GEP->getOperand(IndexIdx)->getType();
})
? VL0Ty
: DL->getIndexType(cast<GetElementPtrInst>(VL0)
->getPointerOperandType()
->getScalarType());
// Prepare the operand vector.
for (Value *V : VL) {
auto *I = dyn_cast<GetElementPtrInst>(V);
if (!I) {
Operands.back().push_back(
ConstantInt::get(Ty, 0, /*isSigned=*/false));
continue;
}
auto *Op = I->getOperand(IndexIdx);
auto *CI = dyn_cast<ConstantInt>(Op);
if (!CI)
Operands.back().push_back(Op);
else
Operands.back().push_back(ConstantExpr::getIntegerCast(
CI, Ty, CI->getValue().isSignBitSet()));
}
TE->setOperand(IndexIdx, Operands.back());
for (unsigned I = 0, Ops = Operands.size(); I < Ops; ++I)
buildTree_rec(Operands[I], Depth + 1, {TE, I});
return;
}
case Instruction::Store: {
// Check if the stores are consecutive or if we need to swizzle them.
llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType();
// Avoid types that are padded when being allocated as scalars, while
// being packed together in a vector (such as i1).
if (DL->getTypeSizeInBits(ScalarTy) !=
DL->getTypeAllocSizeInBits(ScalarTy)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Gathering stores of non-packed type.\n");
return;
}
// Make sure all stores in the bundle are simple - we can't vectorize
// atomic or volatile stores.
SmallVector<Value *, 4> PointerOps(VL.size());
ValueList Operands(VL.size());
auto POIter = PointerOps.begin();
auto OIter = Operands.begin();
for (Value *V : VL) {
auto *SI = cast<StoreInst>(V);
if (!SI->isSimple()) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n");
return;
}
*POIter = SI->getPointerOperand();
*OIter = SI->getValueOperand();
++POIter;
++OIter;
}
OrdersType CurrentOrder;
// Check the order of pointer operands.
if (llvm::sortPtrAccesses(PointerOps, ScalarTy, *DL, *SE, CurrentOrder)) {
Value *Ptr0;
Value *PtrN;
if (CurrentOrder.empty()) {
Ptr0 = PointerOps.front();
PtrN = PointerOps.back();
} else {
Ptr0 = PointerOps[CurrentOrder.front()];
PtrN = PointerOps[CurrentOrder.back()];
}
std::optional<int> Dist =
getPointersDiff(ScalarTy, Ptr0, ScalarTy, PtrN, *DL, *SE);
// Check that the sorted pointer operands are consecutive.
if (static_cast<unsigned>(*Dist) == VL.size() - 1) {
if (CurrentOrder.empty()) {
// Original stores are consecutive and does not require reordering.
TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S,
UserTreeIdx, ReuseShuffleIndicies);
TE->setOperandsInOrder();
buildTree_rec(Operands, Depth + 1, {TE, 0});
LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n");
} else {
fixupOrderingIndices(CurrentOrder);
TreeEntry *TE =
newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies, CurrentOrder);
TE->setOperandsInOrder();
buildTree_rec(Operands, Depth + 1, {TE, 0});
LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n");
}
return;
}
}
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n");
return;
}
case Instruction::Call: {
// Check if the calls are all to the same vectorizable intrinsic or
// library function.
CallInst *CI = cast<CallInst>(VL0);
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
VFShape Shape = VFShape::get(
*CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())),
false /*HasGlobalPred*/);
Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape);
if (!VecFunc && !isTriviallyVectorizable(ID)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n");
return;
}
Function *F = CI->getCalledFunction();
unsigned NumArgs = CI->arg_size();
SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr);
for (unsigned j = 0; j != NumArgs; ++j)
if (isVectorIntrinsicWithScalarOpAtArg(ID, j))
ScalarArgs[j] = CI->getArgOperand(j);
for (Value *V : VL) {
CallInst *CI2 = dyn_cast<CallInst>(V);
if (!CI2 || CI2->getCalledFunction() != F ||
getVectorIntrinsicIDForCall(CI2, TLI) != ID ||
(VecFunc &&
VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) ||
!CI->hasIdenticalOperandBundleSchema(*CI2)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V
<< "\n");
return;
}
// Some intrinsics have scalar arguments and should be same in order for
// them to be vectorized.
for (unsigned j = 0; j != NumArgs; ++j) {
if (isVectorIntrinsicWithScalarOpAtArg(ID, j)) {
Value *A1J = CI2->getArgOperand(j);
if (ScalarArgs[j] != A1J) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI
<< " argument " << ScalarArgs[j] << "!=" << A1J
<< "\n");
return;
}
}
}
// Verify that the bundle operands are identical between the two calls.
if (CI->hasOperandBundles() &&
!std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(),
CI->op_begin() + CI->getBundleOperandsEndIndex(),
CI2->op_begin() + CI2->getBundleOperandsStartIndex())) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:"
<< *CI << "!=" << *V << '\n');
return;
}
}
TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
TE->setOperandsInOrder();
for (unsigned i = 0, e = CI->arg_size(); i != e; ++i) {
// For scalar operands no need to to create an entry since no need to
// vectorize it.
if (isVectorIntrinsicWithScalarOpAtArg(ID, i))
continue;
ValueList Operands;
// Prepare the operand vector.
for (Value *V : VL) {
auto *CI2 = cast<CallInst>(V);
Operands.push_back(CI2->getArgOperand(i));
}
buildTree_rec(Operands, Depth + 1, {TE, i});
}
return;
}
case Instruction::ShuffleVector: {
// If this is not an alternate sequence of opcode like add-sub
// then do not vectorize this instruction.
if (!S.isAltShuffle()) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n");
return;
}
TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n");
// Reorder operands if reordering would enable vectorization.
auto *CI = dyn_cast<CmpInst>(VL0);
if (isa<BinaryOperator>(VL0) || CI) {
ValueList Left, Right;
if (!CI || all_of(VL, [](Value *V) {
return cast<CmpInst>(V)->isCommutative();
})) {
reorderInputsAccordingToOpcode(VL, Left, Right, *TLI, *DL, *SE,
*this);
} else {
auto *MainCI = cast<CmpInst>(S.MainOp);
auto *AltCI = cast<CmpInst>(S.AltOp);
CmpInst::Predicate MainP = MainCI->getPredicate();
CmpInst::Predicate AltP = AltCI->getPredicate();
assert(MainP != AltP &&
"Expected different main/alternate predicates.");
// Collect operands - commute if it uses the swapped predicate or
// alternate operation.
for (Value *V : VL) {
auto *Cmp = cast<CmpInst>(V);
Value *LHS = Cmp->getOperand(0);
Value *RHS = Cmp->getOperand(1);
if (isAlternateInstruction(Cmp, MainCI, AltCI, *TLI)) {
if (AltP == CmpInst::getSwappedPredicate(Cmp->getPredicate()))
std::swap(LHS, RHS);
} else {
if (MainP == CmpInst::getSwappedPredicate(Cmp->getPredicate()))
std::swap(LHS, RHS);
}
Left.push_back(LHS);
Right.push_back(RHS);
}
}
TE->setOperand(0, Left);
TE->setOperand(1, Right);
buildTree_rec(Left, Depth + 1, {TE, 0});
buildTree_rec(Right, Depth + 1, {TE, 1});
return;
}
TE->setOperandsInOrder();
for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *V : VL)
Operands.push_back(cast<Instruction>(V)->getOperand(i));
buildTree_rec(Operands, Depth + 1, {TE, i});
}
return;
}
default:
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, std::nullopt /*not vectorized*/, S, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n");
return;
}
}
unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const {
unsigned N = 1;
Type *EltTy = T;
while (isa<StructType, ArrayType, VectorType>(EltTy)) {
if (auto *ST = dyn_cast<StructType>(EltTy)) {
// Check that struct is homogeneous.
for (const auto *Ty : ST->elements())
if (Ty != *ST->element_begin())
return 0;
N *= ST->getNumElements();
EltTy = *ST->element_begin();
} else if (auto *AT = dyn_cast<ArrayType>(EltTy)) {
N *= AT->getNumElements();
EltTy = AT->getElementType();
} else {
auto *VT = cast<FixedVectorType>(EltTy);
N *= VT->getNumElements();
EltTy = VT->getElementType();
}
}
if (!isValidElementType(EltTy))
return 0;
uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N));
if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T))
return 0;
return N;
}
bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue,
SmallVectorImpl<unsigned> &CurrentOrder) const {
const auto *It = find_if(VL, [](Value *V) {
return isa<ExtractElementInst, ExtractValueInst>(V);
});
assert(It != VL.end() && "Expected at least one extract instruction.");
auto *E0 = cast<Instruction>(*It);
assert(all_of(VL,
[](Value *V) {
return isa<UndefValue, ExtractElementInst, ExtractValueInst>(
V);
}) &&
"Invalid opcode");
// Check if all of the extracts come from the same vector and from the
// correct offset.
Value *Vec = E0->getOperand(0);
CurrentOrder.clear();
// We have to extract from a vector/aggregate with the same number of elements.
unsigned NElts;
if (E0->getOpcode() == Instruction::ExtractValue) {
const DataLayout &DL = E0->getModule()->getDataLayout();
NElts = canMapToVector(Vec->getType(), DL);
if (!NElts)
return false;
// Check if load can be rewritten as load of vector.
LoadInst *LI = dyn_cast<LoadInst>(Vec);
if (!LI || !LI->isSimple() || !LI->hasNUses(VL.size()))
return false;
} else {
NElts = cast<FixedVectorType>(Vec->getType())->getNumElements();
}
if (NElts != VL.size())
return false;
// Check that all of the indices extract from the correct offset.
bool ShouldKeepOrder = true;
unsigned E = VL.size();
// Assign to all items the initial value E + 1 so we can check if the extract
// instruction index was used already.
// Also, later we can check that all the indices are used and we have a
// consecutive access in the extract instructions, by checking that no
// element of CurrentOrder still has value E + 1.
CurrentOrder.assign(E, E);
unsigned I = 0;
for (; I < E; ++I) {
auto *Inst = dyn_cast<Instruction>(VL[I]);
if (!Inst)
continue;
if (Inst->getOperand(0) != Vec)
break;
if (auto *EE = dyn_cast<ExtractElementInst>(Inst))
if (isa<UndefValue>(EE->getIndexOperand()))
continue;
std::optional<unsigned> Idx = getExtractIndex(Inst);
if (!Idx)
break;
const unsigned ExtIdx = *Idx;
if (ExtIdx != I) {
if (ExtIdx >= E || CurrentOrder[ExtIdx] != E)
break;
ShouldKeepOrder = false;
CurrentOrder[ExtIdx] = I;
} else {
if (CurrentOrder[I] != E)
break;
CurrentOrder[I] = I;
}
}
if (I < E) {
CurrentOrder.clear();
return false;
}
if (ShouldKeepOrder)
CurrentOrder.clear();
return ShouldKeepOrder;
}
bool BoUpSLP::areAllUsersVectorized(Instruction *I,
ArrayRef<Value *> VectorizedVals) const {
return (I->hasOneUse() && is_contained(VectorizedVals, I)) ||
all_of(I->users(), [this](User *U) {
return ScalarToTreeEntry.count(U) > 0 ||
isVectorLikeInstWithConstOps(U) ||
(isa<ExtractElementInst>(U) && MustGather.contains(U));
});
}
static std::pair<InstructionCost, InstructionCost>
getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy,
TargetTransformInfo *TTI, TargetLibraryInfo *TLI) {
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
// Calculate the cost of the scalar and vector calls.
SmallVector<Type *, 4> VecTys;
for (Use &Arg : CI->args())
VecTys.push_back(
FixedVectorType::get(Arg->getType(), VecTy->getNumElements()));
FastMathFlags FMF;
if (auto *FPCI = dyn_cast<FPMathOperator>(CI))
FMF = FPCI->getFastMathFlags();
SmallVector<const Value *> Arguments(CI->args());
IntrinsicCostAttributes CostAttrs(ID, VecTy, Arguments, VecTys, FMF,
dyn_cast<IntrinsicInst>(CI));
auto IntrinsicCost =
TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput);
auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>(
VecTy->getNumElements())),
false /*HasGlobalPred*/);
Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape);
auto LibCost = IntrinsicCost;
if (!CI->isNoBuiltin() && VecFunc) {
// Calculate the cost of the vector library call.
// If the corresponding vector call is cheaper, return its cost.
LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys,
TTI::TCK_RecipThroughput);
}
return {IntrinsicCost, LibCost};
}
/// Build shuffle mask for shuffle graph entries and lists of main and alternate
/// operations operands.
static void
buildShuffleEntryMask(ArrayRef<Value *> VL, ArrayRef<unsigned> ReorderIndices,
ArrayRef<int> ReusesIndices,
const function_ref<bool(Instruction *)> IsAltOp,
SmallVectorImpl<int> &Mask,
SmallVectorImpl<Value *> *OpScalars = nullptr,
SmallVectorImpl<Value *> *AltScalars = nullptr) {
unsigned Sz = VL.size();
Mask.assign(Sz, PoisonMaskElem);
SmallVector<int> OrderMask;
if (!ReorderIndices.empty())
inversePermutation(ReorderIndices, OrderMask);
for (unsigned I = 0; I < Sz; ++I) {
unsigned Idx = I;
if (!ReorderIndices.empty())
Idx = OrderMask[I];
auto *OpInst = cast<Instruction>(VL[Idx]);
if (IsAltOp(OpInst)) {
Mask[I] = Sz + Idx;
if (AltScalars)
AltScalars->push_back(OpInst);
} else {
Mask[I] = Idx;
if (OpScalars)
OpScalars->push_back(OpInst);
}
}
if (!ReusesIndices.empty()) {
SmallVector<int> NewMask(ReusesIndices.size(), PoisonMaskElem);
transform(ReusesIndices, NewMask.begin(), [&Mask](int Idx) {
return Idx != PoisonMaskElem ? Mask[Idx] : PoisonMaskElem;
});
Mask.swap(NewMask);
}
}
static bool isAlternateInstruction(const Instruction *I,
const Instruction *MainOp,
const Instruction *AltOp,
const TargetLibraryInfo &TLI) {
if (auto *MainCI = dyn_cast<CmpInst>(MainOp)) {
auto *AltCI = cast<CmpInst>(AltOp);
CmpInst::Predicate MainP = MainCI->getPredicate();
CmpInst::Predicate AltP = AltCI->getPredicate();
assert(MainP != AltP && "Expected different main/alternate predicates.");
auto *CI = cast<CmpInst>(I);
if (isCmpSameOrSwapped(MainCI, CI, TLI))
return false;
if (isCmpSameOrSwapped(AltCI, CI, TLI))
return true;
CmpInst::Predicate P = CI->getPredicate();
CmpInst::Predicate SwappedP = CmpInst::getSwappedPredicate(P);
assert((MainP == P || AltP == P || MainP == SwappedP || AltP == SwappedP) &&
"CmpInst expected to match either main or alternate predicate or "
"their swap.");
(void)AltP;
return MainP != P && MainP != SwappedP;
}
return I->getOpcode() == AltOp->getOpcode();
}
TTI::OperandValueInfo BoUpSLP::getOperandInfo(ArrayRef<Value *> VL,
unsigned OpIdx) {
assert(!VL.empty());
const auto *I0 = cast<Instruction>(*find_if(VL, Instruction::classof));
const auto *Op0 = I0->getOperand(OpIdx);
const bool IsConstant = all_of(VL, [&](Value *V) {
// TODO: We should allow undef elements here
const auto *I = dyn_cast<Instruction>(V);
if (!I)
return true;
auto *Op = I->getOperand(OpIdx);
return isConstant(Op) && !isa<UndefValue>(Op);
});
const bool IsUniform = all_of(VL, [&](Value *V) {
// TODO: We should allow undef elements here
const auto *I = dyn_cast<Instruction>(V);
if (!I)
return false;
return I->getOperand(OpIdx) == Op0;
});
const bool IsPowerOfTwo = all_of(VL, [&](Value *V) {
// TODO: We should allow undef elements here
const auto *I = dyn_cast<Instruction>(V);
if (!I) {
assert((isa<UndefValue>(V) ||
I0->getOpcode() == Instruction::GetElementPtr) &&
"Expected undef or GEP.");
return true;
}
auto *Op = I->getOperand(OpIdx);
if (auto *CI = dyn_cast<ConstantInt>(Op))
return CI->getValue().isPowerOf2();
return false;
});
const bool IsNegatedPowerOfTwo = all_of(VL, [&](Value *V) {
// TODO: We should allow undef elements here
const auto *I = dyn_cast<Instruction>(V);
if (!I) {
assert((isa<UndefValue>(V) ||
I0->getOpcode() == Instruction::GetElementPtr) &&
"Expected undef or GEP.");
return true;
}
const auto *Op = I->getOperand(OpIdx);
if (auto *CI = dyn_cast<ConstantInt>(Op))
return CI->getValue().isNegatedPowerOf2();
return false;
});
TTI::OperandValueKind VK = TTI::OK_AnyValue;
if (IsConstant && IsUniform)
VK = TTI::OK_UniformConstantValue;
else if (IsConstant)
VK = TTI::OK_NonUniformConstantValue;
else if (IsUniform)
VK = TTI::OK_UniformValue;
TTI::OperandValueProperties VP = TTI::OP_None;
VP = IsPowerOfTwo ? TTI::OP_PowerOf2 : VP;
VP = IsNegatedPowerOfTwo ? TTI::OP_NegatedPowerOf2 : VP;
return {VK, VP};
}
namespace {
/// The base class for shuffle instruction emission and shuffle cost estimation.
class BaseShuffleAnalysis {
protected:
/// Checks if the mask is an identity mask.
/// \param IsStrict if is true the function returns false if mask size does
/// not match vector size.
static bool isIdentityMask(ArrayRef<int> Mask, const FixedVectorType *VecTy,
bool IsStrict) {
int Limit = Mask.size();
int VF = VecTy->getNumElements();
return (VF == Limit || !IsStrict) &&
all_of(Mask, [Limit](int Idx) { return Idx < Limit; }) &&
ShuffleVectorInst::isIdentityMask(Mask);
}
/// Tries to combine 2 different masks into single one.
/// \param LocalVF Vector length of the permuted input vector. \p Mask may
/// change the size of the vector, \p LocalVF is the original size of the
/// shuffled vector.
static void combineMasks(unsigned LocalVF, SmallVectorImpl<int> &Mask,
ArrayRef<int> ExtMask) {
unsigned VF = Mask.size();
SmallVector<int> NewMask(ExtMask.size(), PoisonMaskElem);
for (int I = 0, Sz = ExtMask.size(); I < Sz; ++I) {
if (ExtMask[I] == PoisonMaskElem)
continue;
int MaskedIdx = Mask[ExtMask[I] % VF];
NewMask[I] =
MaskedIdx == PoisonMaskElem ? PoisonMaskElem : MaskedIdx % LocalVF;
}
Mask.swap(NewMask);
}
/// Looks through shuffles trying to reduce final number of shuffles in the
/// code. The function looks through the previously emitted shuffle
/// instructions and properly mark indices in mask as undef.
/// For example, given the code
/// \code
/// %s1 = shufflevector <2 x ty> %0, poison, <1, 0>
/// %s2 = shufflevector <2 x ty> %1, poison, <1, 0>
/// \endcode
/// and if need to emit shuffle of %s1 and %s2 with mask <1, 0, 3, 2>, it will
/// look through %s1 and %s2 and select vectors %0 and %1 with mask
/// <0, 1, 2, 3> for the shuffle.
/// If 2 operands are of different size, the smallest one will be resized and
/// the mask recalculated properly.
/// For example, given the code
/// \code
/// %s1 = shufflevector <2 x ty> %0, poison, <1, 0, 1, 0>
/// %s2 = shufflevector <2 x ty> %1, poison, <1, 0, 1, 0>
/// \endcode
/// and if need to emit shuffle of %s1 and %s2 with mask <1, 0, 5, 4>, it will
/// look through %s1 and %s2 and select vectors %0 and %1 with mask
/// <0, 1, 2, 3> for the shuffle.
/// So, it tries to transform permutations to simple vector merge, if
/// possible.
/// \param V The input vector which must be shuffled using the given \p Mask.
/// If the better candidate is found, \p V is set to this best candidate
/// vector.
/// \param Mask The input mask for the shuffle. If the best candidate is found
/// during looking-through-shuffles attempt, it is updated accordingly.
/// \param SinglePermute true if the shuffle operation is originally a
/// single-value-permutation. In this case the look-through-shuffles procedure
/// may look for resizing shuffles as the best candidates.
/// \return true if the shuffle results in the non-resizing identity shuffle
/// (and thus can be ignored), false - otherwise.
static bool peekThroughShuffles(Value *&V, SmallVectorImpl<int> &Mask,
bool SinglePermute) {
Value *Op = V;
ShuffleVectorInst *IdentityOp = nullptr;
SmallVector<int> IdentityMask;
while (auto *SV = dyn_cast<ShuffleVectorInst>(Op)) {
// Exit if not a fixed vector type or changing size shuffle.
auto *SVTy = dyn_cast<FixedVectorType>(SV->getType());
if (!SVTy)
break;
// Remember the identity or broadcast mask, if it is not a resizing
// shuffle. If no better candidates are found, this Op and Mask will be
// used in the final shuffle.
if (isIdentityMask(Mask, SVTy, /*IsStrict=*/false)) {
if (!IdentityOp || !SinglePermute ||
(isIdentityMask(Mask, SVTy, /*IsStrict=*/true) &&
!ShuffleVectorInst::isZeroEltSplatMask(IdentityMask))) {
IdentityOp = SV;
// Store current mask in the IdentityMask so later we did not lost
// this info if IdentityOp is selected as the best candidate for the
// permutation.
IdentityMask.assign(Mask);
}
}
// Remember the broadcast mask. If no better candidates are found, this Op
// and Mask will be used in the final shuffle.
// Zero splat can be used as identity too, since it might be used with
// mask <0, 1, 2, ...>, i.e. identity mask without extra reshuffling.
// E.g. if need to shuffle the vector with the mask <3, 1, 2, 0>, which is
// expensive, the analysis founds out, that the source vector is just a
// broadcast, this original mask can be transformed to identity mask <0,
// 1, 2, 3>.
// \code
// %0 = shuffle %v, poison, zeroinitalizer
// %res = shuffle %0, poison, <3, 1, 2, 0>
// \endcode
// may be transformed to
// \code
// %0 = shuffle %v, poison, zeroinitalizer
// %res = shuffle %0, poison, <0, 1, 2, 3>
// \endcode
if (SV->isZeroEltSplat()) {
IdentityOp = SV;
IdentityMask.assign(Mask);
}
int LocalVF = Mask.size();
if (auto *SVOpTy =
dyn_cast<FixedVectorType>(SV->getOperand(0)->getType()))
LocalVF = SVOpTy->getNumElements();
SmallVector<int> ExtMask(Mask.size(), PoisonMaskElem);
for (auto [Idx, I] : enumerate(Mask)) {
if (I == PoisonMaskElem ||
static_cast<unsigned>(I) >= SV->getShuffleMask().size())
continue;
ExtMask[Idx] = SV->getMaskValue(I);
}
bool IsOp1Undef =
isUndefVector(SV->getOperand(0),
buildUseMask(LocalVF, ExtMask, UseMask::FirstArg))
.all();
bool IsOp2Undef =
isUndefVector(SV->getOperand(1),
buildUseMask(LocalVF, ExtMask, UseMask::SecondArg))
.all();
if (!IsOp1Undef && !IsOp2Undef) {
// Update mask and mark undef elems.
for (int &I : Mask) {
if (I == PoisonMaskElem)
continue;
if (SV->getMaskValue(I % SV->getShuffleMask().size()) ==
PoisonMaskElem)
I = PoisonMaskElem;
}
break;
}
SmallVector<int> ShuffleMask(SV->getShuffleMask().begin(),
SV->getShuffleMask().end());
combineMasks(LocalVF, ShuffleMask, Mask);
Mask.swap(ShuffleMask);
if (IsOp2Undef)
Op = SV->getOperand(0);
else
Op = SV->getOperand(1);
}
if (auto *OpTy = dyn_cast<FixedVectorType>(Op->getType());
!OpTy || !isIdentityMask(Mask, OpTy, SinglePermute) ||
ShuffleVectorInst::isZeroEltSplatMask(Mask)) {
if (IdentityOp) {
V = IdentityOp;
assert(Mask.size() == IdentityMask.size() &&
"Expected masks of same sizes.");
// Clear known poison elements.
for (auto [I, Idx] : enumerate(Mask))
if (Idx == PoisonMaskElem)
IdentityMask[I] = PoisonMaskElem;
Mask.swap(IdentityMask);
auto *Shuffle = dyn_cast<ShuffleVectorInst>(V);
return SinglePermute &&
(isIdentityMask(Mask, cast<FixedVectorType>(V->getType()),
/*IsStrict=*/true) ||
(Shuffle && Mask.size() == Shuffle->getShuffleMask().size() &&
Shuffle->isZeroEltSplat() &&
ShuffleVectorInst::isZeroEltSplatMask(Mask)));
}
V = Op;
return false;
}
V = Op;
return true;
}
/// Smart shuffle instruction emission, walks through shuffles trees and
/// tries to find the best matching vector for the actual shuffle
/// instruction.
template <typename T, typename ShuffleBuilderTy>
static T createShuffle(Value *V1, Value *V2, ArrayRef<int> Mask,
ShuffleBuilderTy &Builder) {
assert(V1 && "Expected at least one vector value.");
if (V2)
Builder.resizeToMatch(V1, V2);
int VF = Mask.size();
if (auto *FTy = dyn_cast<FixedVectorType>(V1->getType()))
VF = FTy->getNumElements();
if (V2 &&
!isUndefVector(V2, buildUseMask(VF, Mask, UseMask::SecondArg)).all()) {
// Peek through shuffles.
Value *Op1 = V1;
Value *Op2 = V2;
int VF =
cast<VectorType>(V1->getType())->getElementCount().getKnownMinValue();
SmallVector<int> CombinedMask1(Mask.size(), PoisonMaskElem);
SmallVector<int> CombinedMask2(Mask.size(), PoisonMaskElem);
for (int I = 0, E = Mask.size(); I < E; ++I) {
if (Mask[I] < VF)
CombinedMask1[I] = Mask[I];
else
CombinedMask2[I] = Mask[I] - VF;
}
Value *PrevOp1;
Value *PrevOp2;
do {
PrevOp1 = Op1;
PrevOp2 = Op2;
(void)peekThroughShuffles(Op1, CombinedMask1, /*SinglePermute=*/false);
(void)peekThroughShuffles(Op2, CombinedMask2, /*SinglePermute=*/false);
// Check if we have 2 resizing shuffles - need to peek through operands
// again.
if (auto *SV1 = dyn_cast<ShuffleVectorInst>(Op1))
if (auto *SV2 = dyn_cast<ShuffleVectorInst>(Op2)) {
SmallVector<int> ExtMask1(Mask.size(), PoisonMaskElem);
for (auto [Idx, I] : enumerate(CombinedMask1)) {
if (I == PoisonMaskElem)
continue;
ExtMask1[Idx] = SV1->getMaskValue(I);
}
SmallBitVector UseMask1 = buildUseMask(
cast<FixedVectorType>(SV1->getOperand(1)->getType())
->getNumElements(),
ExtMask1, UseMask::SecondArg);
SmallVector<int> ExtMask2(CombinedMask2.size(), PoisonMaskElem);
for (auto [Idx, I] : enumerate(CombinedMask2)) {
if (I == PoisonMaskElem)
continue;
ExtMask2[Idx] = SV2->getMaskValue(I);
}
SmallBitVector UseMask2 = buildUseMask(
cast<FixedVectorType>(SV2->getOperand(1)->getType())
->getNumElements(),
ExtMask2, UseMask::SecondArg);
if (SV1->getOperand(0)->getType() ==
SV2->getOperand(0)->getType() &&
SV1->getOperand(0)->getType() != SV1->getType() &&
isUndefVector(SV1->getOperand(1), UseMask1).all() &&
isUndefVector(SV2->getOperand(1), UseMask2).all()) {
Op1 = SV1->getOperand(0);
Op2 = SV2->getOperand(0);
SmallVector<int> ShuffleMask1(SV1->getShuffleMask().begin(),
SV1->getShuffleMask().end());
int LocalVF = ShuffleMask1.size();
if (auto *FTy = dyn_cast<FixedVectorType>(Op1->getType()))
LocalVF = FTy->getNumElements();
combineMasks(LocalVF, ShuffleMask1, CombinedMask1);
CombinedMask1.swap(ShuffleMask1);
SmallVector<int> ShuffleMask2(SV2->getShuffleMask().begin(),
SV2->getShuffleMask().end());
LocalVF = ShuffleMask2.size();
if (auto *FTy = dyn_cast<FixedVectorType>(Op2->getType()))
LocalVF = FTy->getNumElements();
combineMasks(LocalVF, ShuffleMask2, CombinedMask2);
CombinedMask2.swap(ShuffleMask2);
}
}
} while (PrevOp1 != Op1 || PrevOp2 != Op2);
Builder.resizeToMatch(Op1, Op2);
VF = std::max(cast<VectorType>(Op1->getType())
->getElementCount()
.getKnownMinValue(),
cast<VectorType>(Op2->getType())
->getElementCount()
.getKnownMinValue());
for (int I = 0, E = Mask.size(); I < E; ++I) {
if (CombinedMask2[I] != PoisonMaskElem) {
assert(CombinedMask1[I] == PoisonMaskElem &&
"Expected undefined mask element");
CombinedMask1[I] = CombinedMask2[I] + (Op1 == Op2 ? 0 : VF);
}
}
const int Limit = CombinedMask1.size() * 2;
if (Op1 == Op2 && Limit == 2 * VF &&
all_of(CombinedMask1, [=](int Idx) { return Idx < Limit; }) &&
(ShuffleVectorInst::isIdentityMask(CombinedMask1) ||
(ShuffleVectorInst::isZeroEltSplatMask(CombinedMask1) &&
isa<ShuffleVectorInst>(Op1) &&
cast<ShuffleVectorInst>(Op1)->getShuffleMask() ==
ArrayRef(CombinedMask1))))
return Builder.createIdentity(Op1);
return Builder.createShuffleVector(
Op1, Op1 == Op2 ? PoisonValue::get(Op1->getType()) : Op2,
CombinedMask1);
}
if (isa<PoisonValue>(V1))
return Builder.createPoison(
cast<VectorType>(V1->getType())->getElementType(), Mask.size());
SmallVector<int> NewMask(Mask.begin(), Mask.end());
bool IsIdentity = peekThroughShuffles(V1, NewMask, /*SinglePermute=*/true);
assert(V1 && "Expected non-null value after looking through shuffles.");
if (!IsIdentity)
return Builder.createShuffleVector(V1, NewMask);
return Builder.createIdentity(V1);
}
};
} // namespace
/// Merges shuffle masks and emits final shuffle instruction, if required. It
/// supports shuffling of 2 input vectors. It implements lazy shuffles emission,
/// when the actual shuffle instruction is generated only if this is actually
/// required. Otherwise, the shuffle instruction emission is delayed till the
/// end of the process, to reduce the number of emitted instructions and further
/// analysis/transformations.
class BoUpSLP::ShuffleCostEstimator : public BaseShuffleAnalysis {
bool IsFinalized = false;
SmallVector<int> CommonMask;
SmallVector<PointerUnion<Value *, const TreeEntry *> , 2> InVectors;
const TargetTransformInfo &TTI;
InstructionCost Cost = 0;
ArrayRef<Value *> VectorizedVals;
BoUpSLP &R;
SmallPtrSetImpl<Value *> &CheckedExtracts;
constexpr static TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
InstructionCost getBuildVectorCost(ArrayRef<Value *> VL, Value *Root) {
if ((!Root && allConstant(VL)) || all_of(VL, UndefValue::classof))
return TTI::TCC_Free;
auto *VecTy = FixedVectorType::get(VL.front()->getType(), VL.size());
InstructionCost GatherCost = 0;
SmallVector<Value *> Gathers(VL.begin(), VL.end());
// Improve gather cost for gather of loads, if we can group some of the
// loads into vector loads.
InstructionsState S = getSameOpcode(VL, *R.TLI);
if (VL.size() > 2 && S.getOpcode() == Instruction::Load &&
!S.isAltShuffle() &&
!all_of(Gathers, [&](Value *V) { return R.getTreeEntry(V); }) &&
!isSplat(Gathers)) {
BoUpSLP::ValueSet VectorizedLoads;
unsigned StartIdx = 0;
unsigned VF = VL.size() / 2;
unsigned VectorizedCnt = 0;
unsigned ScatterVectorizeCnt = 0;
const unsigned Sz = R.DL->getTypeSizeInBits(S.MainOp->getType());
for (unsigned MinVF = R.getMinVF(2 * Sz); VF >= MinVF; VF /= 2) {
for (unsigned Cnt = StartIdx, End = VL.size(); Cnt + VF <= End;
Cnt += VF) {
ArrayRef<Value *> Slice = VL.slice(Cnt, VF);
if (!VectorizedLoads.count(Slice.front()) &&
!VectorizedLoads.count(Slice.back()) && allSameBlock(Slice)) {
SmallVector<Value *> PointerOps;
OrdersType CurrentOrder;
LoadsState LS =
canVectorizeLoads(Slice, Slice.front(), TTI, *R.DL, *R.SE,
*R.LI, *R.TLI, CurrentOrder, PointerOps);
switch (LS) {
case LoadsState::Vectorize:
case LoadsState::ScatterVectorize:
// Mark the vectorized loads so that we don't vectorize them
// again.
if (LS == LoadsState::Vectorize)
++VectorizedCnt;
else
++ScatterVectorizeCnt;
VectorizedLoads.insert(Slice.begin(), Slice.end());
// If we vectorized initial block, no need to try to vectorize
// it again.
if (Cnt == StartIdx)
StartIdx += VF;
break;
case LoadsState::Gather:
break;
}
}
}
// Check if the whole array was vectorized already - exit.
if (StartIdx >= VL.size())
break;
// Found vectorizable parts - exit.
if (!VectorizedLoads.empty())
break;
}
if (!VectorizedLoads.empty()) {
unsigned NumParts = TTI.getNumberOfParts(VecTy);
bool NeedInsertSubvectorAnalysis =
!NumParts || (VL.size() / VF) > NumParts;
// Get the cost for gathered loads.
for (unsigned I = 0, End = VL.size(); I < End; I += VF) {
if (VectorizedLoads.contains(VL[I]))
continue;
GatherCost += getBuildVectorCost(VL.slice(I, VF), Root);
}
// Exclude potentially vectorized loads from list of gathered
// scalars.
auto *LI = cast<LoadInst>(S.MainOp);
Gathers.assign(Gathers.size(), PoisonValue::get(LI->getType()));
// The cost for vectorized loads.
InstructionCost ScalarsCost = 0;
for (Value *V : VectorizedLoads) {
auto *LI = cast<LoadInst>(V);
ScalarsCost +=
TTI.getMemoryOpCost(Instruction::Load, LI->getType(),
LI->getAlign(), LI->getPointerAddressSpace(),
CostKind, TTI::OperandValueInfo(), LI);
}
auto *LoadTy = FixedVectorType::get(LI->getType(), VF);
Align Alignment = LI->getAlign();
GatherCost +=
VectorizedCnt *
TTI.getMemoryOpCost(Instruction::Load, LoadTy, Alignment,
LI->getPointerAddressSpace(), CostKind,
TTI::OperandValueInfo(), LI);
GatherCost += ScatterVectorizeCnt *
TTI.getGatherScatterOpCost(
Instruction::Load, LoadTy, LI->getPointerOperand(),
/*VariableMask=*/false, Alignment, CostKind, LI);
if (NeedInsertSubvectorAnalysis) {
// Add the cost for the subvectors insert.
for (int I = VF, E = VL.size(); I < E; I += VF)
GatherCost += TTI.getShuffleCost(TTI::SK_InsertSubvector, VecTy,
std::nullopt, CostKind, I, LoadTy);
}
GatherCost -= ScalarsCost;
}
} else if (!Root && isSplat(VL)) {
// Found the broadcasting of the single scalar, calculate the cost as
// the broadcast.
const auto *It =
find_if(VL, [](Value *V) { return !isa<UndefValue>(V); });
assert(It != VL.end() && "Expected at least one non-undef value.");
// Add broadcast for non-identity shuffle only.
bool NeedShuffle =
count(VL, *It) > 1 &&
(VL.front() != *It || !all_of(VL.drop_front(), UndefValue::classof));
InstructionCost InsertCost = TTI.getVectorInstrCost(
Instruction::InsertElement, VecTy, CostKind,
NeedShuffle ? 0 : std::distance(VL.begin(), It),
PoisonValue::get(VecTy), *It);
return InsertCost +
(NeedShuffle ? TTI.getShuffleCost(
TargetTransformInfo::SK_Broadcast, VecTy,
/*Mask=*/std::nullopt, CostKind, /*Index=*/0,
/*SubTp=*/nullptr, /*Args=*/*It)
: TTI::TCC_Free);
}
return GatherCost +
(all_of(Gathers, UndefValue::classof)
? TTI::TCC_Free
: R.getGatherCost(Gathers, !Root && VL.equals(Gathers)));
};
/// Compute the cost of creating a vector of type \p VecTy containing the
/// extracted values from \p VL.
InstructionCost computeExtractCost(ArrayRef<Value *> VL, ArrayRef<int> Mask,
TTI::ShuffleKind ShuffleKind) {
auto *VecTy = FixedVectorType::get(VL.front()->getType(), VL.size());
unsigned NumOfParts = TTI.getNumberOfParts(VecTy);
if (ShuffleKind != TargetTransformInfo::SK_PermuteSingleSrc ||
!NumOfParts || VecTy->getNumElements() < NumOfParts)
return TTI.getShuffleCost(ShuffleKind, VecTy, Mask);
bool AllConsecutive = true;
unsigned EltsPerVector = VecTy->getNumElements() / NumOfParts;
unsigned Idx = -1;
InstructionCost Cost = 0;
// Process extracts in blocks of EltsPerVector to check if the source vector
// operand can be re-used directly. If not, add the cost of creating a
// shuffle to extract the values into a vector register.
SmallVector<int> RegMask(EltsPerVector, PoisonMaskElem);
for (auto *V : VL) {
++Idx;
// Reached the start of a new vector registers.
if (Idx % EltsPerVector == 0) {
RegMask.assign(EltsPerVector, PoisonMaskElem);
AllConsecutive = true;
continue;
}
// Need to exclude undefs from analysis.
if (isa<UndefValue>(V) || Mask[Idx] == PoisonMaskElem)
continue;
// Check all extracts for a vector register on the target directly
// extract values in order.
unsigned CurrentIdx = *getExtractIndex(cast<Instruction>(V));
if (!isa<UndefValue>(VL[Idx - 1]) && Mask[Idx - 1] != PoisonMaskElem) {
unsigned PrevIdx = *getExtractIndex(cast<Instruction>(VL[Idx - 1]));
AllConsecutive &= PrevIdx + 1 == CurrentIdx &&
CurrentIdx % EltsPerVector == Idx % EltsPerVector;
RegMask[Idx % EltsPerVector] = CurrentIdx % EltsPerVector;
}
if (AllConsecutive)
continue;
// Skip all indices, except for the last index per vector block.
if ((Idx + 1) % EltsPerVector != 0 && Idx + 1 != VL.size())
continue;
// If we have a series of extracts which are not consecutive and hence
// cannot re-use the source vector register directly, compute the shuffle
// cost to extract the vector with EltsPerVector elements.
Cost += TTI.getShuffleCost(
TargetTransformInfo::SK_PermuteSingleSrc,
FixedVectorType::get(VecTy->getElementType(), EltsPerVector),
RegMask);
}
return Cost;
}
class ShuffleCostBuilder {
const TargetTransformInfo &TTI;
static bool isEmptyOrIdentity(ArrayRef<int> Mask, unsigned VF) {
int Limit = 2 * VF;
return Mask.empty() ||
(VF == Mask.size() &&
all_of(Mask, [Limit](int Idx) { return Idx < Limit; }) &&
ShuffleVectorInst::isIdentityMask(Mask));
}
public:
ShuffleCostBuilder(const TargetTransformInfo &TTI) : TTI(TTI) {}
~ShuffleCostBuilder() = default;
InstructionCost createShuffleVector(Value *V1, Value *,
ArrayRef<int> Mask) const {
// Empty mask or identity mask are free.
unsigned VF =
cast<VectorType>(V1->getType())->getElementCount().getKnownMinValue();
if (isEmptyOrIdentity(Mask, VF))
return TTI::TCC_Free;
return TTI.getShuffleCost(
TTI::SK_PermuteTwoSrc,
FixedVectorType::get(
cast<VectorType>(V1->getType())->getElementType(), Mask.size()),
Mask);
}
InstructionCost createShuffleVector(Value *V1, ArrayRef<int> Mask) const {
// Empty mask or identity mask are free.
if (isEmptyOrIdentity(Mask, Mask.size()))
return TTI::TCC_Free;
return TTI.getShuffleCost(
TTI::SK_PermuteSingleSrc,
FixedVectorType::get(
cast<VectorType>(V1->getType())->getElementType(), Mask.size()),
Mask);
}
InstructionCost createIdentity(Value *) const { return TTI::TCC_Free; }
InstructionCost createPoison(Type *Ty, unsigned VF) const {
return TTI::TCC_Free;
}
void resizeToMatch(Value *&, Value *&) const {}
};
/// Smart shuffle instruction emission, walks through shuffles trees and
/// tries to find the best matching vector for the actual shuffle
/// instruction.
InstructionCost
createShuffle(const PointerUnion<Value *, const TreeEntry *> &P1,
const PointerUnion<Value *, const TreeEntry *> &P2,
ArrayRef<int> Mask) {
ShuffleCostBuilder Builder(TTI);
Value *V1 = P1.dyn_cast<Value *>(), *V2 = P2.dyn_cast<Value *>();
unsigned CommonVF = 0;
if (!V1) {
const TreeEntry *E = P1.get<const TreeEntry *>();
unsigned VF = E->getVectorFactor();
if (V2) {
unsigned V2VF = cast<FixedVectorType>(V2->getType())->getNumElements();
if (V2VF != VF && V2VF == E->Scalars.size())
VF = E->Scalars.size();
} else if (!P2.isNull()) {
const TreeEntry *E2 = P2.get<const TreeEntry *>();
if (E->Scalars.size() == E2->Scalars.size())
CommonVF = VF = E->Scalars.size();
}
V1 = Constant::getNullValue(
FixedVectorType::get(E->Scalars.front()->getType(), VF));
}
if (!V2 && !P2.isNull()) {
const TreeEntry *E = P2.get<const TreeEntry *>();
unsigned VF = E->getVectorFactor();
unsigned V1VF = cast<FixedVectorType>(V1->getType())->getNumElements();
if (!CommonVF && V1VF == E->Scalars.size())
CommonVF = E->Scalars.size();
if (CommonVF)
VF = CommonVF;
V2 = Constant::getNullValue(
FixedVectorType::get(E->Scalars.front()->getType(), VF));
}
return BaseShuffleAnalysis::createShuffle<InstructionCost>(V1, V2, Mask,
Builder);
}
public:
ShuffleCostEstimator(TargetTransformInfo &TTI,
ArrayRef<Value *> VectorizedVals, BoUpSLP &R,
SmallPtrSetImpl<Value *> &CheckedExtracts)
: TTI(TTI), VectorizedVals(VectorizedVals), R(R),
CheckedExtracts(CheckedExtracts) {}
Value *adjustExtracts(const TreeEntry *E, ArrayRef<int> Mask,
TTI::ShuffleKind ShuffleKind) {
if (Mask.empty())
return nullptr;
Value *VecBase = nullptr;
ArrayRef<Value *> VL = E->Scalars;
auto *VecTy = FixedVectorType::get(VL.front()->getType(), VL.size());
// If the resulting type is scalarized, do not adjust the cost.
unsigned VecNumParts = TTI.getNumberOfParts(VecTy);
if (VecNumParts == VecTy->getNumElements())
return nullptr;
DenseMap<Value *, int> ExtractVectorsTys;
for (auto [I, V] : enumerate(VL)) {
// Ignore non-extractelement scalars.
if (isa<UndefValue>(V) || (!Mask.empty() && Mask[I] == PoisonMaskElem))
continue;
// If all users of instruction are going to be vectorized and this
// instruction itself is not going to be vectorized, consider this
// instruction as dead and remove its cost from the final cost of the
// vectorized tree.
// Also, avoid adjusting the cost for extractelements with multiple uses
// in different graph entries.
const TreeEntry *VE = R.getTreeEntry(V);
if (!CheckedExtracts.insert(V).second ||
!R.areAllUsersVectorized(cast<Instruction>(V), VectorizedVals) ||
(VE && VE != E))
continue;
auto *EE = cast<ExtractElementInst>(V);
VecBase = EE->getVectorOperand();
std::optional<unsigned> EEIdx = getExtractIndex(EE);
if (!EEIdx)
continue;
unsigned Idx = *EEIdx;
if (VecNumParts != TTI.getNumberOfParts(EE->getVectorOperandType())) {
auto It =
ExtractVectorsTys.try_emplace(EE->getVectorOperand(), Idx).first;
It->getSecond() = std::min<int>(It->second, Idx);
}
// Take credit for instruction that will become dead.
if (EE->hasOneUse()) {
Instruction *Ext = EE->user_back();
if (isa<SExtInst, ZExtInst>(Ext) && all_of(Ext->users(), [](User *U) {
return isa<GetElementPtrInst>(U);
})) {
// Use getExtractWithExtendCost() to calculate the cost of
// extractelement/ext pair.
Cost -= TTI.getExtractWithExtendCost(Ext->getOpcode(), Ext->getType(),
EE->getVectorOperandType(), Idx);
// Add back the cost of s|zext which is subtracted separately.
Cost += TTI.getCastInstrCost(
Ext->getOpcode(), Ext->getType(), EE->getType(),
TTI::getCastContextHint(Ext), CostKind, Ext);
continue;
}
}
Cost -= TTI.getVectorInstrCost(*EE, EE->getVectorOperandType(), CostKind,
Idx);
}
// Add a cost for subvector extracts/inserts if required.
for (const auto &Data : ExtractVectorsTys) {
auto *EEVTy = cast<FixedVectorType>(Data.first->getType());
unsigned NumElts = VecTy->getNumElements();
if (Data.second % NumElts == 0)
continue;
if (TTI.getNumberOfParts(EEVTy) > VecNumParts) {
unsigned Idx = (Data.second / NumElts) * NumElts;
unsigned EENumElts = EEVTy->getNumElements();
if (Idx % NumElts == 0)
continue;
if (Idx + NumElts <= EENumElts) {
Cost += TTI.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector,
EEVTy, std::nullopt, CostKind, Idx, VecTy);
} else {
// Need to round up the subvector type vectorization factor to avoid a
// crash in cost model functions. Make SubVT so that Idx + VF of SubVT
// <= EENumElts.
auto *SubVT =
FixedVectorType::get(VecTy->getElementType(), EENumElts - Idx);
Cost += TTI.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector,
EEVTy, std::nullopt, CostKind, Idx, SubVT);
}
} else {
Cost += TTI.getShuffleCost(TargetTransformInfo::SK_InsertSubvector,
VecTy, std::nullopt, CostKind, 0, EEVTy);
}
}
// Check that gather of extractelements can be represented as just a
// shuffle of a single/two vectors the scalars are extracted from.
// Found the bunch of extractelement instructions that must be gathered
// into a vector and can be represented as a permutation elements in a
// single input vector or of 2 input vectors.
Cost += computeExtractCost(VL, Mask, ShuffleKind);
return VecBase;
}
void add(const TreeEntry *E1, const TreeEntry *E2, ArrayRef<int> Mask) {
CommonMask.assign(Mask.begin(), Mask.end());
InVectors.assign({E1, E2});
}
void add(const TreeEntry *E1, ArrayRef<int> Mask) {
CommonMask.assign(Mask.begin(), Mask.end());
InVectors.assign(1, E1);
}
/// Adds another one input vector and the mask for the shuffling.
void add(Value *V1, ArrayRef<int> Mask) {
assert(CommonMask.empty() && InVectors.empty() &&
"Expected empty input mask/vectors.");
CommonMask.assign(Mask.begin(), Mask.end());
InVectors.assign(1, V1);
}
Value *gather(ArrayRef<Value *> VL, Value *Root = nullptr) {
Cost += getBuildVectorCost(VL, Root);
if (!Root) {
assert(InVectors.empty() && "Unexpected input vectors for buildvector.");
// FIXME: Need to find a way to avoid use of getNullValue here.
SmallVector<Constant *> Vals;
for (Value *V : VL) {
if (isa<UndefValue>(V)) {
Vals.push_back(cast<Constant>(V));
continue;
}
Vals.push_back(Constant::getNullValue(V->getType()));
}
return ConstantVector::get(Vals);
}
return ConstantVector::getSplat(
ElementCount::getFixed(VL.size()),
Constant::getNullValue(VL.front()->getType()));
}
/// Finalize emission of the shuffles.
InstructionCost
finalize(ArrayRef<int> ExtMask, unsigned VF = 0,
function_ref<void(Value *&, SmallVectorImpl<int> &)> Action = {}) {
IsFinalized = true;
if (Action) {
const PointerUnion<Value *, const TreeEntry *> &Vec = InVectors.front();
if (InVectors.size() == 2) {
Cost += createShuffle(Vec, InVectors.back(), CommonMask);
InVectors.pop_back();
} else {
Cost += createShuffle(Vec, nullptr, CommonMask);
}
for (unsigned Idx = 0, Sz = CommonMask.size(); Idx < Sz; ++Idx)
if (CommonMask[Idx] != PoisonMaskElem)
CommonMask[Idx] = Idx;
assert(VF > 0 &&
"Expected vector length for the final value before action.");
Value *V = Vec.dyn_cast<Value *>();
if (!Vec.isNull() && !V)
V = Constant::getNullValue(FixedVectorType::get(
Vec.get<const TreeEntry *>()->Scalars.front()->getType(),
CommonMask.size()));
Action(V, CommonMask);
}
::addMask(CommonMask, ExtMask, /*ExtendingManyInputs=*/true);
if (CommonMask.empty())
return Cost;
int Limit = CommonMask.size() * 2;
if (all_of(CommonMask, [=](int Idx) { return Idx < Limit; }) &&
ShuffleVectorInst::isIdentityMask(CommonMask))
return Cost;
return Cost +
createShuffle(InVectors.front(),
InVectors.size() == 2 ? InVectors.back() : nullptr,
CommonMask);
}
~ShuffleCostEstimator() {
assert((IsFinalized || CommonMask.empty()) &&
"Shuffle construction must be finalized.");
}
};
InstructionCost
BoUpSLP::getEntryCost(const TreeEntry *E, ArrayRef<Value *> VectorizedVals,
SmallPtrSetImpl<Value *> &CheckedExtracts) {
ArrayRef<Value *> VL = E->Scalars;
Type *ScalarTy = VL[0]->getType();
if (auto *SI = dyn_cast<StoreInst>(VL[0]))
ScalarTy = SI->getValueOperand()->getType();
else if (auto *CI = dyn_cast<CmpInst>(VL[0]))
ScalarTy = CI->getOperand(0)->getType();
else if (auto *IE = dyn_cast<InsertElementInst>(VL[0]))
ScalarTy = IE->getOperand(1)->getType();
auto *VecTy = FixedVectorType::get(ScalarTy, VL.size());
TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
// If we have computed a smaller type for the expression, update VecTy so
// that the costs will be accurate.
if (MinBWs.count(VL[0]))
VecTy = FixedVectorType::get(
IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size());
unsigned EntryVF = E->getVectorFactor();
auto *FinalVecTy = FixedVectorType::get(VecTy->getElementType(), EntryVF);
bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty();
if (E->State == TreeEntry::NeedToGather) {
if (allConstant(VL))
return 0;
if (isa<InsertElementInst>(VL[0]))
return InstructionCost::getInvalid();
ShuffleCostEstimator Estimator(*TTI, VectorizedVals, *this,
CheckedExtracts);
unsigned VF = E->getVectorFactor();
SmallVector<int> ReuseShuffleIndicies(E->ReuseShuffleIndices.begin(),
E->ReuseShuffleIndices.end());
SmallVector<Value *> GatheredScalars(E->Scalars.begin(), E->Scalars.end());
// Build a mask out of the reorder indices and reorder scalars per this
// mask.
SmallVector<int> ReorderMask;
inversePermutation(E->ReorderIndices, ReorderMask);
if (!ReorderMask.empty())
reorderScalars(GatheredScalars, ReorderMask);
SmallVector<int> Mask;
SmallVector<int> ExtractMask;
std::optional<TargetTransformInfo::ShuffleKind> ExtractShuffle;
std::optional<TargetTransformInfo::ShuffleKind> GatherShuffle;
SmallVector<const TreeEntry *> Entries;
Type *ScalarTy = GatheredScalars.front()->getType();
// Check for gathered extracts.
ExtractShuffle = tryToGatherExtractElements(GatheredScalars, ExtractMask);
SmallVector<Value *> IgnoredVals;
if (UserIgnoreList)
IgnoredVals.assign(UserIgnoreList->begin(), UserIgnoreList->end());
bool Resized = false;
if (Value *VecBase = Estimator.adjustExtracts(
E, ExtractMask, ExtractShuffle.value_or(TTI::SK_PermuteTwoSrc)))
if (auto *VecBaseTy = dyn_cast<FixedVectorType>(VecBase->getType()))
if (VF == VecBaseTy->getNumElements() && GatheredScalars.size() != VF) {
Resized = true;
GatheredScalars.append(VF - GatheredScalars.size(),
PoisonValue::get(ScalarTy));
}
// Do not try to look for reshuffled loads for gathered loads (they will be
// handled later), for vectorized scalars, and cases, which are definitely
// not profitable (splats and small gather nodes.)
if (ExtractShuffle || E->getOpcode() != Instruction::Load ||
E->isAltShuffle() ||
all_of(E->Scalars, [this](Value *V) { return getTreeEntry(V); }) ||
isSplat(E->Scalars) ||
(E->Scalars != GatheredScalars && GatheredScalars.size() <= 2))
GatherShuffle = isGatherShuffledEntry(E, GatheredScalars, Mask, Entries);
if (GatherShuffle) {
assert((Entries.size() == 1 || Entries.size() == 2) &&
"Expected shuffle of 1 or 2 entries.");
if (*GatherShuffle == TTI::SK_PermuteSingleSrc &&
Entries.front()->isSame(E->Scalars)) {
// Perfect match in the graph, will reuse the previously vectorized
// node. Cost is 0.
LLVM_DEBUG(
dbgs()
<< "SLP: perfect diamond match for gather bundle that starts with "
<< *VL.front() << ".\n");
return 0;
}
if (!Resized) {
unsigned VF1 = Entries.front()->getVectorFactor();
unsigned VF2 = Entries.back()->getVectorFactor();
if ((VF == VF1 || VF == VF2) && GatheredScalars.size() != VF)
GatheredScalars.append(VF - GatheredScalars.size(),
PoisonValue::get(ScalarTy));
}
// Remove shuffled elements from list of gathers.
for (int I = 0, Sz = Mask.size(); I < Sz; ++I) {
if (Mask[I] != PoisonMaskElem)
GatheredScalars[I] = PoisonValue::get(ScalarTy);
}
LLVM_DEBUG(dbgs() << "SLP: shuffled " << Entries.size()
<< " entries for bundle that starts with "
<< *VL.front() << ".\n";);
if (Entries.size() == 1)
Estimator.add(Entries.front(), Mask);
else
Estimator.add(Entries.front(), Entries.back(), Mask);
if (all_of(GatheredScalars, PoisonValue ::classof))
return Estimator.finalize(E->ReuseShuffleIndices);
return Estimator.finalize(
E->ReuseShuffleIndices, E->Scalars.size(),
[&](Value *&Vec, SmallVectorImpl<int> &Mask) {
Vec = Estimator.gather(GatheredScalars,
Constant::getNullValue(FixedVectorType::get(
GatheredScalars.front()->getType(),
GatheredScalars.size())));
});
}
if (!all_of(GatheredScalars, PoisonValue::classof)) {
auto Gathers = ArrayRef(GatheredScalars).take_front(VL.size());
bool SameGathers = VL.equals(Gathers);
Value *BV = Estimator.gather(
Gathers, SameGathers ? nullptr
: Constant::getNullValue(FixedVectorType::get(
GatheredScalars.front()->getType(),
GatheredScalars.size())));
SmallVector<int> ReuseMask(Gathers.size(), PoisonMaskElem);
std::iota(ReuseMask.begin(), ReuseMask.end(), 0);
Estimator.add(BV, ReuseMask);
}
if (ExtractShuffle)
Estimator.add(E, std::nullopt);
return Estimator.finalize(E->ReuseShuffleIndices);
}
InstructionCost CommonCost = 0;
SmallVector<int> Mask;
if (!E->ReorderIndices.empty()) {
SmallVector<int> NewMask;
if (E->getOpcode() == Instruction::Store) {
// For stores the order is actually a mask.
NewMask.resize(E->ReorderIndices.size());
copy(E->ReorderIndices, NewMask.begin());
} else {
inversePermutation(E->ReorderIndices, NewMask);
}
::addMask(Mask, NewMask);
}
if (NeedToShuffleReuses)
::addMask(Mask, E->ReuseShuffleIndices);
if (!Mask.empty() && !ShuffleVectorInst::isIdentityMask(Mask))
CommonCost =
TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, FinalVecTy, Mask);
assert((E->State == TreeEntry::Vectorize ||
E->State == TreeEntry::ScatterVectorize) &&
"Unhandled state");
assert(E->getOpcode() &&
((allSameType(VL) && allSameBlock(VL)) ||
(E->getOpcode() == Instruction::GetElementPtr &&
E->getMainOp()->getType()->isPointerTy())) &&
"Invalid VL");
Instruction *VL0 = E->getMainOp();
unsigned ShuffleOrOp =
E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode();
const unsigned Sz = VL.size();
auto GetCostDiff =
[=](function_ref<InstructionCost(unsigned)> ScalarEltCost,
function_ref<InstructionCost(InstructionCost)> VectorCost) {
// Calculate the cost of this instruction.
InstructionCost ScalarCost = 0;
if (isa<CastInst, CmpInst, SelectInst, CallInst>(VL0)) {
// For some of the instructions no need to calculate cost for each
// particular instruction, we can use the cost of the single
// instruction x total number of scalar instructions.
ScalarCost = Sz * ScalarEltCost(0);
} else {
for (unsigned I = 0; I < Sz; ++I)
ScalarCost += ScalarEltCost(I);
}
InstructionCost VecCost = VectorCost(CommonCost);
LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost - CommonCost,
ScalarCost, "Calculated costs for Tree"));
return VecCost - ScalarCost;
};
// Calculate cost difference from vectorizing set of GEPs.
// Negative value means vectorizing is profitable.
auto GetGEPCostDiff = [=](ArrayRef<Value *> Ptrs, Value *BasePtr) {
InstructionCost ScalarCost = 0;
InstructionCost VecCost = 0;
// Here we differentiate two cases: (1) when Ptrs represent a regular
// vectorization tree node (as they are pointer arguments of scattered
// loads) or (2) when Ptrs are the arguments of loads or stores being
// vectorized as plane wide unit-stride load/store since all the
// loads/stores are known to be from/to adjacent locations.
assert(E->State == TreeEntry::Vectorize &&
"Entry state expected to be Vectorize here.");
if (isa<LoadInst, StoreInst>(VL0)) {
// Case 2: estimate costs for pointer related costs when vectorizing to
// a wide load/store.
// Scalar cost is estimated as a set of pointers with known relationship
// between them.
// For vector code we will use BasePtr as argument for the wide load/store
// but we also need to account all the instructions which are going to
// stay in vectorized code due to uses outside of these scalar
// loads/stores.
ScalarCost = TTI->getPointersChainCost(
Ptrs, BasePtr, TTI::PointersChainInfo::getUnitStride(), ScalarTy,
CostKind);
SmallVector<const Value *> PtrsRetainedInVecCode;
for (Value *V : Ptrs) {
if (V == BasePtr) {
PtrsRetainedInVecCode.push_back(V);
continue;
}
auto *Ptr = dyn_cast<GetElementPtrInst>(V);
// For simplicity assume Ptr to stay in vectorized code if it's not a
// GEP instruction. We don't care since it's cost considered free.
// TODO: We should check for any uses outside of vectorizable tree
// rather than just single use.
if (!Ptr || !Ptr->hasOneUse())
PtrsRetainedInVecCode.push_back(V);
}
if (PtrsRetainedInVecCode.size() == Ptrs.size()) {
// If all pointers stay in vectorized code then we don't have
// any savings on that.
LLVM_DEBUG(dumpTreeCosts(E, 0, ScalarCost, ScalarCost,
"Calculated GEPs cost for Tree"));
return InstructionCost{TTI::TCC_Free};
}
VecCost = TTI->getPointersChainCost(
PtrsRetainedInVecCode, BasePtr,
TTI::PointersChainInfo::getKnownStride(), VecTy, CostKind);
} else {
// Case 1: Ptrs are the arguments of loads that we are going to transform
// into masked gather load intrinsic.
// All the scalar GEPs will be removed as a result of vectorization.
// For any external uses of some lanes extract element instructions will
// be generated (which cost is estimated separately).
TTI::PointersChainInfo PtrsInfo =
all_of(Ptrs,
[](const Value *V) {
auto *Ptr = dyn_cast<GetElementPtrInst>(V);
return Ptr && !Ptr->hasAllConstantIndices();
})
? TTI::PointersChainInfo::getUnknownStride()
: TTI::PointersChainInfo::getKnownStride();
ScalarCost = TTI->getPointersChainCost(Ptrs, BasePtr, PtrsInfo, ScalarTy,
CostKind);
// Remark: it not quite correct to use scalar GEP cost for a vector GEP,
// but it's not clear how to do that without having vector GEP arguments
// ready.
// Perhaps using just TTI::TCC_Free/TTI::TCC_Basic would be better option.
if (const auto *Base = dyn_cast<GetElementPtrInst>(BasePtr)) {
SmallVector<const Value *> Indices(Base->indices());
VecCost = TTI->getGEPCost(Base->getSourceElementType(),
Base->getPointerOperand(), Indices, CostKind);
}
}
LLVM_DEBUG(dumpTreeCosts(E, 0, VecCost, ScalarCost,
"Calculated GEPs cost for Tree"));
return VecCost - ScalarCost;
};
switch (ShuffleOrOp) {
case Instruction::PHI: {
// Count reused scalars.
InstructionCost ScalarCost = 0;
SmallPtrSet<const TreeEntry *, 4> CountedOps;
for (Value *V : VL) {
auto *PHI = dyn_cast<PHINode>(V);
if (!PHI)
continue;
ValueList Operands(PHI->getNumIncomingValues(), nullptr);
for (unsigned I = 0, N = PHI->getNumIncomingValues(); I < N; ++I) {
Value *Op = PHI->getIncomingValue(I);
Operands[I] = Op;
}
if (const TreeEntry *OpTE = getTreeEntry(Operands.front()))
if (OpTE->isSame(Operands) && CountedOps.insert(OpTE).second)
if (!OpTE->ReuseShuffleIndices.empty())
ScalarCost += TTI::TCC_Basic * (OpTE->ReuseShuffleIndices.size() -
OpTE->Scalars.size());
}
return CommonCost - ScalarCost;
}
case Instruction::ExtractValue:
case Instruction::ExtractElement: {
auto GetScalarCost = [=](unsigned Idx) {
auto *I = cast<Instruction>(VL[Idx]);
VectorType *SrcVecTy;
if (ShuffleOrOp == Instruction::ExtractElement) {
auto *EE = cast<ExtractElementInst>(I);
SrcVecTy = EE->getVectorOperandType();
} else {
auto *EV = cast<ExtractValueInst>(I);
Type *AggregateTy = EV->getAggregateOperand()->getType();
unsigned NumElts;
if (auto *ATy = dyn_cast<ArrayType>(AggregateTy))
NumElts = ATy->getNumElements();
else
NumElts = AggregateTy->getStructNumElements();
SrcVecTy = FixedVectorType::get(ScalarTy, NumElts);
}
if (I->hasOneUse()) {
Instruction *Ext = I->user_back();
if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) &&
all_of(Ext->users(),
[](User *U) { return isa<GetElementPtrInst>(U); })) {
// Use getExtractWithExtendCost() to calculate the cost of
// extractelement/ext pair.
InstructionCost Cost = TTI->getExtractWithExtendCost(
Ext->getOpcode(), Ext->getType(), SrcVecTy, *getExtractIndex(I));
// Subtract the cost of s|zext which is subtracted separately.
Cost -= TTI->getCastInstrCost(
Ext->getOpcode(), Ext->getType(), I->getType(),
TTI::getCastContextHint(Ext), CostKind, Ext);
return Cost;
}
}
return TTI->getVectorInstrCost(Instruction::ExtractElement, SrcVecTy,
CostKind, *getExtractIndex(I));
};
auto GetVectorCost = [](InstructionCost CommonCost) { return CommonCost; };
return GetCostDiff(GetScalarCost, GetVectorCost);
}
case Instruction::InsertElement: {
assert(E->ReuseShuffleIndices.empty() &&
"Unique insertelements only are expected.");
auto *SrcVecTy = cast<FixedVectorType>(VL0->getType());
unsigned const NumElts = SrcVecTy->getNumElements();
unsigned const NumScalars = VL.size();
unsigned NumOfParts = TTI->getNumberOfParts(SrcVecTy);
SmallVector<int> InsertMask(NumElts, PoisonMaskElem);
unsigned OffsetBeg = *getInsertIndex(VL.front());
unsigned OffsetEnd = OffsetBeg;
InsertMask[OffsetBeg] = 0;
for (auto [I, V] : enumerate(VL.drop_front())) {
unsigned Idx = *getInsertIndex(V);
if (OffsetBeg > Idx)
OffsetBeg = Idx;
else if (OffsetEnd < Idx)
OffsetEnd = Idx;
InsertMask[Idx] = I + 1;
}
unsigned VecScalarsSz = PowerOf2Ceil(NumElts);
if (NumOfParts > 0)
VecScalarsSz = PowerOf2Ceil((NumElts + NumOfParts - 1) / NumOfParts);
unsigned VecSz = (1 + OffsetEnd / VecScalarsSz - OffsetBeg / VecScalarsSz) *
VecScalarsSz;
unsigned Offset = VecScalarsSz * (OffsetBeg / VecScalarsSz);
unsigned InsertVecSz = std::min<unsigned>(
PowerOf2Ceil(OffsetEnd - OffsetBeg + 1),
((OffsetEnd - OffsetBeg + VecScalarsSz) / VecScalarsSz) * VecScalarsSz);
bool IsWholeSubvector =
OffsetBeg == Offset && ((OffsetEnd + 1) % VecScalarsSz == 0);
// Check if we can safely insert a subvector. If it is not possible, just
// generate a whole-sized vector and shuffle the source vector and the new
// subvector.
if (OffsetBeg + InsertVecSz > VecSz) {
// Align OffsetBeg to generate correct mask.
OffsetBeg = alignDown(OffsetBeg, VecSz, Offset);
InsertVecSz = VecSz;
}
APInt DemandedElts = APInt::getZero(NumElts);
// TODO: Add support for Instruction::InsertValue.
SmallVector<int> Mask;
if (!E->ReorderIndices.empty()) {
inversePermutation(E->ReorderIndices, Mask);
Mask.append(InsertVecSz - Mask.size(), PoisonMaskElem);
} else {
Mask.assign(VecSz, PoisonMaskElem);
std::iota(Mask.begin(), std::next(Mask.begin(), InsertVecSz), 0);
}
bool IsIdentity = true;
SmallVector<int> PrevMask(InsertVecSz, PoisonMaskElem);
Mask.swap(PrevMask);
for (unsigned I = 0; I < NumScalars; ++I) {
unsigned InsertIdx = *getInsertIndex(VL[PrevMask[I]]);
DemandedElts.setBit(InsertIdx);
IsIdentity &= InsertIdx - OffsetBeg == I;
Mask[InsertIdx - OffsetBeg] = I;
}
assert(Offset < NumElts && "Failed to find vector index offset");
InstructionCost Cost = 0;
Cost -= TTI->getScalarizationOverhead(SrcVecTy, DemandedElts,
/*Insert*/ true, /*Extract*/ false,
CostKind);
// First cost - resize to actual vector size if not identity shuffle or
// need to shift the vector.
// Do not calculate the cost if the actual size is the register size and
// we can merge this shuffle with the following SK_Select.
auto *InsertVecTy =
FixedVectorType::get(SrcVecTy->getElementType(), InsertVecSz);
if (!IsIdentity)
Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc,
InsertVecTy, Mask);
auto *FirstInsert = cast<Instruction>(*find_if(E->Scalars, [E](Value *V) {
return !is_contained(E->Scalars, cast<Instruction>(V)->getOperand(0));
}));
// Second cost - permutation with subvector, if some elements are from the
// initial vector or inserting a subvector.
// TODO: Implement the analysis of the FirstInsert->getOperand(0)
// subvector of ActualVecTy.
SmallBitVector InMask =
isUndefVector(FirstInsert->getOperand(0),
buildUseMask(NumElts, InsertMask, UseMask::UndefsAsMask));
if (!InMask.all() && NumScalars != NumElts && !IsWholeSubvector) {
if (InsertVecSz != VecSz) {
auto *ActualVecTy =
FixedVectorType::get(SrcVecTy->getElementType(), VecSz);
Cost += TTI->getShuffleCost(TTI::SK_InsertSubvector, ActualVecTy,
std::nullopt, CostKind, OffsetBeg - Offset,
InsertVecTy);
} else {
for (unsigned I = 0, End = OffsetBeg - Offset; I < End; ++I)
Mask[I] = InMask.test(I) ? PoisonMaskElem : I;
for (unsigned I = OffsetBeg - Offset, End = OffsetEnd - Offset;
I <= End; ++I)
if (Mask[I] != PoisonMaskElem)
Mask[I] = I + VecSz;
for (unsigned I = OffsetEnd + 1 - Offset; I < VecSz; ++I)
Mask[I] =
((I >= InMask.size()) || InMask.test(I)) ? PoisonMaskElem : I;
Cost += TTI->getShuffleCost(TTI::SK_PermuteTwoSrc, InsertVecTy, Mask);
}
}
return Cost;
}
case Instruction::ZExt:
case Instruction::SExt:
case Instruction::FPToUI:
case Instruction::FPToSI:
case Instruction::FPExt:
case Instruction::PtrToInt:
case Instruction::IntToPtr:
case Instruction::SIToFP:
case Instruction::UIToFP:
case Instruction::Trunc:
case Instruction::FPTrunc:
case Instruction::BitCast: {
auto GetScalarCost = [=](unsigned Idx) {
auto *VI = cast<Instruction>(VL[Idx]);
return TTI->getCastInstrCost(E->getOpcode(), ScalarTy,
VI->getOperand(0)->getType(),
TTI::getCastContextHint(VI), CostKind, VI);
};
auto GetVectorCost = [=](InstructionCost CommonCost) {
Type *SrcTy = VL0->getOperand(0)->getType();
auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size());
InstructionCost VecCost = CommonCost;
// Check if the values are candidates to demote.
if (!MinBWs.count(VL0) || VecTy != SrcVecTy)
VecCost +=
TTI->getCastInstrCost(E->getOpcode(), VecTy, SrcVecTy,
TTI::getCastContextHint(VL0), CostKind, VL0);
return VecCost;
};
return GetCostDiff(GetScalarCost, GetVectorCost);
}
case Instruction::FCmp:
case Instruction::ICmp:
case Instruction::Select: {
CmpInst::Predicate VecPred, SwappedVecPred;
auto MatchCmp = m_Cmp(VecPred, m_Value(), m_Value());
if (match(VL0, m_Select(MatchCmp, m_Value(), m_Value())) ||
match(VL0, MatchCmp))
SwappedVecPred = CmpInst::getSwappedPredicate(VecPred);
else
SwappedVecPred = VecPred = ScalarTy->isFloatingPointTy()
? CmpInst::BAD_FCMP_PREDICATE
: CmpInst::BAD_ICMP_PREDICATE;
auto GetScalarCost = [&](unsigned Idx) {
auto *VI = cast<Instruction>(VL[Idx]);
CmpInst::Predicate CurrentPred = ScalarTy->isFloatingPointTy()
? CmpInst::BAD_FCMP_PREDICATE
: CmpInst::BAD_ICMP_PREDICATE;
auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value());
if ((!match(VI, m_Select(MatchCmp, m_Value(), m_Value())) &&
!match(VI, MatchCmp)) ||
(CurrentPred != VecPred && CurrentPred != SwappedVecPred))
VecPred = SwappedVecPred = ScalarTy->isFloatingPointTy()
? CmpInst::BAD_FCMP_PREDICATE
: CmpInst::BAD_ICMP_PREDICATE;
return TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy,
Builder.getInt1Ty(), CurrentPred, CostKind,
VI);
};
auto GetVectorCost = [&](InstructionCost CommonCost) {
auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size());
InstructionCost VecCost = TTI->getCmpSelInstrCost(
E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0);
// Check if it is possible and profitable to use min/max for selects
// in VL.
//
auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL);
if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) {
IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy,
{VecTy, VecTy});
InstructionCost IntrinsicCost =
TTI->getIntrinsicInstrCost(CostAttrs, CostKind);
// If the selects are the only uses of the compares, they will be
// dead and we can adjust the cost by removing their cost.
if (IntrinsicAndUse.second)
IntrinsicCost -= TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy,
MaskTy, VecPred, CostKind);
VecCost = std::min(VecCost, IntrinsicCost);
}
return VecCost + CommonCost;
};
return GetCostDiff(GetScalarCost, GetVectorCost);
}
case Instruction::FNeg:
case Instruction::Add:
case Instruction::FAdd:
case Instruction::Sub:
case Instruction::FSub:
case Instruction::Mul:
case Instruction::FMul:
case Instruction::UDiv:
case Instruction::SDiv:
case Instruction::FDiv:
case Instruction::URem:
case Instruction::SRem:
case Instruction::FRem:
case Instruction::Shl:
case Instruction::LShr:
case Instruction::AShr:
case Instruction::And:
case Instruction::Or:
case Instruction::Xor: {
auto GetScalarCost = [=](unsigned Idx) {
auto *VI = cast<Instruction>(VL[Idx]);
unsigned OpIdx = isa<UnaryOperator>(VI) ? 0 : 1;
TTI::OperandValueInfo Op1Info = TTI::getOperandInfo(VI->getOperand(0));
TTI::OperandValueInfo Op2Info =
TTI::getOperandInfo(VI->getOperand(OpIdx));
SmallVector<const Value *> Operands(VI->operand_values());
return TTI->getArithmeticInstrCost(ShuffleOrOp, ScalarTy, CostKind,
Op1Info, Op2Info, Operands, VI);
};
auto GetVectorCost = [=](InstructionCost CommonCost) {
unsigned OpIdx = isa<UnaryOperator>(VL0) ? 0 : 1;
TTI::OperandValueInfo Op1Info = getOperandInfo(VL, 0);
TTI::OperandValueInfo Op2Info = getOperandInfo(VL, OpIdx);
return TTI->getArithmeticInstrCost(ShuffleOrOp, VecTy, CostKind, Op1Info,
Op2Info) +
CommonCost;
};
return GetCostDiff(GetScalarCost, GetVectorCost);
}
case Instruction::GetElementPtr: {
return CommonCost + GetGEPCostDiff(VL, VL0);
}
case Instruction::Load: {
auto GetScalarCost = [=](unsigned Idx) {
auto *VI = cast<LoadInst>(VL[Idx]);
return TTI->getMemoryOpCost(Instruction::Load, ScalarTy, VI->getAlign(),
VI->getPointerAddressSpace(), CostKind,
TTI::OperandValueInfo(), VI);
};
auto *LI0 = cast<LoadInst>(VL0);
auto GetVectorCost = [=](InstructionCost CommonCost) {
InstructionCost VecLdCost;
if (E->State == TreeEntry::Vectorize) {
VecLdCost = TTI->getMemoryOpCost(
Instruction::Load, VecTy, LI0->getAlign(),
LI0->getPointerAddressSpace(), CostKind, TTI::OperandValueInfo());
} else {
assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState");
Align CommonAlignment = LI0->getAlign();
for (Value *V : VL)
CommonAlignment =
std::min(CommonAlignment, cast<LoadInst>(V)->getAlign());
VecLdCost = TTI->getGatherScatterOpCost(
Instruction::Load, VecTy, LI0->getPointerOperand(),
/*VariableMask=*/false, CommonAlignment, CostKind);
}
return VecLdCost + CommonCost;
};
InstructionCost Cost = GetCostDiff(GetScalarCost, GetVectorCost);
// If this node generates masked gather load then it is not a terminal node.
// Hence address operand cost is estimated separately.
if (E->State == TreeEntry::ScatterVectorize)
return Cost;
// Estimate cost of GEPs since this tree node is a terminator.
SmallVector<Value *> PointerOps(VL.size());
for (auto [I, V] : enumerate(VL))
PointerOps[I] = cast<LoadInst>(V)->getPointerOperand();
return Cost + GetGEPCostDiff(PointerOps, LI0->getPointerOperand());
}
case Instruction::Store: {
bool IsReorder = !E->ReorderIndices.empty();
auto GetScalarCost = [=](unsigned Idx) {
auto *VI = cast<StoreInst>(VL[Idx]);
TTI::OperandValueInfo OpInfo = getOperandInfo(VI, 0);
return TTI->getMemoryOpCost(Instruction::Store, ScalarTy, VI->getAlign(),
VI->getPointerAddressSpace(), CostKind,
OpInfo, VI);
};
auto *BaseSI =
cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0);
auto GetVectorCost = [=](InstructionCost CommonCost) {
// We know that we can merge the stores. Calculate the cost.
TTI::OperandValueInfo OpInfo = getOperandInfo(VL, 0);
return TTI->getMemoryOpCost(Instruction::Store, VecTy, BaseSI->getAlign(),
BaseSI->getPointerAddressSpace(), CostKind,
OpInfo) +
CommonCost;
};
SmallVector<Value *> PointerOps(VL.size());
for (auto [I, V] : enumerate(VL)) {
unsigned Idx = IsReorder ? E->ReorderIndices[I] : I;
PointerOps[Idx] = cast<StoreInst>(V)->getPointerOperand();
}
return GetCostDiff(GetScalarCost, GetVectorCost) +
GetGEPCostDiff(PointerOps, BaseSI->getPointerOperand());
}
case Instruction::Call: {
auto GetScalarCost = [=](unsigned Idx) {
auto *CI = cast<CallInst>(VL[Idx]);
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
if (ID != Intrinsic::not_intrinsic) {
IntrinsicCostAttributes CostAttrs(ID, *CI, 1);
return TTI->getIntrinsicInstrCost(CostAttrs, CostKind);
}
return TTI->getCallInstrCost(CI->getCalledFunction(),
CI->getFunctionType()->getReturnType(),
CI->getFunctionType()->params(), CostKind);
};
auto GetVectorCost = [=](InstructionCost CommonCost) {
auto *CI = cast<CallInst>(VL0);
auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI);
return std::min(VecCallCosts.first, VecCallCosts.second) + CommonCost;
};
return GetCostDiff(GetScalarCost, GetVectorCost);
}
case Instruction::ShuffleVector: {
assert(E->isAltShuffle() &&
((Instruction::isBinaryOp(E->getOpcode()) &&
Instruction::isBinaryOp(E->getAltOpcode())) ||
(Instruction::isCast(E->getOpcode()) &&
Instruction::isCast(E->getAltOpcode())) ||
(isa<CmpInst>(VL0) && isa<CmpInst>(E->getAltOp()))) &&
"Invalid Shuffle Vector Operand");
// Try to find the previous shuffle node with the same operands and same
// main/alternate ops.
auto TryFindNodeWithEqualOperands = [=]() {
for (const std::unique_ptr<TreeEntry> &TE : VectorizableTree) {
if (TE.get() == E)
break;
if (TE->isAltShuffle() &&
((TE->getOpcode() == E->getOpcode() &&
TE->getAltOpcode() == E->getAltOpcode()) ||
(TE->getOpcode() == E->getAltOpcode() &&
TE->getAltOpcode() == E->getOpcode())) &&
TE->hasEqualOperands(*E))
return true;
}
return false;
};
auto GetScalarCost = [=](unsigned Idx) {
auto *VI = cast<Instruction>(VL[Idx]);
assert(E->isOpcodeOrAlt(VI) && "Unexpected main/alternate opcode");
(void)E;
return TTI->getInstructionCost(VI, CostKind);
};
// Need to clear CommonCost since the final shuffle cost is included into
// vector cost.
auto GetVectorCost = [&](InstructionCost) {
// VecCost is equal to sum of the cost of creating 2 vectors
// and the cost of creating shuffle.
InstructionCost VecCost = 0;
if (TryFindNodeWithEqualOperands()) {
LLVM_DEBUG({
dbgs() << "SLP: diamond match for alternate node found.\n";
E->dump();
});
// No need to add new vector costs here since we're going to reuse
// same main/alternate vector ops, just do different shuffling.
} else if (Instruction::isBinaryOp(E->getOpcode())) {
VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind);
VecCost +=
TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, CostKind);
} else if (auto *CI0 = dyn_cast<CmpInst>(VL0)) {
VecCost = TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy,
Builder.getInt1Ty(),
CI0->getPredicate(), CostKind, VL0);
VecCost += TTI->getCmpSelInstrCost(
E->getOpcode(), ScalarTy, Builder.getInt1Ty(),
cast<CmpInst>(E->getAltOp())->getPredicate(), CostKind,
E->getAltOp());
} else {
Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType();
Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType();
auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size());
auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size());
VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty,
TTI::CastContextHint::None, CostKind);
VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty,
TTI::CastContextHint::None, CostKind);
}
if (E->ReuseShuffleIndices.empty()) {
VecCost +=
TTI->getShuffleCost(TargetTransformInfo::SK_Select, FinalVecTy);
} else {
SmallVector<int> Mask;
buildShuffleEntryMask(
E->Scalars, E->ReorderIndices, E->ReuseShuffleIndices,
[E](Instruction *I) {
assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode");
return I->getOpcode() == E->getAltOpcode();
},
Mask);
VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteTwoSrc,
FinalVecTy, Mask);
}
return VecCost;
};
return GetCostDiff(GetScalarCost, GetVectorCost);
}
default:
llvm_unreachable("Unknown instruction");
}
}
bool BoUpSLP::isFullyVectorizableTinyTree(bool ForReduction) const {
LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height "
<< VectorizableTree.size() << " is fully vectorizable .\n");
auto &&AreVectorizableGathers = [this](const TreeEntry *TE, unsigned Limit) {
SmallVector<int> Mask;
return TE->State == TreeEntry::NeedToGather &&
!any_of(TE->Scalars,
[this](Value *V) { return EphValues.contains(V); }) &&
(allConstant(TE->Scalars) || isSplat(TE->Scalars) ||
TE->Scalars.size() < Limit ||
((TE->getOpcode() == Instruction::ExtractElement ||
all_of(TE->Scalars,
[](Value *V) {
return isa<ExtractElementInst, UndefValue>(V);
})) &&
isFixedVectorShuffle(TE->Scalars, Mask)) ||
(TE->State == TreeEntry::NeedToGather &&
TE->getOpcode() == Instruction::Load && !TE->isAltShuffle()));
};
// We only handle trees of heights 1 and 2.
if (VectorizableTree.size() == 1 &&
(VectorizableTree[0]->State == TreeEntry::Vectorize ||
(ForReduction &&
AreVectorizableGathers(VectorizableTree[0].get(),
VectorizableTree[0]->Scalars.size()) &&
VectorizableTree[0]->getVectorFactor() > 2)))
return true;
if (VectorizableTree.size() != 2)
return false;
// Handle splat and all-constants stores. Also try to vectorize tiny trees
// with the second gather nodes if they have less scalar operands rather than
// the initial tree element (may be profitable to shuffle the second gather)
// or they are extractelements, which form shuffle.
SmallVector<int> Mask;
if (VectorizableTree[0]->State == TreeEntry::Vectorize &&
AreVectorizableGathers(VectorizableTree[1].get(),
VectorizableTree[0]->Scalars.size()))
return true;
// Gathering cost would be too much for tiny trees.
if (VectorizableTree[0]->State == TreeEntry::NeedToGather ||
(VectorizableTree[1]->State == TreeEntry::NeedToGather &&
VectorizableTree[0]->State != TreeEntry::ScatterVectorize))
return false;
return true;
}
static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts,
TargetTransformInfo *TTI,
bool MustMatchOrInst) {
// Look past the root to find a source value. Arbitrarily follow the
// path through operand 0 of any 'or'. Also, peek through optional
// shift-left-by-multiple-of-8-bits.
Value *ZextLoad = Root;
const APInt *ShAmtC;
bool FoundOr = false;
while (!isa<ConstantExpr>(ZextLoad) &&
(match(ZextLoad, m_Or(m_Value(), m_Value())) ||
(match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) &&
ShAmtC->urem(8) == 0))) {
auto *BinOp = cast<BinaryOperator>(ZextLoad);
ZextLoad = BinOp->getOperand(0);
if (BinOp->getOpcode() == Instruction::Or)
FoundOr = true;
}
// Check if the input is an extended load of the required or/shift expression.
Value *Load;
if ((MustMatchOrInst && !FoundOr) || ZextLoad == Root ||
!match(ZextLoad, m_ZExt(m_Value(Load))) || !isa<LoadInst>(Load))
return false;
// Require that the total load bit width is a legal integer type.
// For example, <8 x i8> --> i64 is a legal integer on a 64-bit target.
// But <16 x i8> --> i128 is not, so the backend probably can't reduce it.
Type *SrcTy = Load->getType();
unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts;
if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth)))
return false;
// Everything matched - assume that we can fold the whole sequence using
// load combining.
LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at "
<< *(cast<Instruction>(Root)) << "\n");
return true;
}
bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const {
if (RdxKind != RecurKind::Or)
return false;
unsigned NumElts = VectorizableTree[0]->Scalars.size();
Value *FirstReduced = VectorizableTree[0]->Scalars[0];
return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI,
/* MatchOr */ false);
}
bool BoUpSLP::isLoadCombineCandidate() const {
// Peek through a final sequence of stores and check if all operations are
// likely to be load-combined.
unsigned NumElts = VectorizableTree[0]->Scalars.size();
for (Value *Scalar : VectorizableTree[0]->Scalars) {
Value *X;
if (!match(Scalar, m_Store(m_Value(X), m_Value())) ||
!isLoadCombineCandidateImpl(X, NumElts, TTI, /* MatchOr */ true))
return false;
}
return true;
}
bool BoUpSLP::isTreeTinyAndNotFullyVectorizable(bool ForReduction) const {
// No need to vectorize inserts of gathered values.
if (VectorizableTree.size() == 2 &&
isa<InsertElementInst>(VectorizableTree[0]->Scalars[0]) &&
VectorizableTree[1]->State == TreeEntry::NeedToGather &&
(VectorizableTree[1]->getVectorFactor() <= 2 ||
!(isSplat(VectorizableTree[1]->Scalars) ||
allConstant(VectorizableTree[1]->Scalars))))
return true;
// We can vectorize the tree if its size is greater than or equal to the
// minimum size specified by the MinTreeSize command line option.
if (VectorizableTree.size() >= MinTreeSize)
return false;
// If we have a tiny tree (a tree whose size is less than MinTreeSize), we
// can vectorize it if we can prove it fully vectorizable.
if (isFullyVectorizableTinyTree(ForReduction))
return false;
assert(VectorizableTree.empty()
? ExternalUses.empty()
: true && "We shouldn't have any external users");
// Otherwise, we can't vectorize the tree. It is both tiny and not fully
// vectorizable.
return true;
}
InstructionCost BoUpSLP::getSpillCost() const {
// Walk from the bottom of the tree to the top, tracking which values are
// live. When we see a call instruction that is not part of our tree,
// query TTI to see if there is a cost to keeping values live over it
// (for example, if spills and fills are required).
unsigned BundleWidth = VectorizableTree.front()->Scalars.size();
InstructionCost Cost = 0;
SmallPtrSet<Instruction*, 4> LiveValues;
Instruction *PrevInst = nullptr;
// The entries in VectorizableTree are not necessarily ordered by their
// position in basic blocks. Collect them and order them by dominance so later
// instructions are guaranteed to be visited first. For instructions in
// different basic blocks, we only scan to the beginning of the block, so
// their order does not matter, as long as all instructions in a basic block
// are grouped together. Using dominance ensures a deterministic order.
SmallVector<Instruction *, 16> OrderedScalars;
for (const auto &TEPtr : VectorizableTree) {
if (TEPtr->State != TreeEntry::Vectorize)
continue;
Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]);
if (!Inst)
continue;
OrderedScalars.push_back(Inst);
}
llvm::sort(OrderedScalars, [&](Instruction *A, Instruction *B) {
auto *NodeA = DT->getNode(A->getParent());
auto *NodeB = DT->getNode(B->getParent());
assert(NodeA && "Should only process reachable instructions");
assert(NodeB && "Should only process reachable instructions");
assert((NodeA == NodeB) == (NodeA->getDFSNumIn() == NodeB->getDFSNumIn()) &&
"Different nodes should have different DFS numbers");
if (NodeA != NodeB)
return NodeA->getDFSNumIn() > NodeB->getDFSNumIn();
return B->comesBefore(A);
});
for (Instruction *Inst : OrderedScalars) {
if (!PrevInst) {
PrevInst = Inst;
continue;
}
// Update LiveValues.
LiveValues.erase(PrevInst);
for (auto &J : PrevInst->operands()) {
if (isa<Instruction>(&*J) && getTreeEntry(&*J))
LiveValues.insert(cast<Instruction>(&*J));
}
LLVM_DEBUG({
dbgs() << "SLP: #LV: " << LiveValues.size();
for (auto *X : LiveValues)
dbgs() << " " << X->getName();
dbgs() << ", Looking at ";
Inst->dump();
});
// Now find the sequence of instructions between PrevInst and Inst.
unsigned NumCalls = 0;
BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(),
PrevInstIt =
PrevInst->getIterator().getReverse();
while (InstIt != PrevInstIt) {
if (PrevInstIt == PrevInst->getParent()->rend()) {
PrevInstIt = Inst->getParent()->rbegin();
continue;
}
auto NoCallIntrinsic = [this](Instruction *I) {
if (auto *II = dyn_cast<IntrinsicInst>(I)) {
if (II->isAssumeLikeIntrinsic())
return true;
FastMathFlags FMF;
SmallVector<Type *, 4> Tys;
for (auto &ArgOp : II->args())
Tys.push_back(ArgOp->getType());
if (auto *FPMO = dyn_cast<FPMathOperator>(II))
FMF = FPMO->getFastMathFlags();
IntrinsicCostAttributes ICA(II->getIntrinsicID(), II->getType(), Tys,
FMF);
InstructionCost IntrCost =
TTI->getIntrinsicInstrCost(ICA, TTI::TCK_RecipThroughput);
InstructionCost CallCost = TTI->getCallInstrCost(
nullptr, II->getType(), Tys, TTI::TCK_RecipThroughput);
if (IntrCost < CallCost)
return true;
}
return false;
};
// Debug information does not impact spill cost.
if (isa<CallBase>(&*PrevInstIt) && !NoCallIntrinsic(&*PrevInstIt) &&
&*PrevInstIt != PrevInst)
NumCalls++;
++PrevInstIt;
}
if (NumCalls) {
SmallVector<Type*, 4> V;
for (auto *II : LiveValues) {
auto *ScalarTy = II->getType();
if (auto *VectorTy = dyn_cast<FixedVectorType>(ScalarTy))
ScalarTy = VectorTy->getElementType();
V.push_back(FixedVectorType::get(ScalarTy, BundleWidth));
}
Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V);
}
PrevInst = Inst;
}
return Cost;
}
/// Checks if the \p IE1 instructions is followed by \p IE2 instruction in the
/// buildvector sequence.
static bool isFirstInsertElement(const InsertElementInst *IE1,
const InsertElementInst *IE2) {
if (IE1 == IE2)
return false;
const auto *I1 = IE1;
const auto *I2 = IE2;
const InsertElementInst *PrevI1;
const InsertElementInst *PrevI2;
unsigned Idx1 = *getInsertIndex(IE1);
unsigned Idx2 = *getInsertIndex(IE2);
do {
if (I2 == IE1)
return true;
if (I1 == IE2)
return false;
PrevI1 = I1;
PrevI2 = I2;
if (I1 && (I1 == IE1 || I1->hasOneUse()) &&
getInsertIndex(I1).value_or(Idx2) != Idx2)
I1 = dyn_cast<InsertElementInst>(I1->getOperand(0));
if (I2 && ((I2 == IE2 || I2->hasOneUse())) &&
getInsertIndex(I2).value_or(Idx1) != Idx1)
I2 = dyn_cast<InsertElementInst>(I2->getOperand(0));
} while ((I1 && PrevI1 != I1) || (I2 && PrevI2 != I2));
llvm_unreachable("Two different buildvectors not expected.");
}
namespace {
/// Returns incoming Value *, if the requested type is Value * too, or a default
/// value, otherwise.
struct ValueSelect {
template <typename U>
static std::enable_if_t<std::is_same_v<Value *, U>, Value *> get(Value *V) {
return V;
}
template <typename U>
static std::enable_if_t<!std::is_same_v<Value *, U>, U> get(Value *) {
return U();
}
};
} // namespace
/// Does the analysis of the provided shuffle masks and performs the requested
/// actions on the vectors with the given shuffle masks. It tries to do it in
/// several steps.
/// 1. If the Base vector is not undef vector, resizing the very first mask to
/// have common VF and perform action for 2 input vectors (including non-undef
/// Base). Other shuffle masks are combined with the resulting after the 1 stage
/// and processed as a shuffle of 2 elements.
/// 2. If the Base is undef vector and have only 1 shuffle mask, perform the
/// action only for 1 vector with the given mask, if it is not the identity
/// mask.
/// 3. If > 2 masks are used, perform the remaining shuffle actions for 2
/// vectors, combing the masks properly between the steps.
template <typename T>
static T *performExtractsShuffleAction(
MutableArrayRef<std::pair<T *, SmallVector<int>>> ShuffleMask, Value *Base,
function_ref<unsigned(T *)> GetVF,
function_ref<std::pair<T *, bool>(T *, ArrayRef<int>, bool)> ResizeAction,
function_ref<T *(ArrayRef<int>, ArrayRef<T *>)> Action) {
assert(!ShuffleMask.empty() && "Empty list of shuffles for inserts.");
SmallVector<int> Mask(ShuffleMask.begin()->second);
auto VMIt = std::next(ShuffleMask.begin());
T *Prev = nullptr;
SmallBitVector UseMask =
buildUseMask(Mask.size(), Mask, UseMask::UndefsAsMask);
SmallBitVector IsBaseUndef = isUndefVector(Base, UseMask);
if (!IsBaseUndef.all()) {
// Base is not undef, need to combine it with the next subvectors.
std::pair<T *, bool> Res =
ResizeAction(ShuffleMask.begin()->first, Mask, /*ForSingleMask=*/false);
SmallBitVector IsBasePoison = isUndefVector<true>(Base, UseMask);
for (unsigned Idx = 0, VF = Mask.size(); Idx < VF; ++Idx) {
if (Mask[Idx] == PoisonMaskElem)
Mask[Idx] = IsBasePoison.test(Idx) ? PoisonMaskElem : Idx;
else
Mask[Idx] = (Res.second ? Idx : Mask[Idx]) + VF;
}
auto *V = ValueSelect::get<T *>(Base);
(void)V;
assert((!V || GetVF(V) == Mask.size()) &&
"Expected base vector of VF number of elements.");
Prev = Action(Mask, {nullptr, Res.first});
} else if (ShuffleMask.size() == 1) {
// Base is undef and only 1 vector is shuffled - perform the action only for
// single vector, if the mask is not the identity mask.
std::pair<T *, bool> Res = ResizeAction(ShuffleMask.begin()->first, Mask,
/*ForSingleMask=*/true);
if (Res.second)
// Identity mask is found.
Prev = Res.first;
else
Prev = Action(Mask, {ShuffleMask.begin()->first});
} else {
// Base is undef and at least 2 input vectors shuffled - perform 2 vectors
// shuffles step by step, combining shuffle between the steps.
unsigned Vec1VF = GetVF(ShuffleMask.begin()->first);
unsigned Vec2VF = GetVF(VMIt->first);
if (Vec1VF == Vec2VF) {
// No need to resize the input vectors since they are of the same size, we
// can shuffle them directly.
ArrayRef<int> SecMask = VMIt->second;
for (unsigned I = 0, VF = Mask.size(); I < VF; ++I) {
if (SecMask[I] != PoisonMaskElem) {
assert(Mask[I] == PoisonMaskElem && "Multiple uses of scalars.");
Mask[I] = SecMask[I] + Vec1VF;
}
}
Prev = Action(Mask, {ShuffleMask.begin()->first, VMIt->first});
} else {
// Vectors of different sizes - resize and reshuffle.
std::pair<T *, bool> Res1 = ResizeAction(ShuffleMask.begin()->first, Mask,
/*ForSingleMask=*/false);
std::pair<T *, bool> Res2 =
ResizeAction(VMIt->first, VMIt->second, /*ForSingleMask=*/false);
ArrayRef<int> SecMask = VMIt->second;
for (unsigned I = 0, VF = Mask.size(); I < VF; ++I) {
if (Mask[I] != PoisonMaskElem) {
assert(SecMask[I] == PoisonMaskElem && "Multiple uses of scalars.");
if (Res1.second)
Mask[I] = I;
} else if (SecMask[I] != PoisonMaskElem) {
assert(Mask[I] == PoisonMaskElem && "Multiple uses of scalars.");
Mask[I] = (Res2.second ? I : SecMask[I]) + VF;
}
}
Prev = Action(Mask, {Res1.first, Res2.first});
}
VMIt = std::next(VMIt);
}
bool IsBaseNotUndef = !IsBaseUndef.all();
(void)IsBaseNotUndef;
// Perform requested actions for the remaining masks/vectors.
for (auto E = ShuffleMask.end(); VMIt != E; ++VMIt) {
// Shuffle other input vectors, if any.
std::pair<T *, bool> Res =
ResizeAction(VMIt->first, VMIt->second, /*ForSingleMask=*/false);
ArrayRef<int> SecMask = VMIt->second;
for (unsigned I = 0, VF = Mask.size(); I < VF; ++I) {
if (SecMask[I] != PoisonMaskElem) {
assert((Mask[I] == PoisonMaskElem || IsBaseNotUndef) &&
"Multiple uses of scalars.");
Mask[I] = (Res.second ? I : SecMask[I]) + VF;
} else if (Mask[I] != PoisonMaskElem) {
Mask[I] = I;
}
}
Prev = Action(Mask, {Prev, Res.first});
}
return Prev;
}
InstructionCost BoUpSLP::getTreeCost(ArrayRef<Value *> VectorizedVals) {
// Build a map for gathered scalars to the nodes where they are used.
ValueToGatherNodes.clear();
for (const std::unique_ptr<TreeEntry> &EntryPtr : VectorizableTree) {
if (EntryPtr->State != TreeEntry::NeedToGather)
continue;
for (Value *V : EntryPtr->Scalars)
if (!isConstant(V))
ValueToGatherNodes.try_emplace(V).first->getSecond().insert(
EntryPtr.get());
}
InstructionCost Cost = 0;
LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size "
<< VectorizableTree.size() << ".\n");
unsigned BundleWidth = VectorizableTree[0]->Scalars.size();
SmallPtrSet<Value *, 4> CheckedExtracts;
for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) {
TreeEntry &TE = *VectorizableTree[I];
if (TE.State == TreeEntry::NeedToGather) {
if (const TreeEntry *E = getTreeEntry(TE.getMainOp());
E && E->getVectorFactor() == TE.getVectorFactor() &&
E->isSame(TE.Scalars)) {
// Some gather nodes might be absolutely the same as some vectorizable
// nodes after reordering, need to handle it.
LLVM_DEBUG(dbgs() << "SLP: Adding cost 0 for bundle that starts with "
<< *TE.Scalars[0] << ".\n"
<< "SLP: Current total cost = " << Cost << "\n");
continue;
}
}
InstructionCost C = getEntryCost(&TE, VectorizedVals, CheckedExtracts);
Cost += C;
LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C
<< " for bundle that starts with " << *TE.Scalars[0]
<< ".\n"
<< "SLP: Current total cost = " << Cost << "\n");
}
SmallPtrSet<Value *, 16> ExtractCostCalculated;
InstructionCost ExtractCost = 0;
SmallVector<MapVector<const TreeEntry *, SmallVector<int>>> ShuffleMasks;
SmallVector<std::pair<Value *, const TreeEntry *>> FirstUsers;
SmallVector<APInt> DemandedElts;
for (ExternalUser &EU : ExternalUses) {
// We only add extract cost once for the same scalar.
if (!isa_and_nonnull<InsertElementInst>(EU.User) &&
!ExtractCostCalculated.insert(EU.Scalar).second)
continue;
// Uses by ephemeral values are free (because the ephemeral value will be
// removed prior to code generation, and so the extraction will be
// removed as well).
if (EphValues.count(EU.User))
continue;
// No extract cost for vector "scalar"
if (isa<FixedVectorType>(EU.Scalar->getType()))
continue;
// If found user is an insertelement, do not calculate extract cost but try
// to detect it as a final shuffled/identity match.
if (auto *VU = dyn_cast_or_null<InsertElementInst>(EU.User)) {
if (auto *FTy = dyn_cast<FixedVectorType>(VU->getType())) {
std::optional<unsigned> InsertIdx = getInsertIndex(VU);
if (InsertIdx) {
const TreeEntry *ScalarTE = getTreeEntry(EU.Scalar);
auto *It = find_if(
FirstUsers,
[this, VU](const std::pair<Value *, const TreeEntry *> &Pair) {
return areTwoInsertFromSameBuildVector(
VU, cast<InsertElementInst>(Pair.first),
[this](InsertElementInst *II) -> Value * {
Value *Op0 = II->getOperand(0);
if (getTreeEntry(II) && !getTreeEntry(Op0))
return nullptr;
return Op0;
});
});
int VecId = -1;
if (It == FirstUsers.end()) {
(void)ShuffleMasks.emplace_back();
SmallVectorImpl<int> &Mask = ShuffleMasks.back()[ScalarTE];
if (Mask.empty())
Mask.assign(FTy->getNumElements(), PoisonMaskElem);
// Find the insertvector, vectorized in tree, if any.
Value *Base = VU;
while (auto *IEBase = dyn_cast<InsertElementInst>(Base)) {
if (IEBase != EU.User &&
(!IEBase->hasOneUse() ||
getInsertIndex(IEBase).value_or(*InsertIdx) == *InsertIdx))
break;
// Build the mask for the vectorized insertelement instructions.
if (const TreeEntry *E = getTreeEntry(IEBase)) {
VU = IEBase;
do {
IEBase = cast<InsertElementInst>(Base);
int Idx = *getInsertIndex(IEBase);
assert(Mask[Idx] == PoisonMaskElem &&
"InsertElementInstruction used already.");
Mask[Idx] = Idx;
Base = IEBase->getOperand(0);
} while (E == getTreeEntry(Base));
break;
}
Base = cast<InsertElementInst>(Base)->getOperand(0);
}
FirstUsers.emplace_back(VU, ScalarTE);
DemandedElts.push_back(APInt::getZero(FTy->getNumElements()));
VecId = FirstUsers.size() - 1;
} else {
if (isFirstInsertElement(VU, cast<InsertElementInst>(It->first)))
It->first = VU;
VecId = std::distance(FirstUsers.begin(), It);
}
int InIdx = *InsertIdx;
SmallVectorImpl<int> &Mask = ShuffleMasks[VecId][ScalarTE];
if (Mask.empty())
Mask.assign(FTy->getNumElements(), PoisonMaskElem);
Mask[InIdx] = EU.Lane;
DemandedElts[VecId].setBit(InIdx);
continue;
}
}
}
// If we plan to rewrite the tree in a smaller type, we will need to sign
// extend the extracted value back to the original type. Here, we account
// for the extract and the added cost of the sign extend if needed.
auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth);
TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
auto *ScalarRoot = VectorizableTree[0]->Scalars[0];
if (MinBWs.count(ScalarRoot)) {
auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first);
auto Extend =
MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt;
VecTy = FixedVectorType::get(MinTy, BundleWidth);
ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(),
VecTy, EU.Lane);
} else {
ExtractCost += TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy,
CostKind, EU.Lane);
}
}
InstructionCost SpillCost = getSpillCost();
Cost += SpillCost + ExtractCost;
auto &&ResizeToVF = [this, &Cost](const TreeEntry *TE, ArrayRef<int> Mask,
bool) {
InstructionCost C = 0;
unsigned VF = Mask.size();
unsigned VecVF = TE->getVectorFactor();
if (VF != VecVF &&
(any_of(Mask, [VF](int Idx) { return Idx >= static_cast<int>(VF); }) ||
(all_of(Mask,
[VF](int Idx) { return Idx < 2 * static_cast<int>(VF); }) &&
!ShuffleVectorInst::isIdentityMask(Mask)))) {
SmallVector<int> OrigMask(VecVF, PoisonMaskElem);
std::copy(Mask.begin(), std::next(Mask.begin(), std::min(VF, VecVF)),
OrigMask.begin());
C = TTI->getShuffleCost(
TTI::SK_PermuteSingleSrc,
FixedVectorType::get(TE->getMainOp()->getType(), VecVF), OrigMask);
LLVM_DEBUG(
dbgs() << "SLP: Adding cost " << C
<< " for final shuffle of insertelement external users.\n";
TE->dump(); dbgs() << "SLP: Current total cost = " << Cost << "\n");
Cost += C;
return std::make_pair(TE, true);
}
return std::make_pair(TE, false);
};
// Calculate the cost of the reshuffled vectors, if any.
for (int I = 0, E = FirstUsers.size(); I < E; ++I) {
Value *Base = cast<Instruction>(FirstUsers[I].first)->getOperand(0);
unsigned VF = ShuffleMasks[I].begin()->second.size();
auto *FTy = FixedVectorType::get(
cast<VectorType>(FirstUsers[I].first->getType())->getElementType(), VF);
auto Vector = ShuffleMasks[I].takeVector();
auto &&EstimateShufflesCost = [this, FTy,
&Cost](ArrayRef<int> Mask,
ArrayRef<const TreeEntry *> TEs) {
assert((TEs.size() == 1 || TEs.size() == 2) &&
"Expected exactly 1 or 2 tree entries.");
if (TEs.size() == 1) {
int Limit = 2 * Mask.size();
if (!all_of(Mask, [Limit](int Idx) { return Idx < Limit; }) ||
!ShuffleVectorInst::isIdentityMask(Mask)) {
InstructionCost C =
TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, FTy, Mask);
LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C
<< " for final shuffle of insertelement "
"external users.\n";
TEs.front()->dump();
dbgs() << "SLP: Current total cost = " << Cost << "\n");
Cost += C;
}
} else {
InstructionCost C =
TTI->getShuffleCost(TTI::SK_PermuteTwoSrc, FTy, Mask);
LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C
<< " for final shuffle of vector node and external "
"insertelement users.\n";
if (TEs.front()) { TEs.front()->dump(); } TEs.back()->dump();
dbgs() << "SLP: Current total cost = " << Cost << "\n");
Cost += C;
}
return TEs.back();
};
(void)performExtractsShuffleAction<const TreeEntry>(
MutableArrayRef(Vector.data(), Vector.size()), Base,
[](const TreeEntry *E) { return E->getVectorFactor(); }, ResizeToVF,
EstimateShufflesCost);
InstructionCost InsertCost = TTI->getScalarizationOverhead(
cast<FixedVectorType>(FirstUsers[I].first->getType()), DemandedElts[I],
/*Insert*/ true, /*Extract*/ false, TTI::TCK_RecipThroughput);
Cost -= InsertCost;
}
#ifndef NDEBUG
SmallString<256> Str;
{
raw_svector_ostream OS(Str);
OS << "SLP: Spill Cost = " << SpillCost << ".\n"
<< "SLP: Extract Cost = " << ExtractCost << ".\n"
<< "SLP: Total Cost = " << Cost << ".\n";
}
LLVM_DEBUG(dbgs() << Str);
if (ViewSLPTree)
ViewGraph(this, "SLP" + F->getName(), false, Str);
#endif
return Cost;
}
std::optional<TargetTransformInfo::ShuffleKind>
BoUpSLP::isGatherShuffledEntry(const TreeEntry *TE, ArrayRef<Value *> VL,
SmallVectorImpl<int> &Mask,
SmallVectorImpl<const TreeEntry *> &Entries) {
Entries.clear();
// No need to check for the topmost gather node.
if (TE == VectorizableTree.front().get())
return std::nullopt;
Mask.assign(VL.size(), PoisonMaskElem);
assert(TE->UserTreeIndices.size() == 1 &&
"Expected only single user of the gather node.");
// TODO: currently checking only for Scalars in the tree entry, need to count
// reused elements too for better cost estimation.
Instruction &UserInst =
getLastInstructionInBundle(TE->UserTreeIndices.front().UserTE);
BasicBlock *ParentBB = nullptr;
// Main node of PHI entries keeps the correct order of operands/incoming
// blocks.
if (auto *PHI =
dyn_cast<PHINode>(TE->UserTreeIndices.front().UserTE->getMainOp())) {
ParentBB = PHI->getIncomingBlock(TE->UserTreeIndices.front().EdgeIdx);
} else {
ParentBB = UserInst.getParent();
}
auto *NodeUI = DT->getNode(ParentBB);
assert(NodeUI && "Should only process reachable instructions");
SmallPtrSet<Value *, 4> GatheredScalars(VL.begin(), VL.end());
auto CheckOrdering = [&](Instruction *LastEI) {
// Check if the user node of the TE comes after user node of EntryPtr,
// otherwise EntryPtr depends on TE.
// Gather nodes usually are not scheduled and inserted before their first
// user node. So, instead of checking dependency between the gather nodes
// themselves, we check the dependency between their user nodes.
// If one user node comes before the second one, we cannot use the second
// gather node as the source vector for the first gather node, because in
// the list of instructions it will be emitted later.
auto *EntryParent = LastEI->getParent();
auto *NodeEUI = DT->getNode(EntryParent);
if (!NodeEUI)
return false;
assert((NodeUI == NodeEUI) ==
(NodeUI->getDFSNumIn() == NodeEUI->getDFSNumIn()) &&
"Different nodes should have different DFS numbers");
// Check the order of the gather nodes users.
if (UserInst.getParent() != EntryParent &&
(DT->dominates(NodeUI, NodeEUI) || !DT->dominates(NodeEUI, NodeUI)))
return false;
if (UserInst.getParent() == EntryParent && UserInst.comesBefore(LastEI))
return false;
return true;
};
// Find all tree entries used by the gathered values. If no common entries
// found - not a shuffle.
// Here we build a set of tree nodes for each gathered value and trying to
// find the intersection between these sets. If we have at least one common
// tree node for each gathered value - we have just a permutation of the
// single vector. If we have 2 different sets, we're in situation where we
// have a permutation of 2 input vectors.
SmallVector<SmallPtrSet<const TreeEntry *, 4>> UsedTEs;
DenseMap<Value *, int> UsedValuesEntry;
for (Value *V : VL) {
if (isConstant(V))
continue;
// Build a list of tree entries where V is used.
SmallPtrSet<const TreeEntry *, 4> VToTEs;
for (const TreeEntry *TEPtr : ValueToGatherNodes.find(V)->second) {
if (TEPtr == TE)
continue;
if (!any_of(TEPtr->Scalars, [&GatheredScalars](Value *V) {
return GatheredScalars.contains(V);
}))
continue;
assert(TEPtr->UserTreeIndices.size() == 1 &&
"Expected only single user of the gather node.");
Instruction &EntryUserInst =
getLastInstructionInBundle(TEPtr->UserTreeIndices.front().UserTE);
PHINode *EntryPHI =
dyn_cast<PHINode>(TEPtr->UserTreeIndices.front().UserTE->getMainOp());
if (&UserInst == &EntryUserInst && !EntryPHI) {
// If 2 gathers are operands of the same entry, compare operands
// indices, use the earlier one as the base.
if (TE->UserTreeIndices.front().UserTE ==
TEPtr->UserTreeIndices.front().UserTE &&
TE->UserTreeIndices.front().EdgeIdx <
TEPtr->UserTreeIndices.front().EdgeIdx)
continue;
}
// Check if the user node of the TE comes after user node of EntryPtr,
// otherwise EntryPtr depends on TE.
auto *EntryI = EntryPHI
? EntryPHI
->getIncomingBlock(
TEPtr->UserTreeIndices.front().EdgeIdx)
->getTerminator()
: &EntryUserInst;
if (!CheckOrdering(EntryI) &&
(ParentBB != EntryI->getParent() ||
TE->UserTreeIndices.front().UserTE !=
TEPtr->UserTreeIndices.front().UserTE ||
TE->UserTreeIndices.front().EdgeIdx <
TEPtr->UserTreeIndices.front().EdgeIdx))
continue;
VToTEs.insert(TEPtr);
}
if (const TreeEntry *VTE = getTreeEntry(V)) {
Instruction &EntryUserInst = getLastInstructionInBundle(VTE);
if (&EntryUserInst == &UserInst || !CheckOrdering(&EntryUserInst))
continue;
VToTEs.insert(VTE);
}
if (VToTEs.empty())
continue;
if (UsedTEs.empty()) {
// The first iteration, just insert the list of nodes to vector.
UsedTEs.push_back(VToTEs);
UsedValuesEntry.try_emplace(V, 0);
} else {
// Need to check if there are any previously used tree nodes which use V.
// If there are no such nodes, consider that we have another one input
// vector.
SmallPtrSet<const TreeEntry *, 4> SavedVToTEs(VToTEs);
unsigned Idx = 0;
for (SmallPtrSet<const TreeEntry *, 4> &Set : UsedTEs) {
// Do we have a non-empty intersection of previously listed tree entries
// and tree entries using current V?
set_intersect(VToTEs, Set);
if (!VToTEs.empty()) {
// Yes, write the new subset and continue analysis for the next
// scalar.
Set.swap(VToTEs);
break;
}
VToTEs = SavedVToTEs;
++Idx;
}
// No non-empty intersection found - need to add a second set of possible
// source vectors.
if (Idx == UsedTEs.size()) {
// If the number of input vectors is greater than 2 - not a permutation,
// fallback to the regular gather.
// TODO: support multiple reshuffled nodes.
if (UsedTEs.size() == 2)
continue;
UsedTEs.push_back(SavedVToTEs);
Idx = UsedTEs.size() - 1;
}
UsedValuesEntry.try_emplace(V, Idx);
}
}
if (UsedTEs.empty())
return std::nullopt;
unsigned VF = 0;
if (UsedTEs.size() == 1) {
// Keep the order to avoid non-determinism.
SmallVector<const TreeEntry *> FirstEntries(UsedTEs.front().begin(),
UsedTEs.front().end());
sort(FirstEntries, [](const TreeEntry *TE1, const TreeEntry *TE2) {
return TE1->Idx < TE2->Idx;
});
// Try to find the perfect match in another gather node at first.
auto *It = find_if(FirstEntries, [=](const TreeEntry *EntryPtr) {
return EntryPtr->isSame(VL) || EntryPtr->isSame(TE->Scalars);
});
if (It != FirstEntries.end() && (*It)->getVectorFactor() == VL.size()) {
Entries.push_back(*It);
std::iota(Mask.begin(), Mask.end(), 0);
// Clear undef scalars.
for (int I = 0, Sz = VL.size(); I < Sz; ++I)
if (isa<PoisonValue>(VL[I]))
Mask[I] = PoisonMaskElem;
return TargetTransformInfo::SK_PermuteSingleSrc;
}
// No perfect match, just shuffle, so choose the first tree node from the
// tree.
Entries.push_back(FirstEntries.front());
} else {
// Try to find nodes with the same vector factor.
assert(UsedTEs.size() == 2 && "Expected at max 2 permuted entries.");
// Keep the order of tree nodes to avoid non-determinism.
DenseMap<int, const TreeEntry *> VFToTE;
for (const TreeEntry *TE : UsedTEs.front()) {
unsigned VF = TE->getVectorFactor();
auto It = VFToTE.find(VF);
if (It != VFToTE.end()) {
if (It->second->Idx > TE->Idx)
It->getSecond() = TE;
continue;
}
VFToTE.try_emplace(VF, TE);
}
// Same, keep the order to avoid non-determinism.
SmallVector<const TreeEntry *> SecondEntries(UsedTEs.back().begin(),
UsedTEs.back().end());
sort(SecondEntries, [](const TreeEntry *TE1, const TreeEntry *TE2) {
return TE1->Idx < TE2->Idx;
});
for (const TreeEntry *TE : SecondEntries) {
auto It = VFToTE.find(TE->getVectorFactor());
if (It != VFToTE.end()) {
VF = It->first;
Entries.push_back(It->second);
Entries.push_back(TE);
break;
}
}
// No 2 source vectors with the same vector factor - just choose 2 with max
// index.
if (Entries.empty()) {
Entries.push_back(
*std::max_element(UsedTEs.front().begin(), UsedTEs.front().end(),
[](const TreeEntry *TE1, const TreeEntry *TE2) {
return TE1->Idx < TE2->Idx;
}));
Entries.push_back(SecondEntries.front());
VF = std::max(Entries.front()->getVectorFactor(),
Entries.back()->getVectorFactor());
}
}
bool IsSplatOrUndefs = isSplat(VL) || all_of(VL, UndefValue::classof);
// Checks if the 2 PHIs are compatible in terms of high possibility to be
// vectorized.
auto AreCompatiblePHIs = [&](Value *V, Value *V1) {
auto *PHI = cast<PHINode>(V);
auto *PHI1 = cast<PHINode>(V1);
// Check that all incoming values are compatible/from same parent (if they
// are instructions).
// The incoming values are compatible if they all are constants, or
// instruction with the same/alternate opcodes from the same basic block.
for (int I = 0, E = PHI->getNumIncomingValues(); I < E; ++I) {
Value *In = PHI->getIncomingValue(I);
Value *In1 = PHI1->getIncomingValue(I);
if (isConstant(In) && isConstant(In1))
continue;
if (!getSameOpcode({In, In1}, *TLI).getOpcode())
return false;
if (cast<Instruction>(In)->getParent() !=
cast<Instruction>(In1)->getParent())
return false;
}
return true;
};
// Check if the value can be ignored during analysis for shuffled gathers.
// We suppose it is better to ignore instruction, which do not form splats,
// are not vectorized/not extractelements (these instructions will be handled
// by extractelements processing) or may form vector node in future.
auto MightBeIgnored = [=](Value *V) {
auto *I = dyn_cast<Instruction>(V);
SmallVector<Value *> IgnoredVals;
if (UserIgnoreList)
IgnoredVals.assign(UserIgnoreList->begin(), UserIgnoreList->end());
return I && !IsSplatOrUndefs && !ScalarToTreeEntry.count(I) &&
!isVectorLikeInstWithConstOps(I) &&
!areAllUsersVectorized(I, IgnoredVals) && isSimple(I);
};
// Check that the neighbor instruction may form a full vector node with the
// current instruction V. It is possible, if they have same/alternate opcode
// and same parent basic block.
auto NeighborMightBeIgnored = [&](Value *V, int Idx) {
Value *V1 = VL[Idx];
bool UsedInSameVTE = false;
auto It = UsedValuesEntry.find(V1);
if (It != UsedValuesEntry.end())
UsedInSameVTE = It->second == UsedValuesEntry.find(V)->second;
return V != V1 && MightBeIgnored(V1) && !UsedInSameVTE &&
getSameOpcode({V, V1}, *TLI).getOpcode() &&
cast<Instruction>(V)->getParent() ==
cast<Instruction>(V1)->getParent() &&
(!isa<PHINode>(V1) || AreCompatiblePHIs(V, V1));
};
// Build a shuffle mask for better cost estimation and vector emission.
SmallBitVector UsedIdxs(Entries.size());
SmallVector<std::pair<unsigned, int>> EntryLanes;
for (int I = 0, E = VL.size(); I < E; ++I) {
Value *V = VL[I];
auto It = UsedValuesEntry.find(V);
if (It == UsedValuesEntry.end())
continue;
// Do not try to shuffle scalars, if they are constants, or instructions
// that can be vectorized as a result of the following vector build
// vectorization.
if (isConstant(V) || (MightBeIgnored(V) &&
((I > 0 && NeighborMightBeIgnored(V, I - 1)) ||
(I != E - 1 && NeighborMightBeIgnored(V, I + 1)))))
continue;
unsigned Idx = It->second;
EntryLanes.emplace_back(Idx, I);
UsedIdxs.set(Idx);
}
// Iterate through all shuffled scalars and select entries, which can be used
// for final shuffle.
SmallVector<const TreeEntry *> TempEntries;
for (unsigned I = 0, Sz = Entries.size(); I < Sz; ++I) {
if (!UsedIdxs.test(I))
continue;
// Fix the entry number for the given scalar. If it is the first entry, set
// Pair.first to 0, otherwise to 1 (currently select at max 2 nodes).
// These indices are used when calculating final shuffle mask as the vector
// offset.
for (std::pair<unsigned, int> &Pair : EntryLanes)
if (Pair.first == I)
Pair.first = TempEntries.size();
TempEntries.push_back(Entries[I]);
}
Entries.swap(TempEntries);
if (EntryLanes.size() == Entries.size() && !VL.equals(TE->Scalars)) {
// We may have here 1 or 2 entries only. If the number of scalars is equal
// to the number of entries, no need to do the analysis, it is not very
// profitable. Since VL is not the same as TE->Scalars, it means we already
// have some shuffles before. Cut off not profitable case.
Entries.clear();
return std::nullopt;
}
// Build the final mask, check for the identity shuffle, if possible.
bool IsIdentity = Entries.size() == 1;
// Pair.first is the offset to the vector, while Pair.second is the index of
// scalar in the list.
for (const std::pair<unsigned, int> &Pair : EntryLanes) {
Mask[Pair.second] = Pair.first * VF +
Entries[Pair.first]->findLaneForValue(VL[Pair.second]);
IsIdentity &= Mask[Pair.second] == Pair.second;
}
switch (Entries.size()) {
case 1:
if (IsIdentity || EntryLanes.size() > 1 || VL.size() <= 2)
return TargetTransformInfo::SK_PermuteSingleSrc;
break;
case 2:
if (EntryLanes.size() > 2 || VL.size() <= 2)
return TargetTransformInfo::SK_PermuteTwoSrc;
break;
default:
break;
}
Entries.clear();
return std::nullopt;
}
InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL,
bool ForPoisonSrc) const {
// Find the type of the operands in VL.
Type *ScalarTy = VL[0]->getType();
if (StoreInst *SI = dyn_cast<StoreInst>(VL[0]))
ScalarTy = SI->getValueOperand()->getType();
auto *VecTy = FixedVectorType::get(ScalarTy, VL.size());
bool DuplicateNonConst = false;
// Find the cost of inserting/extracting values from the vector.
// Check if the same elements are inserted several times and count them as
// shuffle candidates.
APInt ShuffledElements = APInt::getZero(VL.size());
DenseSet<Value *> UniqueElements;
constexpr TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
InstructionCost Cost;
auto EstimateInsertCost = [&](unsigned I, Value *V) {
if (!ForPoisonSrc)
Cost +=
TTI->getVectorInstrCost(Instruction::InsertElement, VecTy, CostKind,
I, Constant::getNullValue(VecTy), V);
};
for (unsigned I = 0, E = VL.size(); I < E; ++I) {
Value *V = VL[I];
// No need to shuffle duplicates for constants.
if ((ForPoisonSrc && isConstant(V)) || isa<UndefValue>(V)) {
ShuffledElements.setBit(I);
continue;
}
if (!UniqueElements.insert(V).second) {
DuplicateNonConst = true;
ShuffledElements.setBit(I);
continue;
}
EstimateInsertCost(I, V);
}
if (ForPoisonSrc)
Cost =
TTI->getScalarizationOverhead(VecTy, ~ShuffledElements, /*Insert*/ true,
/*Extract*/ false, CostKind);
if (DuplicateNonConst)
Cost +=
TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy);
return Cost;
}
// Perform operand reordering on the instructions in VL and return the reordered
// operands in Left and Right.
void BoUpSLP::reorderInputsAccordingToOpcode(
ArrayRef<Value *> VL, SmallVectorImpl<Value *> &Left,
SmallVectorImpl<Value *> &Right, const TargetLibraryInfo &TLI,
const DataLayout &DL, ScalarEvolution &SE, const BoUpSLP &R) {
if (VL.empty())
return;
VLOperands Ops(VL, TLI, DL, SE, R);
// Reorder the operands in place.
Ops.reorder();
Left = Ops.getVL(0);
Right = Ops.getVL(1);
}
Instruction &BoUpSLP::getLastInstructionInBundle(const TreeEntry *E) {
// Get the basic block this bundle is in. All instructions in the bundle
// should be in this block (except for extractelement-like instructions with
// constant indeces).
auto *Front = E->getMainOp();
auto *BB = Front->getParent();
assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool {
if (E->getOpcode() == Instruction::GetElementPtr &&
!isa<GetElementPtrInst>(V))
return true;
auto *I = cast<Instruction>(V);
return !E->isOpcodeOrAlt(I) || I->getParent() == BB ||
isVectorLikeInstWithConstOps(I);
}));
auto &&FindLastInst = [E, Front, this, &BB]() {
Instruction *LastInst = Front;
for (Value *V : E->Scalars) {
auto *I = dyn_cast<Instruction>(V);
if (!I)
continue;
if (LastInst->getParent() == I->getParent()) {
if (LastInst->comesBefore(I))
LastInst = I;
continue;
}
assert(((E->getOpcode() == Instruction::GetElementPtr &&
!isa<GetElementPtrInst>(I)) ||
(isVectorLikeInstWithConstOps(LastInst) &&
isVectorLikeInstWithConstOps(I))) &&
"Expected vector-like or non-GEP in GEP node insts only.");
if (!DT->isReachableFromEntry(LastInst->getParent())) {
LastInst = I;
continue;
}
if (!DT->isReachableFromEntry(I->getParent()))
continue;
auto *NodeA = DT->getNode(LastInst->getParent());
auto *NodeB = DT->getNode(I->getParent());
assert(NodeA && "Should only process reachable instructions");
assert(NodeB && "Should only process reachable instructions");
assert((NodeA == NodeB) ==
(NodeA->getDFSNumIn() == NodeB->getDFSNumIn()) &&
"Different nodes should have different DFS numbers");
if (NodeA->getDFSNumIn() < NodeB->getDFSNumIn())
LastInst = I;
}
BB = LastInst->getParent();
return LastInst;
};
auto &&FindFirstInst = [E, Front, this]() {
Instruction *FirstInst = Front;
for (Value *V : E->Scalars) {
auto *I = dyn_cast<Instruction>(V);
if (!I)
continue;
if (FirstInst->getParent() == I->getParent()) {
if (I->comesBefore(FirstInst))
FirstInst = I;
continue;
}
assert(((E->getOpcode() == Instruction::GetElementPtr &&
!isa<GetElementPtrInst>(I)) ||
(isVectorLikeInstWithConstOps(FirstInst) &&
isVectorLikeInstWithConstOps(I))) &&
"Expected vector-like or non-GEP in GEP node insts only.");
if (!DT->isReachableFromEntry(FirstInst->getParent())) {
FirstInst = I;
continue;
}
if (!DT->isReachableFromEntry(I->getParent()))
continue;
auto *NodeA = DT->getNode(FirstInst->getParent());
auto *NodeB = DT->getNode(I->getParent());
assert(NodeA && "Should only process reachable instructions");
assert(NodeB && "Should only process reachable instructions");
assert((NodeA == NodeB) ==
(NodeA->getDFSNumIn() == NodeB->getDFSNumIn()) &&
"Different nodes should have different DFS numbers");
if (NodeA->getDFSNumIn() > NodeB->getDFSNumIn())
FirstInst = I;
}
return FirstInst;
};
// Set the insert point to the beginning of the basic block if the entry
// should not be scheduled.
if (E->State != TreeEntry::NeedToGather &&
(doesNotNeedToSchedule(E->Scalars) ||
all_of(E->Scalars, isVectorLikeInstWithConstOps))) {
Instruction *InsertInst;
if ((E->getOpcode() == Instruction::GetElementPtr &&
any_of(E->Scalars,
[](Value *V) {
return !isa<GetElementPtrInst>(V) && isa<Instruction>(V);
})) ||
all_of(E->Scalars, [](Value *V) {
return !isVectorLikeInstWithConstOps(V) && isUsedOutsideBlock(V);
}))
InsertInst = FindLastInst();
else
InsertInst = FindFirstInst();
return *InsertInst;
}
// The last instruction in the bundle in program order.
Instruction *LastInst = nullptr;
// Find the last instruction. The common case should be that BB has been
// scheduled, and the last instruction is VL.back(). So we start with
// VL.back() and iterate over schedule data until we reach the end of the
// bundle. The end of the bundle is marked by null ScheduleData.
if (BlocksSchedules.count(BB)) {
Value *V = E->isOneOf(E->Scalars.back());
if (doesNotNeedToBeScheduled(V))
V = *find_if_not(E->Scalars, doesNotNeedToBeScheduled);
auto *Bundle = BlocksSchedules[BB]->getScheduleData(V);
if (Bundle && Bundle->isPartOfBundle())
for (; Bundle; Bundle = Bundle->NextInBundle)
if (Bundle->OpValue == Bundle->Inst)
LastInst = Bundle->Inst;
}
// LastInst can still be null at this point if there's either not an entry
// for BB in BlocksSchedules or there's no ScheduleData available for
// VL.back(). This can be the case if buildTree_rec aborts for various
// reasons (e.g., the maximum recursion depth is reached, the maximum region
// size is reached, etc.). ScheduleData is initialized in the scheduling
// "dry-run".
//
// If this happens, we can still find the last instruction by brute force. We
// iterate forwards from Front (inclusive) until we either see all
// instructions in the bundle or reach the end of the block. If Front is the
// last instruction in program order, LastInst will be set to Front, and we
// will visit all the remaining instructions in the block.
//
// One of the reasons we exit early from buildTree_rec is to place an upper
// bound on compile-time. Thus, taking an additional compile-time hit here is
// not ideal. However, this should be exceedingly rare since it requires that
// we both exit early from buildTree_rec and that the bundle be out-of-order
// (causing us to iterate all the way to the end of the block).
if (!LastInst)
LastInst = FindLastInst();
assert(LastInst && "Failed to find last instruction in bundle");
return *LastInst;
}
void BoUpSLP::setInsertPointAfterBundle(const TreeEntry *E) {
auto *Front = E->getMainOp();
Instruction *LastInst = EntryToLastInstruction.lookup(E);
assert(LastInst && "Failed to find last instruction in bundle");
// If the instruction is PHI, set the insert point after all the PHIs.
bool IsPHI = isa<PHINode>(LastInst);
if (IsPHI)
LastInst = LastInst->getParent()->getFirstNonPHI();
if (IsPHI || (E->State != TreeEntry::NeedToGather &&
doesNotNeedToSchedule(E->Scalars))) {
Builder.SetInsertPoint(LastInst);
} else {
// Set the insertion point after the last instruction in the bundle. Set the
// debug location to Front.
Builder.SetInsertPoint(LastInst->getParent(),
std::next(LastInst->getIterator()));
}
Builder.SetCurrentDebugLocation(Front->getDebugLoc());
}
Value *BoUpSLP::gather(ArrayRef<Value *> VL, Value *Root) {
// List of instructions/lanes from current block and/or the blocks which are
// part of the current loop. These instructions will be inserted at the end to
// make it possible to optimize loops and hoist invariant instructions out of
// the loops body with better chances for success.
SmallVector<std::pair<Value *, unsigned>, 4> PostponedInsts;
SmallSet<int, 4> PostponedIndices;
Loop *L = LI->getLoopFor(Builder.GetInsertBlock());
auto &&CheckPredecessor = [](BasicBlock *InstBB, BasicBlock *InsertBB) {
SmallPtrSet<BasicBlock *, 4> Visited;
while (InsertBB && InsertBB != InstBB && Visited.insert(InsertBB).second)
InsertBB = InsertBB->getSinglePredecessor();
return InsertBB && InsertBB == InstBB;
};
for (int I = 0, E = VL.size(); I < E; ++I) {
if (auto *Inst = dyn_cast<Instruction>(VL[I]))
if ((CheckPredecessor(Inst->getParent(), Builder.GetInsertBlock()) ||
getTreeEntry(Inst) ||
(L && (!Root || L->isLoopInvariant(Root)) && L->contains(Inst))) &&
PostponedIndices.insert(I).second)
PostponedInsts.emplace_back(Inst, I);
}
auto &&CreateInsertElement = [this](Value *Vec, Value *V, unsigned Pos) {
Vec = Builder.CreateInsertElement(Vec, V, Builder.getInt32(Pos));
auto *InsElt = dyn_cast<InsertElementInst>(Vec);
if (!InsElt)
return Vec;
GatherShuffleExtractSeq.insert(InsElt);
CSEBlocks.insert(InsElt->getParent());
// Add to our 'need-to-extract' list.
if (TreeEntry *Entry = getTreeEntry(V)) {
// Find which lane we need to extract.
unsigned FoundLane = Entry->findLaneForValue(V);
ExternalUses.emplace_back(V, InsElt, FoundLane);
}
return Vec;
};
Value *Val0 =
isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0];
FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size());
Value *Vec = Root ? Root : PoisonValue::get(VecTy);
SmallVector<int> NonConsts;
// Insert constant values at first.
for (int I = 0, E = VL.size(); I < E; ++I) {
if (PostponedIndices.contains(I))
continue;
if (!isConstant(VL[I])) {
NonConsts.push_back(I);
continue;
}
if (Root) {
if (!isa<UndefValue>(VL[I])) {
NonConsts.push_back(I);
continue;
}
if (isa<PoisonValue>(VL[I]))
continue;
if (auto *SV = dyn_cast<ShuffleVectorInst>(Root)) {
if (SV->getMaskValue(I) == PoisonMaskElem)
continue;
}
}
Vec = CreateInsertElement(Vec, VL[I], I);
}
// Insert non-constant values.
for (int I : NonConsts)
Vec = CreateInsertElement(Vec, VL[I], I);
// Append instructions, which are/may be part of the loop, in the end to make
// it possible to hoist non-loop-based instructions.
for (const std::pair<Value *, unsigned> &Pair : PostponedInsts)
Vec = CreateInsertElement(Vec, Pair.first, Pair.second);
return Vec;
}
/// Merges shuffle masks and emits final shuffle instruction, if required. It
/// supports shuffling of 2 input vectors. It implements lazy shuffles emission,
/// when the actual shuffle instruction is generated only if this is actually
/// required. Otherwise, the shuffle instruction emission is delayed till the
/// end of the process, to reduce the number of emitted instructions and further
/// analysis/transformations.
/// The class also will look through the previously emitted shuffle instructions
/// and properly mark indices in mask as undef.
/// For example, given the code
/// \code
/// %s1 = shufflevector <2 x ty> %0, poison, <1, 0>
/// %s2 = shufflevector <2 x ty> %1, poison, <1, 0>
/// \endcode
/// and if need to emit shuffle of %s1 and %s2 with mask <1, 0, 3, 2>, it will
/// look through %s1 and %s2 and emit
/// \code
/// %res = shufflevector <2 x ty> %0, %1, <0, 1, 2, 3>
/// \endcode
/// instead.
/// If 2 operands are of different size, the smallest one will be resized and
/// the mask recalculated properly.
/// For example, given the code
/// \code
/// %s1 = shufflevector <2 x ty> %0, poison, <1, 0, 1, 0>
/// %s2 = shufflevector <2 x ty> %1, poison, <1, 0, 1, 0>
/// \endcode
/// and if need to emit shuffle of %s1 and %s2 with mask <1, 0, 5, 4>, it will
/// look through %s1 and %s2 and emit
/// \code
/// %res = shufflevector <2 x ty> %0, %1, <0, 1, 2, 3>
/// \endcode
/// instead.
class BoUpSLP::ShuffleInstructionBuilder final : public BaseShuffleAnalysis {
bool IsFinalized = false;
/// Combined mask for all applied operands and masks. It is built during
/// analysis and actual emission of shuffle vector instructions.
SmallVector<int> CommonMask;
/// List of operands for the shuffle vector instruction. It hold at max 2
/// operands, if the 3rd is going to be added, the first 2 are combined into
/// shuffle with \p CommonMask mask, the first operand sets to be the
/// resulting shuffle and the second operand sets to be the newly added
/// operand. The \p CommonMask is transformed in the proper way after that.
SmallVector<Value *, 2> InVectors;
IRBuilderBase &Builder;
BoUpSLP &R;
class ShuffleIRBuilder {
IRBuilderBase &Builder;
/// Holds all of the instructions that we gathered.
SetVector<Instruction *> &GatherShuffleExtractSeq;
/// A list of blocks that we are going to CSE.
SetVector<BasicBlock *> &CSEBlocks;
public:
ShuffleIRBuilder(IRBuilderBase &Builder,
SetVector<Instruction *> &GatherShuffleExtractSeq,
SetVector<BasicBlock *> &CSEBlocks)
: Builder(Builder), GatherShuffleExtractSeq(GatherShuffleExtractSeq),
CSEBlocks(CSEBlocks) {}
~ShuffleIRBuilder() = default;
/// Creates shufflevector for the 2 operands with the given mask.
Value *createShuffleVector(Value *V1, Value *V2, ArrayRef<int> Mask) {
Value *Vec = Builder.CreateShuffleVector(V1, V2, Mask);
if (auto *I = dyn_cast<Instruction>(Vec)) {
GatherShuffleExtractSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
return Vec;
}
/// Creates permutation of the single vector operand with the given mask, if
/// it is not identity mask.
Value *createShuffleVector(Value *V1, ArrayRef<int> Mask) {
if (Mask.empty())
return V1;
unsigned VF = Mask.size();
unsigned LocalVF = cast<FixedVectorType>(V1->getType())->getNumElements();
if (VF == LocalVF && ShuffleVectorInst::isIdentityMask(Mask))
return V1;
Value *Vec = Builder.CreateShuffleVector(V1, Mask);
if (auto *I = dyn_cast<Instruction>(Vec)) {
GatherShuffleExtractSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
return Vec;
}
Value *createIdentity(Value *V) { return V; }
Value *createPoison(Type *Ty, unsigned VF) {
return PoisonValue::get(FixedVectorType::get(Ty, VF));
}
/// Resizes 2 input vector to match the sizes, if the they are not equal
/// yet. The smallest vector is resized to the size of the larger vector.
void resizeToMatch(Value *&V1, Value *&V2) {
if (V1->getType() == V2->getType())
return;
int V1VF = cast<FixedVectorType>(V1->getType())->getNumElements();
int V2VF = cast<FixedVectorType>(V2->getType())->getNumElements();
int VF = std::max(V1VF, V2VF);
int MinVF = std::min(V1VF, V2VF);
SmallVector<int> IdentityMask(VF, PoisonMaskElem);
std::iota(IdentityMask.begin(), std::next(IdentityMask.begin(), MinVF),
0);
Value *&Op = MinVF == V1VF ? V1 : V2;
Op = Builder.CreateShuffleVector(Op, IdentityMask);
if (auto *I = dyn_cast<Instruction>(Op)) {
GatherShuffleExtractSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
if (MinVF == V1VF)
V1 = Op;
else
V2 = Op;
}
};
/// Smart shuffle instruction emission, walks through shuffles trees and
/// tries to find the best matching vector for the actual shuffle
/// instruction.
Value *createShuffle(Value *V1, Value *V2, ArrayRef<int> Mask) {
assert(V1 && "Expected at least one vector value.");
ShuffleIRBuilder ShuffleBuilder(Builder, R.GatherShuffleExtractSeq,
R.CSEBlocks);
return BaseShuffleAnalysis::createShuffle<Value *>(V1, V2, Mask,
ShuffleBuilder);
}
/// Transforms mask \p CommonMask per given \p Mask to make proper set after
/// shuffle emission.
static void transformMaskAfterShuffle(MutableArrayRef<int> CommonMask,
ArrayRef<int> Mask) {
for (unsigned Idx = 0, Sz = CommonMask.size(); Idx < Sz; ++Idx)
if (Mask[Idx] != PoisonMaskElem)
CommonMask[Idx] = Idx;
}
public:
ShuffleInstructionBuilder(IRBuilderBase &Builder, BoUpSLP &R)
: Builder(Builder), R(R) {}
/// Adjusts extractelements after reusing them.
Value *adjustExtracts(const TreeEntry *E, ArrayRef<int> Mask) {
Value *VecBase = nullptr;
for (int I = 0, Sz = Mask.size(); I < Sz; ++I) {
int Idx = Mask[I];
if (Idx == PoisonMaskElem)
continue;
auto *EI = cast<ExtractElementInst>(E->Scalars[I]);
VecBase = EI->getVectorOperand();
// If the only one use is vectorized - can delete the extractelement
// itself.
if (!EI->hasOneUse() || any_of(EI->users(), [&](User *U) {
return !R.ScalarToTreeEntry.count(U);
}))
continue;
R.eraseInstruction(EI);
}
return VecBase;
}
/// Checks if the specified entry \p E needs to be delayed because of its
/// dependency nodes.
Value *needToDelay(const TreeEntry *E, ArrayRef<const TreeEntry *> Deps) {
// No need to delay emission if all deps are ready.
if (all_of(Deps, [](const TreeEntry *TE) { return TE->VectorizedValue; }))
return nullptr;
// Postpone gather emission, will be emitted after the end of the
// process to keep correct order.
auto *VecTy = FixedVectorType::get(E->Scalars.front()->getType(),
E->getVectorFactor());
Value *Vec = Builder.CreateAlignedLoad(
VecTy, PoisonValue::get(VecTy->getPointerTo()), MaybeAlign());
return Vec;
}
/// Adds 2 input vectors and the mask for their shuffling.
void add(Value *V1, Value *V2, ArrayRef<int> Mask) {
assert(V1 && V2 && !Mask.empty() && "Expected non-empty input vectors.");
if (InVectors.empty()) {
InVectors.push_back(V1);
InVectors.push_back(V2);
CommonMask.assign(Mask.begin(), Mask.end());
return;
}
Value *Vec = InVectors.front();
if (InVectors.size() == 2) {
Vec = createShuffle(Vec, InVectors.back(), CommonMask);
transformMaskAfterShuffle(CommonMask, CommonMask);
} else if (cast<FixedVectorType>(Vec->getType())->getNumElements() !=
Mask.size()) {
Vec = createShuffle(Vec, nullptr, CommonMask);
transformMaskAfterShuffle(CommonMask, CommonMask);
}
V1 = createShuffle(V1, V2, Mask);
for (unsigned Idx = 0, Sz = CommonMask.size(); Idx < Sz; ++Idx)
if (Mask[Idx] != PoisonMaskElem)
CommonMask[Idx] = Idx + Sz;
InVectors.front() = Vec;
if (InVectors.size() == 2)
InVectors.back() = V1;
else
InVectors.push_back(V1);
}
/// Adds another one input vector and the mask for the shuffling.
void add(Value *V1, ArrayRef<int> Mask) {
if (InVectors.empty()) {
if (!isa<FixedVectorType>(V1->getType())) {
V1 = createShuffle(V1, nullptr, CommonMask);
CommonMask.assign(Mask.size(), PoisonMaskElem);
transformMaskAfterShuffle(CommonMask, Mask);
}
InVectors.push_back(V1);
CommonMask.assign(Mask.begin(), Mask.end());
return;
}
const auto *It = find(InVectors, V1);
if (It == InVectors.end()) {
if (InVectors.size() == 2 ||
InVectors.front()->getType() != V1->getType() ||
!isa<FixedVectorType>(V1->getType())) {
Value *V = InVectors.front();
if (InVectors.size() == 2) {
V = createShuffle(InVectors.front(), InVectors.back(), CommonMask);
transformMaskAfterShuffle(CommonMask, CommonMask);
} else if (cast<FixedVectorType>(V->getType())->getNumElements() !=
CommonMask.size()) {
V = createShuffle(InVectors.front(), nullptr, CommonMask);
transformMaskAfterShuffle(CommonMask, CommonMask);
}
for (unsigned Idx = 0, Sz = CommonMask.size(); Idx < Sz; ++Idx)
if (CommonMask[Idx] == PoisonMaskElem && Mask[Idx] != PoisonMaskElem)
CommonMask[Idx] =
V->getType() != V1->getType()
? Idx + Sz
: Mask[Idx] + cast<FixedVectorType>(V1->getType())
->getNumElements();
if (V->getType() != V1->getType())
V1 = createShuffle(V1, nullptr, Mask);
InVectors.front() = V;
if (InVectors.size() == 2)
InVectors.back() = V1;
else
InVectors.push_back(V1);
return;
}
// Check if second vector is required if the used elements are already
// used from the first one.
for (unsigned Idx = 0, Sz = CommonMask.size(); Idx < Sz; ++Idx)
if (Mask[Idx] != PoisonMaskElem && CommonMask[Idx] == PoisonMaskElem) {
InVectors.push_back(V1);
break;
}
}
int VF = CommonMask.size();
if (auto *FTy = dyn_cast<FixedVectorType>(V1->getType()))
VF = FTy->getNumElements();
for (unsigned Idx = 0, Sz = CommonMask.size(); Idx < Sz; ++Idx)
if (Mask[Idx] != PoisonMaskElem && CommonMask[Idx] == PoisonMaskElem)
CommonMask[Idx] = Mask[Idx] + (It == InVectors.begin() ? 0 : VF);
}
/// Adds another one input vector and the mask for the shuffling.
void addOrdered(Value *V1, ArrayRef<unsigned> Order) {
SmallVector<int> NewMask;
inversePermutation(Order, NewMask);
add(V1, NewMask);
}
Value *gather(ArrayRef<Value *> VL, Value *Root = nullptr) {
return R.gather(VL, Root);
}
Value *createFreeze(Value *V) { return Builder.CreateFreeze(V); }
/// Finalize emission of the shuffles.
/// \param Action the action (if any) to be performed before final applying of
/// the \p ExtMask mask.
Value *
finalize(ArrayRef<int> ExtMask, unsigned VF = 0,
function_ref<void(Value *&, SmallVectorImpl<int> &)> Action = {}) {
IsFinalized = true;
if (Action) {
Value *Vec = InVectors.front();
if (InVectors.size() == 2) {
Vec = createShuffle(Vec, InVectors.back(), CommonMask);
InVectors.pop_back();
} else {
Vec = createShuffle(Vec, nullptr, CommonMask);
}
for (unsigned Idx = 0, Sz = CommonMask.size(); Idx < Sz; ++Idx)
if (CommonMask[Idx] != PoisonMaskElem)
CommonMask[Idx] = Idx;
assert(VF > 0 &&
"Expected vector length for the final value before action.");
unsigned VecVF = cast<FixedVectorType>(Vec->getType())->getNumElements();
if (VecVF < VF) {
SmallVector<int> ResizeMask(VF, PoisonMaskElem);
std::iota(ResizeMask.begin(), std::next(ResizeMask.begin(), VecVF), 0);
Vec = createShuffle(Vec, nullptr, ResizeMask);
}
Action(Vec, CommonMask);
InVectors.front() = Vec;
}
if (!ExtMask.empty()) {
if (CommonMask.empty()) {
CommonMask.assign(ExtMask.begin(), ExtMask.end());
} else {
SmallVector<int> NewMask(ExtMask.size(), PoisonMaskElem);
for (int I = 0, Sz = ExtMask.size(); I < Sz; ++I) {
if (ExtMask[I] == PoisonMaskElem)
continue;
NewMask[I] = CommonMask[ExtMask[I]];
}
CommonMask.swap(NewMask);
}
}
if (CommonMask.empty()) {
assert(InVectors.size() == 1 && "Expected only one vector with no mask");
return InVectors.front();
}
if (InVectors.size() == 2)
return createShuffle(InVectors.front(), InVectors.back(), CommonMask);
return createShuffle(InVectors.front(), nullptr, CommonMask);
}
~ShuffleInstructionBuilder() {
assert((IsFinalized || CommonMask.empty()) &&
"Shuffle construction must be finalized.");
}
};
Value *BoUpSLP::vectorizeOperand(TreeEntry *E, unsigned NodeIdx) {
ArrayRef<Value *> VL = E->getOperand(NodeIdx);
const unsigned VF = VL.size();
InstructionsState S = getSameOpcode(VL, *TLI);
// Special processing for GEPs bundle, which may include non-gep values.
if (!S.getOpcode() && VL.front()->getType()->isPointerTy()) {
const auto *It =
find_if(VL, [](Value *V) { return isa<GetElementPtrInst>(V); });
if (It != VL.end())
S = getSameOpcode(*It, *TLI);
}
if (S.getOpcode()) {
if (TreeEntry *VE = getTreeEntry(S.OpValue);
VE && VE->isSame(VL) &&
(any_of(VE->UserTreeIndices,
[E, NodeIdx](const EdgeInfo &EI) {
return EI.UserTE == E && EI.EdgeIdx == NodeIdx;
}) ||
any_of(VectorizableTree,
[E, NodeIdx, VE](const std::unique_ptr<TreeEntry> &TE) {
return TE->isOperandGatherNode({E, NodeIdx}) &&
VE->isSame(TE->Scalars);
}))) {
auto FinalShuffle = [&](Value *V, ArrayRef<int> Mask) {
ShuffleInstructionBuilder ShuffleBuilder(Builder, *this);
ShuffleBuilder.add(V, Mask);
return ShuffleBuilder.finalize(std::nullopt);
};
Value *V = vectorizeTree(VE);
if (VF != cast<FixedVectorType>(V->getType())->getNumElements()) {
if (!VE->ReuseShuffleIndices.empty()) {
// Reshuffle to get only unique values.
// If some of the scalars are duplicated in the vectorization
// tree entry, we do not vectorize them but instead generate a
// mask for the reuses. But if there are several users of the
// same entry, they may have different vectorization factors.
// This is especially important for PHI nodes. In this case, we
// need to adapt the resulting instruction for the user
// vectorization factor and have to reshuffle it again to take
// only unique elements of the vector. Without this code the
// function incorrectly returns reduced vector instruction with
// the same elements, not with the unique ones.
// block:
// %phi = phi <2 x > { .., %entry} {%shuffle, %block}
// %2 = shuffle <2 x > %phi, poison, <4 x > <1, 1, 0, 0>
// ... (use %2)
// %shuffle = shuffle <2 x> %2, poison, <2 x> {2, 0}
// br %block
SmallVector<int> UniqueIdxs(VF, PoisonMaskElem);
SmallSet<int, 4> UsedIdxs;
int Pos = 0;
for (int Idx : VE->ReuseShuffleIndices) {
if (Idx != static_cast<int>(VF) && Idx != PoisonMaskElem &&
UsedIdxs.insert(Idx).second)
UniqueIdxs[Idx] = Pos;
++Pos;
}
assert(VF >= UsedIdxs.size() && "Expected vectorization factor "
"less than original vector size.");
UniqueIdxs.append(VF - UsedIdxs.size(), PoisonMaskElem);
V = FinalShuffle(V, UniqueIdxs);
} else {
assert(VF < cast<FixedVectorType>(V->getType())->getNumElements() &&
"Expected vectorization factor less "
"than original vector size.");
SmallVector<int> UniformMask(VF, 0);
std::iota(UniformMask.begin(), UniformMask.end(), 0);
V = FinalShuffle(V, UniformMask);
}
}
// Need to update the operand gather node, if actually the operand is not a
// vectorized node, but the buildvector/gather node, which matches one of
// the vectorized nodes.
if (find_if(VE->UserTreeIndices, [&](const EdgeInfo &EI) {
return EI.UserTE == E && EI.EdgeIdx == NodeIdx;
}) == VE->UserTreeIndices.end()) {
auto *It = find_if(
VectorizableTree, [&](const std::unique_ptr<TreeEntry> &TE) {
return TE->State == TreeEntry::NeedToGather &&
TE->UserTreeIndices.front().UserTE == E &&
TE->UserTreeIndices.front().EdgeIdx == NodeIdx;
});
assert(It != VectorizableTree.end() && "Expected gather node operand.");
(*It)->VectorizedValue = V;
}
return V;
}
}
// Find the corresponding gather entry and vectorize it.
// Allows to be more accurate with tree/graph transformations, checks for the
// correctness of the transformations in many cases.
auto *I = find_if(VectorizableTree,
[E, NodeIdx](const std::unique_ptr<TreeEntry> &TE) {
return TE->isOperandGatherNode({E, NodeIdx});
});
assert(I != VectorizableTree.end() && "Gather node is not in the graph.");
assert(I->get()->UserTreeIndices.size() == 1 &&
"Expected only single user for the gather node.");
assert(I->get()->isSame(VL) && "Expected same list of scalars.");
IRBuilder<>::InsertPointGuard Guard(Builder);
if (E->getOpcode() != Instruction::InsertElement &&
E->getOpcode() != Instruction::PHI) {
Instruction *LastInst = EntryToLastInstruction.lookup(E);
assert(LastInst && "Failed to find last instruction in bundle");
Builder.SetInsertPoint(LastInst);
}
return vectorizeTree(I->get());
}
template <typename BVTy, typename ResTy, typename... Args>
ResTy BoUpSLP::processBuildVector(const TreeEntry *E, Args &...Params) {
assert(E->State == TreeEntry::NeedToGather && "Expected gather node.");
unsigned VF = E->getVectorFactor();
bool NeedFreeze = false;
SmallVector<int> ReuseShuffleIndicies(E->ReuseShuffleIndices.begin(),
E->ReuseShuffleIndices.end());
SmallVector<Value *> GatheredScalars(E->Scalars.begin(), E->Scalars.end());
// Build a mask out of the reorder indices and reorder scalars per this
// mask.
SmallVector<int> ReorderMask;
inversePermutation(E->ReorderIndices, ReorderMask);
if (!ReorderMask.empty())
reorderScalars(GatheredScalars, ReorderMask);
auto FindReusedSplat = [&](SmallVectorImpl<int> &Mask) {
if (!isSplat(E->Scalars) || none_of(E->Scalars, [](Value *V) {
return isa<UndefValue>(V) && !isa<PoisonValue>(V);
}))
return false;
TreeEntry *UserTE = E->UserTreeIndices.back().UserTE;
unsigned EdgeIdx = E->UserTreeIndices.back().EdgeIdx;
if (UserTE->getNumOperands() != 2)
return false;
auto *It =
find_if(VectorizableTree, [=](const std::unique_ptr<TreeEntry> &TE) {
return find_if(TE->UserTreeIndices, [=](const EdgeInfo &EI) {
return EI.UserTE == UserTE && EI.EdgeIdx != EdgeIdx;
}) != TE->UserTreeIndices.end();
});
if (It == VectorizableTree.end())
return false;
unsigned I =
*find_if_not(Mask, [](int Idx) { return Idx == PoisonMaskElem; });
int Sz = Mask.size();
if (all_of(Mask, [Sz](int Idx) { return Idx < 2 * Sz; }) &&
ShuffleVectorInst::isIdentityMask(Mask))
std::iota(Mask.begin(), Mask.end(), 0);
else
std::fill(Mask.begin(), Mask.end(), I);
return true;
};
BVTy ShuffleBuilder(Params...);
ResTy Res = ResTy();
SmallVector<int> Mask;
SmallVector<int> ExtractMask;
std::optional<TargetTransformInfo::ShuffleKind> ExtractShuffle;
std::optional<TargetTransformInfo::ShuffleKind> GatherShuffle;
SmallVector<const TreeEntry *> Entries;
Type *ScalarTy = GatheredScalars.front()->getType();
if (!all_of(GatheredScalars, UndefValue::classof)) {
// Check for gathered extracts.
ExtractShuffle = tryToGatherExtractElements(GatheredScalars, ExtractMask);
SmallVector<Value *> IgnoredVals;
if (UserIgnoreList)
IgnoredVals.assign(UserIgnoreList->begin(), UserIgnoreList->end());
bool Resized = false;
if (Value *VecBase = ShuffleBuilder.adjustExtracts(E, ExtractMask))
if (auto *VecBaseTy = dyn_cast<FixedVectorType>(VecBase->getType()))
if (VF == VecBaseTy->getNumElements() && GatheredScalars.size() != VF) {
Resized = true;
GatheredScalars.append(VF - GatheredScalars.size(),
PoisonValue::get(ScalarTy));
}
// Gather extracts after we check for full matched gathers only.
if (ExtractShuffle || E->getOpcode() != Instruction::Load ||
E->isAltShuffle() ||
all_of(E->Scalars, [this](Value *V) { return getTreeEntry(V); }) ||
isSplat(E->Scalars) ||
(E->Scalars != GatheredScalars && GatheredScalars.size() <= 2)) {
GatherShuffle = isGatherShuffledEntry(E, GatheredScalars, Mask, Entries);
}
if (GatherShuffle) {
if (Value *Delayed = ShuffleBuilder.needToDelay(E, Entries)) {
// Delay emission of gathers which are not ready yet.
PostponedGathers.insert(E);
// Postpone gather emission, will be emitted after the end of the
// process to keep correct order.
return Delayed;
}
assert((Entries.size() == 1 || Entries.size() == 2) &&
"Expected shuffle of 1 or 2 entries.");
if (*GatherShuffle == TTI::SK_PermuteSingleSrc &&
Entries.front()->isSame(E->Scalars)) {
// Perfect match in the graph, will reuse the previously vectorized
// node. Cost is 0.
LLVM_DEBUG(
dbgs()
<< "SLP: perfect diamond match for gather bundle that starts with "
<< *E->Scalars.front() << ".\n");
// Restore the mask for previous partially matched values.
for (auto [I, V] : enumerate(E->Scalars)) {
if (isa<PoisonValue>(V)) {
Mask[I] = PoisonMaskElem;
continue;
}
if (Mask[I] == PoisonMaskElem)
Mask[I] = Entries.front()->findLaneForValue(V);
}
ShuffleBuilder.add(Entries.front()->VectorizedValue, Mask);
Res = ShuffleBuilder.finalize(E->ReuseShuffleIndices);
return Res;
}
if (!Resized) {
unsigned VF1 = Entries.front()->getVectorFactor();
unsigned VF2 = Entries.back()->getVectorFactor();
if ((VF == VF1 || VF == VF2) && GatheredScalars.size() != VF)
GatheredScalars.append(VF - GatheredScalars.size(),
PoisonValue::get(ScalarTy));
}
// Remove shuffled elements from list of gathers.
for (int I = 0, Sz = Mask.size(); I < Sz; ++I) {
if (Mask[I] != PoisonMaskElem)
GatheredScalars[I] = PoisonValue::get(ScalarTy);
}
}
}
auto TryPackScalars = [&](SmallVectorImpl<Value *> &Scalars,
SmallVectorImpl<int> &ReuseMask,
bool IsRootPoison) {
// For splats with can emit broadcasts instead of gathers, so try to find
// such sequences.
bool IsSplat = IsRootPoison && isSplat(Scalars) &&
(Scalars.size() > 2 || Scalars.front() == Scalars.back());
Scalars.append(VF - Scalars.size(), PoisonValue::get(ScalarTy));
SmallVector<int> UndefPos;
DenseMap<Value *, unsigned> UniquePositions;
// Gather unique non-const values and all constant values.
// For repeated values, just shuffle them.
int NumNonConsts = 0;
int SinglePos = 0;
for (auto [I, V] : enumerate(Scalars)) {
if (isa<UndefValue>(V)) {
if (!isa<PoisonValue>(V)) {
ReuseMask[I] = I;
UndefPos.push_back(I);
}
continue;
}
if (isConstant(V)) {
ReuseMask[I] = I;
continue;
}
++NumNonConsts;
SinglePos = I;
Value *OrigV = V;
Scalars[I] = PoisonValue::get(ScalarTy);
if (IsSplat) {
Scalars.front() = OrigV;
ReuseMask[I] = 0;
} else {
const auto Res = UniquePositions.try_emplace(OrigV, I);
Scalars[Res.first->second] = OrigV;
ReuseMask[I] = Res.first->second;
}
}
if (NumNonConsts == 1) {
// Restore single insert element.
if (IsSplat) {
ReuseMask.assign(VF, PoisonMaskElem);
std::swap(Scalars.front(), Scalars[SinglePos]);
if (!UndefPos.empty() && UndefPos.front() == 0)
Scalars.front() = UndefValue::get(ScalarTy);
}
ReuseMask[SinglePos] = SinglePos;
} else if (!UndefPos.empty() && IsSplat) {
// For undef values, try to replace them with the simple broadcast.
// We can do it if the broadcasted value is guaranteed to be
// non-poisonous, or by freezing the incoming scalar value first.
auto *It = find_if(Scalars, [this, E](Value *V) {
return !isa<UndefValue>(V) &&
(getTreeEntry(V) || isGuaranteedNotToBePoison(V) ||
(E->UserTreeIndices.size() == 1 &&
any_of(V->uses(), [E](const Use &U) {
// Check if the value already used in the same operation in
// one of the nodes already.
return E->UserTreeIndices.front().EdgeIdx !=
U.getOperandNo() &&
is_contained(
E->UserTreeIndices.front().UserTE->Scalars,
U.getUser());
})));
});
if (It != Scalars.end()) {
// Replace undefs by the non-poisoned scalars and emit broadcast.
int Pos = std::distance(Scalars.begin(), It);
for_each(UndefPos, [&](int I) {
// Set the undef position to the non-poisoned scalar.
ReuseMask[I] = Pos;
// Replace the undef by the poison, in the mask it is replaced by
// non-poisoned scalar already.
if (I != Pos)
Scalars[I] = PoisonValue::get(ScalarTy);
});
} else {
// Replace undefs by the poisons, emit broadcast and then emit
// freeze.
for_each(UndefPos, [&](int I) {
ReuseMask[I] = PoisonMaskElem;
if (isa<UndefValue>(Scalars[I]))
Scalars[I] = PoisonValue::get(ScalarTy);
});
NeedFreeze = true;
}
}
};
if (ExtractShuffle || GatherShuffle) {
bool IsNonPoisoned = true;
bool IsUsedInExpr = false;
Value *Vec1 = nullptr;
if (ExtractShuffle) {
// Gather of extractelements can be represented as just a shuffle of
// a single/two vectors the scalars are extracted from.
// Find input vectors.
Value *Vec2 = nullptr;
for (unsigned I = 0, Sz = ExtractMask.size(); I < Sz; ++I) {
if (ExtractMask[I] == PoisonMaskElem ||
(!Mask.empty() && Mask[I] != PoisonMaskElem)) {
ExtractMask[I] = PoisonMaskElem;
continue;
}
if (isa<UndefValue>(E->Scalars[I]))
continue;
auto *EI = cast<ExtractElementInst>(E->Scalars[I]);
if (!Vec1) {
Vec1 = EI->getVectorOperand();
} else if (Vec1 != EI->getVectorOperand()) {
assert((!Vec2 || Vec2 == EI->getVectorOperand()) &&
"Expected only 1 or 2 vectors shuffle.");
Vec2 = EI->getVectorOperand();
}
}
if (Vec2) {
IsNonPoisoned &=
isGuaranteedNotToBePoison(Vec1) && isGuaranteedNotToBePoison(Vec2);
ShuffleBuilder.add(Vec1, Vec2, ExtractMask);
} else if (Vec1) {
IsUsedInExpr = FindReusedSplat(ExtractMask);
ShuffleBuilder.add(Vec1, ExtractMask);
IsNonPoisoned &= isGuaranteedNotToBePoison(Vec1);
} else {
ShuffleBuilder.add(PoisonValue::get(FixedVectorType::get(
ScalarTy, GatheredScalars.size())),
ExtractMask);
}
}
if (GatherShuffle) {
if (Entries.size() == 1) {
IsUsedInExpr = FindReusedSplat(Mask);
ShuffleBuilder.add(Entries.front()->VectorizedValue, Mask);
IsNonPoisoned &=
isGuaranteedNotToBePoison(Entries.front()->VectorizedValue);
} else {
ShuffleBuilder.add(Entries.front()->VectorizedValue,
Entries.back()->VectorizedValue, Mask);
IsNonPoisoned &=
isGuaranteedNotToBePoison(Entries.front()->VectorizedValue) &&
isGuaranteedNotToBePoison(Entries.back()->VectorizedValue);
}
}
// Try to figure out best way to combine values: build a shuffle and insert
// elements or just build several shuffles.
// Insert non-constant scalars.
SmallVector<Value *> NonConstants(GatheredScalars);
int EMSz = ExtractMask.size();
int MSz = Mask.size();
// Try to build constant vector and shuffle with it only if currently we
// have a single permutation and more than 1 scalar constants.
bool IsSingleShuffle = !ExtractShuffle || !GatherShuffle;
bool IsIdentityShuffle =
(ExtractShuffle.value_or(TTI::SK_PermuteTwoSrc) ==
TTI::SK_PermuteSingleSrc &&
none_of(ExtractMask, [&](int I) { return I >= EMSz; }) &&
ShuffleVectorInst::isIdentityMask(ExtractMask)) ||
(GatherShuffle.value_or(TTI::SK_PermuteTwoSrc) ==
TTI::SK_PermuteSingleSrc &&
none_of(Mask, [&](int I) { return I >= MSz; }) &&
ShuffleVectorInst::isIdentityMask(Mask));
bool EnoughConstsForShuffle =
IsSingleShuffle &&
(none_of(GatheredScalars,
[](Value *V) {
return isa<UndefValue>(V) && !isa<PoisonValue>(V);
}) ||
any_of(GatheredScalars,
[](Value *V) {
return isa<Constant>(V) && !isa<UndefValue>(V);
})) &&
(!IsIdentityShuffle ||
(GatheredScalars.size() == 2 &&
any_of(GatheredScalars,
[](Value *V) { return !isa<UndefValue>(V); })) ||
count_if(GatheredScalars, [](Value *V) {
return isa<Constant>(V) && !isa<PoisonValue>(V);
}) > 1);
// NonConstants array contains just non-constant values, GatheredScalars
// contains only constant to build final vector and then shuffle.
for (int I = 0, Sz = GatheredScalars.size(); I < Sz; ++I) {
if (EnoughConstsForShuffle && isa<Constant>(GatheredScalars[I]))
NonConstants[I] = PoisonValue::get(ScalarTy);
else
GatheredScalars[I] = PoisonValue::get(ScalarTy);
}
// Generate constants for final shuffle and build a mask for them.
if (!all_of(GatheredScalars, PoisonValue::classof)) {
SmallVector<int> BVMask(GatheredScalars.size(), PoisonMaskElem);
TryPackScalars(GatheredScalars, BVMask, /*IsRootPoison=*/true);
Value *BV = ShuffleBuilder.gather(GatheredScalars);
ShuffleBuilder.add(BV, BVMask);
}
if (all_of(NonConstants, [=](Value *V) {
return isa<PoisonValue>(V) ||
(IsSingleShuffle && ((IsIdentityShuffle &&
IsNonPoisoned) || IsUsedInExpr) && isa<UndefValue>(V));
}))
Res = ShuffleBuilder.finalize(E->ReuseShuffleIndices);
else
Res = ShuffleBuilder.finalize(
E->ReuseShuffleIndices, E->Scalars.size(),
[&](Value *&Vec, SmallVectorImpl<int> &Mask) {
TryPackScalars(NonConstants, Mask, /*IsRootPoison=*/false);
Vec = ShuffleBuilder.gather(NonConstants, Vec);
});
} else if (!allConstant(GatheredScalars)) {
// Gather unique scalars and all constants.
SmallVector<int> ReuseMask(GatheredScalars.size(), PoisonMaskElem);
TryPackScalars(GatheredScalars, ReuseMask, /*IsRootPoison=*/true);
Value *BV = ShuffleBuilder.gather(GatheredScalars);
ShuffleBuilder.add(BV, ReuseMask);
Res = ShuffleBuilder.finalize(E->ReuseShuffleIndices);
} else {
// Gather all constants.
SmallVector<int> Mask(E->Scalars.size(), PoisonMaskElem);
for (auto [I, V] : enumerate(E->Scalars)) {
if (!isa<PoisonValue>(V))
Mask[I] = I;
}
Value *BV = ShuffleBuilder.gather(E->Scalars);
ShuffleBuilder.add(BV, Mask);
Res = ShuffleBuilder.finalize(E->ReuseShuffleIndices);
}
if (NeedFreeze)
Res = ShuffleBuilder.createFreeze(Res);
return Res;
}
Value *BoUpSLP::createBuildVector(const TreeEntry *E) {
return processBuildVector<ShuffleInstructionBuilder, Value *>(E, Builder,
*this);
}
Value *BoUpSLP::vectorizeTree(TreeEntry *E) {
IRBuilder<>::InsertPointGuard Guard(Builder);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *E->Scalars[0] << ".\n");
return E->VectorizedValue;
}
if (E->State == TreeEntry::NeedToGather) {
if (E->getMainOp() && E->Idx == 0)
setInsertPointAfterBundle(E);
Value *Vec = createBuildVector(E);
E->VectorizedValue = Vec;
return Vec;
}
auto FinalShuffle = [&](Value *V, const TreeEntry *E) {
ShuffleInstructionBuilder ShuffleBuilder(Builder, *this);
if (E->getOpcode() == Instruction::Store) {
ArrayRef<int> Mask =
ArrayRef(reinterpret_cast<const int *>(E->ReorderIndices.begin()),
E->ReorderIndices.size());
ShuffleBuilder.add(V, Mask);
} else {
ShuffleBuilder.addOrdered(V, E->ReorderIndices);
}
return ShuffleBuilder.finalize(E->ReuseShuffleIndices);
};
assert((E->State == TreeEntry::Vectorize ||
E->State == TreeEntry::ScatterVectorize) &&
"Unhandled state");
unsigned ShuffleOrOp =
E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode();
Instruction *VL0 = E->getMainOp();
Type *ScalarTy = VL0->getType();
if (auto *Store = dyn_cast<StoreInst>(VL0))
ScalarTy = Store->getValueOperand()->getType();
else if (auto *IE = dyn_cast<InsertElementInst>(VL0))
ScalarTy = IE->getOperand(1)->getType();
auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size());
switch (ShuffleOrOp) {
case Instruction::PHI: {
assert((E->ReorderIndices.empty() ||
E != VectorizableTree.front().get() ||
!E->UserTreeIndices.empty()) &&
"PHI reordering is free.");
auto *PH = cast<PHINode>(VL0);
Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI());
Builder.SetCurrentDebugLocation(PH->getDebugLoc());
PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues());
Value *V = NewPhi;
// Adjust insertion point once all PHI's have been generated.
Builder.SetInsertPoint(&*PH->getParent()->getFirstInsertionPt());
Builder.SetCurrentDebugLocation(PH->getDebugLoc());
V = FinalShuffle(V, E);
E->VectorizedValue = V;
// PHINodes may have multiple entries from the same block. We want to
// visit every block once.
SmallPtrSet<BasicBlock*, 4> VisitedBBs;
for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) {
ValueList Operands;
BasicBlock *IBB = PH->getIncomingBlock(i);
// Stop emission if all incoming values are generated.
if (NewPhi->getNumIncomingValues() == PH->getNumIncomingValues()) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return V;
}
if (!VisitedBBs.insert(IBB).second) {
NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB);
continue;
}
Builder.SetInsertPoint(IBB->getTerminator());
Builder.SetCurrentDebugLocation(PH->getDebugLoc());
Value *Vec = vectorizeOperand(E, i);
NewPhi->addIncoming(Vec, IBB);
}
assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() &&
"Invalid number of incoming values");
return V;
}
case Instruction::ExtractElement: {
Value *V = E->getSingleOperand(0);
setInsertPointAfterBundle(E);
V = FinalShuffle(V, E);
E->VectorizedValue = V;
return V;
}
case Instruction::ExtractValue: {
auto *LI = cast<LoadInst>(E->getSingleOperand(0));
Builder.SetInsertPoint(LI);
auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace());
Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy);
LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign());
Value *NewV = propagateMetadata(V, E->Scalars);
NewV = FinalShuffle(NewV, E);
E->VectorizedValue = NewV;
return NewV;
}
case Instruction::InsertElement: {
assert(E->ReuseShuffleIndices.empty() && "All inserts should be unique");
Builder.SetInsertPoint(cast<Instruction>(E->Scalars.back()));
Value *V = vectorizeOperand(E, 1);
// Create InsertVector shuffle if necessary
auto *FirstInsert = cast<Instruction>(*find_if(E->Scalars, [E](Value *V) {
return !is_contained(E->Scalars, cast<Instruction>(V)->getOperand(0));
}));
const unsigned NumElts =
cast<FixedVectorType>(FirstInsert->getType())->getNumElements();
const unsigned NumScalars = E->Scalars.size();
unsigned Offset = *getInsertIndex(VL0);
assert(Offset < NumElts && "Failed to find vector index offset");
// Create shuffle to resize vector
SmallVector<int> Mask;
if (!E->ReorderIndices.empty()) {
inversePermutation(E->ReorderIndices, Mask);
Mask.append(NumElts - NumScalars, PoisonMaskElem);
} else {
Mask.assign(NumElts, PoisonMaskElem);
std::iota(Mask.begin(), std::next(Mask.begin(), NumScalars), 0);
}
// Create InsertVector shuffle if necessary
bool IsIdentity = true;
SmallVector<int> PrevMask(NumElts, PoisonMaskElem);
Mask.swap(PrevMask);
for (unsigned I = 0; I < NumScalars; ++I) {
Value *Scalar = E->Scalars[PrevMask[I]];
unsigned InsertIdx = *getInsertIndex(Scalar);
IsIdentity &= InsertIdx - Offset == I;
Mask[InsertIdx - Offset] = I;
}
if (!IsIdentity || NumElts != NumScalars) {
V = Builder.CreateShuffleVector(V, Mask);
if (auto *I = dyn_cast<Instruction>(V)) {
GatherShuffleExtractSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
}
SmallVector<int> InsertMask(NumElts, PoisonMaskElem);
for (unsigned I = 0; I < NumElts; I++) {
if (Mask[I] != PoisonMaskElem)
InsertMask[Offset + I] = I;
}
SmallBitVector UseMask =
buildUseMask(NumElts, InsertMask, UseMask::UndefsAsMask);
SmallBitVector IsFirstUndef =
isUndefVector(FirstInsert->getOperand(0), UseMask);
if ((!IsIdentity || Offset != 0 || !IsFirstUndef.all()) &&
NumElts != NumScalars) {
if (IsFirstUndef.all()) {
if (!ShuffleVectorInst::isIdentityMask(InsertMask)) {
SmallBitVector IsFirstPoison =
isUndefVector<true>(FirstInsert->getOperand(0), UseMask);
if (!IsFirstPoison.all()) {
for (unsigned I = 0; I < NumElts; I++) {
if (InsertMask[I] == PoisonMaskElem && !IsFirstPoison.test(I))
InsertMask[I] = I + NumElts;
}
}
V = Builder.CreateShuffleVector(
V,
IsFirstPoison.all() ? PoisonValue::get(V->getType())
: FirstInsert->getOperand(0),
InsertMask, cast<Instruction>(E->Scalars.back())->getName());
if (auto *I = dyn_cast<Instruction>(V)) {
GatherShuffleExtractSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
}
} else {
SmallBitVector IsFirstPoison =
isUndefVector<true>(FirstInsert->getOperand(0), UseMask);
for (unsigned I = 0; I < NumElts; I++) {
if (InsertMask[I] == PoisonMaskElem)
InsertMask[I] = IsFirstPoison.test(I) ? PoisonMaskElem : I;
else
InsertMask[I] += NumElts;
}
V = Builder.CreateShuffleVector(
FirstInsert->getOperand(0), V, InsertMask,
cast<Instruction>(E->Scalars.back())->getName());
if (auto *I = dyn_cast<Instruction>(V)) {
GatherShuffleExtractSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
}
}
++NumVectorInstructions;
E->VectorizedValue = V;
return V;
}
case Instruction::ZExt:
case Instruction::SExt:
case Instruction::FPToUI:
case Instruction::FPToSI:
case Instruction::FPExt:
case Instruction::PtrToInt:
case Instruction::IntToPtr:
case Instruction::SIToFP:
case Instruction::UIToFP:
case Instruction::Trunc:
case Instruction::FPTrunc:
case Instruction::BitCast: {
setInsertPointAfterBundle(E);
Value *InVec = vectorizeOperand(E, 0);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
auto *CI = cast<CastInst>(VL0);
Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy);
V = FinalShuffle(V, E);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::FCmp:
case Instruction::ICmp: {
setInsertPointAfterBundle(E);
Value *L = vectorizeOperand(E, 0);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *R = vectorizeOperand(E, 1);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate();
Value *V = Builder.CreateCmp(P0, L, R);
propagateIRFlags(V, E->Scalars, VL0);
V = FinalShuffle(V, E);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::Select: {
setInsertPointAfterBundle(E);
Value *Cond = vectorizeOperand(E, 0);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *True = vectorizeOperand(E, 1);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *False = vectorizeOperand(E, 2);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *V = Builder.CreateSelect(Cond, True, False);
V = FinalShuffle(V, E);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::FNeg: {
setInsertPointAfterBundle(E);
Value *Op = vectorizeOperand(E, 0);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *V = Builder.CreateUnOp(
static_cast<Instruction::UnaryOps>(E->getOpcode()), Op);
propagateIRFlags(V, E->Scalars, VL0);
if (auto *I = dyn_cast<Instruction>(V))
V = propagateMetadata(I, E->Scalars);
V = FinalShuffle(V, E);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::Add:
case Instruction::FAdd:
case Instruction::Sub:
case Instruction::FSub:
case Instruction::Mul:
case Instruction::FMul:
case Instruction::UDiv:
case Instruction::SDiv:
case Instruction::FDiv:
case Instruction::URem:
case Instruction::SRem:
case Instruction::FRem:
case Instruction::Shl:
case Instruction::LShr:
case Instruction::AShr:
case Instruction::And:
case Instruction::Or:
case Instruction::Xor: {
setInsertPointAfterBundle(E);
Value *LHS = vectorizeOperand(E, 0);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *RHS = vectorizeOperand(E, 1);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *V = Builder.CreateBinOp(
static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS,
RHS);
propagateIRFlags(V, E->Scalars, VL0);
if (auto *I = dyn_cast<Instruction>(V))
V = propagateMetadata(I, E->Scalars);
V = FinalShuffle(V, E);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::Load: {
// Loads are inserted at the head of the tree because we don't want to
// sink them all the way down past store instructions.
setInsertPointAfterBundle(E);
LoadInst *LI = cast<LoadInst>(VL0);
Instruction *NewLI;
unsigned AS = LI->getPointerAddressSpace();
Value *PO = LI->getPointerOperand();
if (E->State == TreeEntry::Vectorize) {
Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS));
NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign());
// The pointer operand uses an in-tree scalar so we add the new BitCast
// or LoadInst to ExternalUses list to make sure that an extract will
// be generated in the future.
if (TreeEntry *Entry = getTreeEntry(PO)) {
// Find which lane we need to extract.
unsigned FoundLane = Entry->findLaneForValue(PO);
ExternalUses.emplace_back(
PO, PO != VecPtr ? cast<User>(VecPtr) : NewLI, FoundLane);
}
} else {
assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state");
Value *VecPtr = vectorizeOperand(E, 0);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
// Use the minimum alignment of the gathered loads.
Align CommonAlignment = LI->getAlign();
for (Value *V : E->Scalars)
CommonAlignment =
std::min(CommonAlignment, cast<LoadInst>(V)->getAlign());
NewLI = Builder.CreateMaskedGather(VecTy, VecPtr, CommonAlignment);
}
Value *V = propagateMetadata(NewLI, E->Scalars);
V = FinalShuffle(V, E);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::Store: {
auto *SI = cast<StoreInst>(VL0);
unsigned AS = SI->getPointerAddressSpace();
setInsertPointAfterBundle(E);
Value *VecValue = vectorizeOperand(E, 0);
VecValue = FinalShuffle(VecValue, E);
Value *ScalarPtr = SI->getPointerOperand();
Value *VecPtr = Builder.CreateBitCast(
ScalarPtr, VecValue->getType()->getPointerTo(AS));
StoreInst *ST =
Builder.CreateAlignedStore(VecValue, VecPtr, SI->getAlign());
// The pointer operand uses an in-tree scalar, so add the new BitCast or
// StoreInst to ExternalUses to make sure that an extract will be
// generated in the future.
if (TreeEntry *Entry = getTreeEntry(ScalarPtr)) {
// Find which lane we need to extract.
unsigned FoundLane = Entry->findLaneForValue(ScalarPtr);
ExternalUses.push_back(ExternalUser(
ScalarPtr, ScalarPtr != VecPtr ? cast<User>(VecPtr) : ST,
FoundLane));
}
Value *V = propagateMetadata(ST, E->Scalars);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::GetElementPtr: {
auto *GEP0 = cast<GetElementPtrInst>(VL0);
setInsertPointAfterBundle(E);
Value *Op0 = vectorizeOperand(E, 0);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
SmallVector<Value *> OpVecs;
for (int J = 1, N = GEP0->getNumOperands(); J < N; ++J) {
Value *OpVec = vectorizeOperand(E, J);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
OpVecs.push_back(OpVec);
}
Value *V = Builder.CreateGEP(GEP0->getSourceElementType(), Op0, OpVecs);
if (Instruction *I = dyn_cast<GetElementPtrInst>(V)) {
SmallVector<Value *> GEPs;
for (Value *V : E->Scalars) {
if (isa<GetElementPtrInst>(V))
GEPs.push_back(V);
}
V = propagateMetadata(I, GEPs);
}
V = FinalShuffle(V, E);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::Call: {
CallInst *CI = cast<CallInst>(VL0);
setInsertPointAfterBundle(E);
Intrinsic::ID IID = Intrinsic::not_intrinsic;
if (Function *FI = CI->getCalledFunction())
IID = FI->getIntrinsicID();
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI);
bool UseIntrinsic = ID != Intrinsic::not_intrinsic &&
VecCallCosts.first <= VecCallCosts.second;
Value *ScalarArg = nullptr;
std::vector<Value *> OpVecs;
SmallVector<Type *, 2> TysForDecl;
// Add return type if intrinsic is overloaded on it.
if (isVectorIntrinsicWithOverloadTypeAtArg(IID, -1))
TysForDecl.push_back(
FixedVectorType::get(CI->getType(), E->Scalars.size()));
for (int j = 0, e = CI->arg_size(); j < e; ++j) {
ValueList OpVL;
// Some intrinsics have scalar arguments. This argument should not be
// vectorized.
if (UseIntrinsic && isVectorIntrinsicWithScalarOpAtArg(IID, j)) {
CallInst *CEI = cast<CallInst>(VL0);
ScalarArg = CEI->getArgOperand(j);
OpVecs.push_back(CEI->getArgOperand(j));
if (isVectorIntrinsicWithOverloadTypeAtArg(IID, j))
TysForDecl.push_back(ScalarArg->getType());
continue;
}
Value *OpVec = vectorizeOperand(E, j);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n");
OpVecs.push_back(OpVec);
if (isVectorIntrinsicWithOverloadTypeAtArg(IID, j))
TysForDecl.push_back(OpVec->getType());
}
Function *CF;
if (!UseIntrinsic) {
VFShape Shape =
VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>(
VecTy->getNumElements())),
false /*HasGlobalPred*/);
CF = VFDatabase(*CI).getVectorizedFunction(Shape);
} else {
CF = Intrinsic::getDeclaration(F->getParent(), ID, TysForDecl);
}
SmallVector<OperandBundleDef, 1> OpBundles;
CI->getOperandBundlesAsDefs(OpBundles);
Value *V = Builder.CreateCall(CF, OpVecs, OpBundles);
// The scalar argument uses an in-tree scalar so we add the new vectorized
// call to ExternalUses list to make sure that an extract will be
// generated in the future.
if (ScalarArg) {
if (TreeEntry *Entry = getTreeEntry(ScalarArg)) {
// Find which lane we need to extract.
unsigned FoundLane = Entry->findLaneForValue(ScalarArg);
ExternalUses.push_back(
ExternalUser(ScalarArg, cast<User>(V), FoundLane));
}
}
propagateIRFlags(V, E->Scalars, VL0);
V = FinalShuffle(V, E);
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::ShuffleVector: {
assert(E->isAltShuffle() &&
((Instruction::isBinaryOp(E->getOpcode()) &&
Instruction::isBinaryOp(E->getAltOpcode())) ||
(Instruction::isCast(E->getOpcode()) &&
Instruction::isCast(E->getAltOpcode())) ||
(isa<CmpInst>(VL0) && isa<CmpInst>(E->getAltOp()))) &&
"Invalid Shuffle Vector Operand");
Value *LHS = nullptr, *RHS = nullptr;
if (Instruction::isBinaryOp(E->getOpcode()) || isa<CmpInst>(VL0)) {
setInsertPointAfterBundle(E);
LHS = vectorizeOperand(E, 0);
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
RHS = vectorizeOperand(E, 1);
} else {
setInsertPointAfterBundle(E);
LHS = vectorizeOperand(E, 0);
}
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *V0, *V1;
if (Instruction::isBinaryOp(E->getOpcode())) {
V0 = Builder.CreateBinOp(
static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS);
V1 = Builder.CreateBinOp(
static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS);
} else if (auto *CI0 = dyn_cast<CmpInst>(VL0)) {
V0 = Builder.CreateCmp(CI0->getPredicate(), LHS, RHS);
auto *AltCI = cast<CmpInst>(E->getAltOp());
CmpInst::Predicate AltPred = AltCI->getPredicate();
V1 = Builder.CreateCmp(AltPred, LHS, RHS);
} else {
V0 = Builder.CreateCast(
static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy);
V1 = Builder.CreateCast(
static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy);
}
// Add V0 and V1 to later analysis to try to find and remove matching
// instruction, if any.
for (Value *V : {V0, V1}) {
if (auto *I = dyn_cast<Instruction>(V)) {
GatherShuffleExtractSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
}
// Create shuffle to take alternate operations from the vector.
// Also, gather up main and alt scalar ops to propagate IR flags to
// each vector operation.
ValueList OpScalars, AltScalars;
SmallVector<int> Mask;
buildShuffleEntryMask(
E->Scalars, E->ReorderIndices, E->ReuseShuffleIndices,
[E, this](Instruction *I) {
assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode");
return isAlternateInstruction(I, E->getMainOp(), E->getAltOp(),
*TLI);
},
Mask, &OpScalars, &AltScalars);
propagateIRFlags(V0, OpScalars);
propagateIRFlags(V1, AltScalars);
Value *V = Builder.CreateShuffleVector(V0, V1, Mask);
if (auto *I = dyn_cast<Instruction>(V)) {
V = propagateMetadata(I, E->Scalars);
GatherShuffleExtractSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
default:
llvm_unreachable("unknown inst");
}
return nullptr;
}
Value *BoUpSLP::vectorizeTree() {
ExtraValueToDebugLocsMap ExternallyUsedValues;
SmallVector<std::pair<Value *, Value *>> ReplacedExternals;
return vectorizeTree(ExternallyUsedValues, ReplacedExternals);
}
namespace {
/// Data type for handling buildvector sequences with the reused scalars from
/// other tree entries.
struct ShuffledInsertData {
/// List of insertelements to be replaced by shuffles.
SmallVector<InsertElementInst *> InsertElements;
/// The parent vectors and shuffle mask for the given list of inserts.
MapVector<Value *, SmallVector<int>> ValueMasks;
};
} // namespace
Value *BoUpSLP::vectorizeTree(
const ExtraValueToDebugLocsMap &ExternallyUsedValues,
SmallVectorImpl<std::pair<Value *, Value *>> &ReplacedExternals,
Instruction *ReductionRoot) {
// All blocks must be scheduled before any instructions are inserted.
for (auto &BSIter : BlocksSchedules) {
scheduleBlock(BSIter.second.get());
}
// Pre-gather last instructions.
for (const std::unique_ptr<TreeEntry> &E : VectorizableTree) {
if ((E->State == TreeEntry::NeedToGather &&
(!E->getMainOp() || E->Idx > 0)) ||
(E->State != TreeEntry::NeedToGather &&
E->getOpcode() == Instruction::ExtractValue) ||
E->getOpcode() == Instruction::InsertElement)
continue;
Instruction *LastInst = &getLastInstructionInBundle(E.get());
EntryToLastInstruction.try_emplace(E.get(), LastInst);
}
Builder.SetInsertPoint(ReductionRoot ? ReductionRoot
: &F->getEntryBlock().front());
auto *VectorRoot = vectorizeTree(VectorizableTree[0].get());
// Run through the list of postponed gathers and emit them, replacing the temp
// emitted allocas with actual vector instructions.
ArrayRef<const TreeEntry *> PostponedNodes = PostponedGathers.getArrayRef();
DenseMap<Value *, SmallVector<TreeEntry *>> PostponedValues;
for (const TreeEntry *E : PostponedNodes) {
auto *TE = const_cast<TreeEntry *>(E);
if (auto *VecTE = getTreeEntry(TE->Scalars.front()))
if (VecTE->isSame(TE->UserTreeIndices.front().UserTE->getOperand(
TE->UserTreeIndices.front().EdgeIdx)))
// Found gather node which is absolutely the same as one of the
// vectorized nodes. It may happen after reordering.
continue;
auto *PrevVec = cast<Instruction>(TE->VectorizedValue);
TE->VectorizedValue = nullptr;
auto *UserI =
cast<Instruction>(TE->UserTreeIndices.front().UserTE->VectorizedValue);
Builder.SetInsertPoint(PrevVec);
Builder.SetCurrentDebugLocation(UserI->getDebugLoc());
Value *Vec = vectorizeTree(TE);
PrevVec->replaceAllUsesWith(Vec);
PostponedValues.try_emplace(Vec).first->second.push_back(TE);
// Replace the stub vector node, if it was used before for one of the
// buildvector nodes already.
auto It = PostponedValues.find(PrevVec);
if (It != PostponedValues.end()) {
for (TreeEntry *VTE : It->getSecond())
VTE->VectorizedValue = Vec;
}
eraseInstruction(PrevVec);
}
// If the vectorized tree can be rewritten in a smaller type, we truncate the
// vectorized root. InstCombine will then rewrite the entire expression. We
// sign extend the extracted values below.
auto *ScalarRoot = VectorizableTree[0]->Scalars[0];
if (MinBWs.count(ScalarRoot)) {
if (auto *I = dyn_cast<Instruction>(VectorRoot)) {
// If current instr is a phi and not the last phi, insert it after the
// last phi node.
if (isa<PHINode>(I))
Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt());
else
Builder.SetInsertPoint(&*++BasicBlock::iterator(I));
}
auto BundleWidth = VectorizableTree[0]->Scalars.size();
auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first);
auto *VecTy = FixedVectorType::get(MinTy, BundleWidth);
auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy);
VectorizableTree[0]->VectorizedValue = Trunc;
}
LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size()
<< " values .\n");
SmallVector<ShuffledInsertData> ShuffledInserts;
// Maps vector instruction to original insertelement instruction
DenseMap<Value *, InsertElementInst *> VectorToInsertElement;
// Maps extract Scalar to the corresponding extractelement instruction in the
// basic block. Only one extractelement per block should be emitted.
DenseMap<Value *, DenseMap<BasicBlock *, Instruction *>> ScalarToEEs;
// Extract all of the elements with the external uses.
for (const auto &ExternalUse : ExternalUses) {
Value *Scalar = ExternalUse.Scalar;
llvm::User *User = ExternalUse.User;
// Skip users that we already RAUW. This happens when one instruction
// has multiple uses of the same value.
if (User && !is_contained(Scalar->users(), User))
continue;
TreeEntry *E = getTreeEntry(Scalar);
assert(E && "Invalid scalar");
assert(E->State != TreeEntry::NeedToGather &&
"Extracting from a gather list");
// Non-instruction pointers are not deleted, just skip them.
if (E->getOpcode() == Instruction::GetElementPtr &&
!isa<GetElementPtrInst>(Scalar))
continue;
Value *Vec = E->VectorizedValue;
assert(Vec && "Can't find vectorizable value");
Value *Lane = Builder.getInt32(ExternalUse.Lane);
auto ExtractAndExtendIfNeeded = [&](Value *Vec) {
if (Scalar->getType() != Vec->getType()) {
Value *Ex = nullptr;
auto It = ScalarToEEs.find(Scalar);
if (It != ScalarToEEs.end()) {
// No need to emit many extracts, just move the only one in the
// current block.
auto EEIt = It->second.find(Builder.GetInsertBlock());
if (EEIt != It->second.end()) {
Instruction *I = EEIt->second;
if (Builder.GetInsertPoint() != Builder.GetInsertBlock()->end() &&
Builder.GetInsertPoint()->comesBefore(I))
I->moveBefore(&*Builder.GetInsertPoint());
Ex = I;
}
}
if (!Ex) {
// "Reuse" the existing extract to improve final codegen.
if (auto *ES = dyn_cast<ExtractElementInst>(Scalar)) {
Ex = Builder.CreateExtractElement(ES->getOperand(0),
ES->getOperand(1));
} else {
Ex = Builder.CreateExtractElement(Vec, Lane);
}
if (auto *I = dyn_cast<Instruction>(Ex))
ScalarToEEs[Scalar].try_emplace(Builder.GetInsertBlock(), I);
}
// The then branch of the previous if may produce constants, since 0
// operand might be a constant.
if (auto *ExI = dyn_cast<Instruction>(Ex)) {
GatherShuffleExtractSeq.insert(ExI);
CSEBlocks.insert(ExI->getParent());
}
// If necessary, sign-extend or zero-extend ScalarRoot
// to the larger type.
if (!MinBWs.count(ScalarRoot))
return Ex;
if (MinBWs[ScalarRoot].second)
return Builder.CreateSExt(Ex, Scalar->getType());
return Builder.CreateZExt(Ex, Scalar->getType());
}
assert(isa<FixedVectorType>(Scalar->getType()) &&
isa<InsertElementInst>(Scalar) &&
"In-tree scalar of vector type is not insertelement?");
auto *IE = cast<InsertElementInst>(Scalar);
VectorToInsertElement.try_emplace(Vec, IE);
return Vec;
};
// If User == nullptr, the Scalar is used as extra arg. Generate
// ExtractElement instruction and update the record for this scalar in
// ExternallyUsedValues.
if (!User) {
assert(ExternallyUsedValues.count(Scalar) &&
"Scalar with nullptr as an external user must be registered in "
"ExternallyUsedValues map");
if (auto *VecI = dyn_cast<Instruction>(Vec)) {
if (auto *PHI = dyn_cast<PHINode>(VecI))
Builder.SetInsertPoint(PHI->getParent()->getFirstNonPHI());
else
Builder.SetInsertPoint(VecI->getParent(),
std::next(VecI->getIterator()));
} else {
Builder.SetInsertPoint(&F->getEntryBlock().front());
}
Value *NewInst = ExtractAndExtendIfNeeded(Vec);
// Required to update internally referenced instructions.
Scalar->replaceAllUsesWith(NewInst);
ReplacedExternals.emplace_back(Scalar, NewInst);
continue;
}
if (auto *VU = dyn_cast<InsertElementInst>(User)) {
// Skip if the scalar is another vector op or Vec is not an instruction.
if (!Scalar->getType()->isVectorTy() && isa<Instruction>(Vec)) {
if (auto *FTy = dyn_cast<FixedVectorType>(User->getType())) {
std::optional<unsigned> InsertIdx = getInsertIndex(VU);
if (InsertIdx) {
// Need to use original vector, if the root is truncated.
if (MinBWs.count(Scalar) &&
VectorizableTree[0]->VectorizedValue == Vec)
Vec = VectorRoot;
auto *It =
find_if(ShuffledInserts, [VU](const ShuffledInsertData &Data) {
// Checks if 2 insertelements are from the same buildvector.
InsertElementInst *VecInsert = Data.InsertElements.front();
return areTwoInsertFromSameBuildVector(
VU, VecInsert,
[](InsertElementInst *II) { return II->getOperand(0); });
});
unsigned Idx = *InsertIdx;
if (It == ShuffledInserts.end()) {
(void)ShuffledInserts.emplace_back();
It = std::next(ShuffledInserts.begin(),
ShuffledInserts.size() - 1);
SmallVectorImpl<int> &Mask = It->ValueMasks[Vec];
if (Mask.empty())
Mask.assign(FTy->getNumElements(), PoisonMaskElem);
// Find the insertvector, vectorized in tree, if any.
Value *Base = VU;
while (auto *IEBase = dyn_cast<InsertElementInst>(Base)) {
if (IEBase != User &&
(!IEBase->hasOneUse() ||
getInsertIndex(IEBase).value_or(Idx) == Idx))
break;
// Build the mask for the vectorized insertelement instructions.
if (const TreeEntry *E = getTreeEntry(IEBase)) {
do {
IEBase = cast<InsertElementInst>(Base);
int IEIdx = *getInsertIndex(IEBase);
assert(Mask[Idx] == PoisonMaskElem &&
"InsertElementInstruction used already.");
Mask[IEIdx] = IEIdx;
Base = IEBase->getOperand(0);
} while (E == getTreeEntry(Base));
break;
}
Base = cast<InsertElementInst>(Base)->getOperand(0);
// After the vectorization the def-use chain has changed, need
// to look through original insertelement instructions, if they
// get replaced by vector instructions.
auto It = VectorToInsertElement.find(Base);
if (It != VectorToInsertElement.end())
Base = It->second;
}
}
SmallVectorImpl<int> &Mask = It->ValueMasks[Vec];
if (Mask.empty())
Mask.assign(FTy->getNumElements(), PoisonMaskElem);
Mask[Idx] = ExternalUse.Lane;
It->InsertElements.push_back(cast<InsertElementInst>(User));
continue;
}
}
}
}
// Generate extracts for out-of-tree users.
// Find the insertion point for the extractelement lane.
if (auto *VecI = dyn_cast<Instruction>(Vec)) {
if (PHINode *PH = dyn_cast<PHINode>(User)) {
for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) {
if (PH->getIncomingValue(i) == Scalar) {
Instruction *IncomingTerminator =
PH->getIncomingBlock(i)->getTerminator();
if (isa<CatchSwitchInst>(IncomingTerminator)) {
Builder.SetInsertPoint(VecI->getParent(),
std::next(VecI->getIterator()));
} else {
Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator());
}
Value *NewInst = ExtractAndExtendIfNeeded(Vec);
PH->setOperand(i, NewInst);
}
}
} else {
Builder.SetInsertPoint(cast<Instruction>(User));
Value *NewInst = ExtractAndExtendIfNeeded(Vec);
User->replaceUsesOfWith(Scalar, NewInst);
}
} else {
Builder.SetInsertPoint(&F->getEntryBlock().front());
Value *NewInst = ExtractAndExtendIfNeeded(Vec);
User->replaceUsesOfWith(Scalar, NewInst);
}
LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n");
}
auto CreateShuffle = [&](Value *V1, Value *V2, ArrayRef<int> Mask) {
SmallVector<int> CombinedMask1(Mask.size(), PoisonMaskElem);
SmallVector<int> CombinedMask2(Mask.size(), PoisonMaskElem);
int VF = cast<FixedVectorType>(V1->getType())->getNumElements();
for (int I = 0, E = Mask.size(); I < E; ++I) {
if (Mask[I] < VF)
CombinedMask1[I] = Mask[I];
else
CombinedMask2[I] = Mask[I] - VF;
}
ShuffleInstructionBuilder ShuffleBuilder(Builder, *this);
ShuffleBuilder.add(V1, CombinedMask1);
if (V2)
ShuffleBuilder.add(V2, CombinedMask2);
return ShuffleBuilder.finalize(std::nullopt);
};
auto &&ResizeToVF = [&CreateShuffle](Value *Vec, ArrayRef<int> Mask,
bool ForSingleMask) {
unsigned VF = Mask.size();
unsigned VecVF = cast<FixedVectorType>(Vec->getType())->getNumElements();
if (VF != VecVF) {
if (any_of(Mask, [VF](int Idx) { return Idx >= static_cast<int>(VF); })) {
Vec = CreateShuffle(Vec, nullptr, Mask);
return std::make_pair(Vec, true);
}
if (!ForSingleMask) {
SmallVector<int> ResizeMask(VF, PoisonMaskElem);
for (unsigned I = 0; I < VF; ++I) {
if (Mask[I] != PoisonMaskElem)
ResizeMask[Mask[I]] = Mask[I];
}
Vec = CreateShuffle(Vec, nullptr, ResizeMask);
}
}
return std::make_pair(Vec, false);
};
// Perform shuffling of the vectorize tree entries for better handling of
// external extracts.
for (int I = 0, E = ShuffledInserts.size(); I < E; ++I) {
// Find the first and the last instruction in the list of insertelements.
sort(ShuffledInserts[I].InsertElements, isFirstInsertElement);
InsertElementInst *FirstInsert = ShuffledInserts[I].InsertElements.front();
InsertElementInst *LastInsert = ShuffledInserts[I].InsertElements.back();
Builder.SetInsertPoint(LastInsert);
auto Vector = ShuffledInserts[I].ValueMasks.takeVector();
Value *NewInst = performExtractsShuffleAction<Value>(
MutableArrayRef(Vector.data(), Vector.size()),
FirstInsert->getOperand(0),
[](Value *Vec) {
return cast<VectorType>(Vec->getType())
->getElementCount()
.getKnownMinValue();
},
ResizeToVF,
[FirstInsert, &CreateShuffle](ArrayRef<int> Mask,
ArrayRef<Value *> Vals) {
assert((Vals.size() == 1 || Vals.size() == 2) &&
"Expected exactly 1 or 2 input values.");
if (Vals.size() == 1) {
// Do not create shuffle if the mask is a simple identity
// non-resizing mask.
if (Mask.size() != cast<FixedVectorType>(Vals.front()->getType())
->getNumElements() ||
!ShuffleVectorInst::isIdentityMask(Mask))
return CreateShuffle(Vals.front(), nullptr, Mask);
return Vals.front();
}
return CreateShuffle(Vals.front() ? Vals.front()
: FirstInsert->getOperand(0),
Vals.back(), Mask);
});
auto It = ShuffledInserts[I].InsertElements.rbegin();
// Rebuild buildvector chain.
InsertElementInst *II = nullptr;
if (It != ShuffledInserts[I].InsertElements.rend())
II = *It;
SmallVector<Instruction *> Inserts;
while (It != ShuffledInserts[I].InsertElements.rend()) {
assert(II && "Must be an insertelement instruction.");
if (*It == II)
++It;
else
Inserts.push_back(cast<Instruction>(II));
II = dyn_cast<InsertElementInst>(II->getOperand(0));
}
for (Instruction *II : reverse(Inserts)) {
II->replaceUsesOfWith(II->getOperand(0), NewInst);
if (auto *NewI = dyn_cast<Instruction>(NewInst))
if (II->getParent() == NewI->getParent() && II->comesBefore(NewI))
II->moveAfter(NewI);
NewInst = II;
}
LastInsert->replaceAllUsesWith(NewInst);
for (InsertElementInst *IE : reverse(ShuffledInserts[I].InsertElements)) {
IE->replaceUsesOfWith(IE->getOperand(0),
PoisonValue::get(IE->getOperand(0)->getType()));
IE->replaceUsesOfWith(IE->getOperand(1),
PoisonValue::get(IE->getOperand(1)->getType()));
eraseInstruction(IE);
}
CSEBlocks.insert(LastInsert->getParent());
}
SmallVector<Instruction *> RemovedInsts;
// For each vectorized value:
for (auto &TEPtr : VectorizableTree) {
TreeEntry *Entry = TEPtr.get();
// No need to handle users of gathered values.
if (Entry->State == TreeEntry::NeedToGather)
continue;
assert(Entry->VectorizedValue && "Can't find vectorizable value");
// For each lane:
for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) {
Value *Scalar = Entry->Scalars[Lane];
if (Entry->getOpcode() == Instruction::GetElementPtr &&
!isa<GetElementPtrInst>(Scalar))
continue;
#ifndef NDEBUG
Type *Ty = Scalar->getType();
if (!Ty->isVoidTy()) {
for (User *U : Scalar->users()) {
LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n");
// It is legal to delete users in the ignorelist.
assert((getTreeEntry(U) ||
(UserIgnoreList && UserIgnoreList->contains(U)) ||
(isa_and_nonnull<Instruction>(U) &&
isDeleted(cast<Instruction>(U)))) &&
"Deleting out-of-tree value");
}
}
#endif
LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n");
eraseInstruction(cast<Instruction>(Scalar));
// Retain to-be-deleted instructions for some debug-info
// bookkeeping. NOTE: eraseInstruction only marks the instruction for
// deletion - instructions are not deleted until later.
RemovedInsts.push_back(cast<Instruction>(Scalar));
}
}
// Merge the DIAssignIDs from the about-to-be-deleted instructions into the
// new vector instruction.
if (auto *V = dyn_cast<Instruction>(VectorizableTree[0]->VectorizedValue))
V->mergeDIAssignID(RemovedInsts);
Builder.ClearInsertionPoint();
InstrElementSize.clear();
return VectorizableTree[0]->VectorizedValue;
}
void BoUpSLP::optimizeGatherSequence() {
LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherShuffleExtractSeq.size()
<< " gather sequences instructions.\n");
// LICM InsertElementInst sequences.
for (Instruction *I : GatherShuffleExtractSeq) {
if (isDeleted(I))
continue;
// Check if this block is inside a loop.
Loop *L = LI->getLoopFor(I->getParent());
if (!L)
continue;
// Check if it has a preheader.
BasicBlock *PreHeader = L->getLoopPreheader();
if (!PreHeader)
continue;
// If the vector or the element that we insert into it are
// instructions that are defined in this basic block then we can't
// hoist this instruction.
if (any_of(I->operands(), [L](Value *V) {
auto *OpI = dyn_cast<Instruction>(V);
return OpI && L->contains(OpI);
}))
continue;
// We can hoist this instruction. Move it to the pre-header.
I->moveBefore(PreHeader->getTerminator());
CSEBlocks.insert(PreHeader);
}
// Make a list of all reachable blocks in our CSE queue.
SmallVector<const DomTreeNode *, 8> CSEWorkList;
CSEWorkList.reserve(CSEBlocks.size());
for (BasicBlock *BB : CSEBlocks)
if (DomTreeNode *N = DT->getNode(BB)) {
assert(DT->isReachableFromEntry(N));
CSEWorkList.push_back(N);
}
// Sort blocks by domination. This ensures we visit a block after all blocks
// dominating it are visited.
llvm::sort(CSEWorkList, [](const DomTreeNode *A, const DomTreeNode *B) {
assert((A == B) == (A->getDFSNumIn() == B->getDFSNumIn()) &&
"Different nodes should have different DFS numbers");
return A->getDFSNumIn() < B->getDFSNumIn();
});
// Less defined shuffles can be replaced by the more defined copies.
// Between two shuffles one is less defined if it has the same vector operands
// and its mask indeces are the same as in the first one or undefs. E.g.
// shuffle %0, poison, <0, 0, 0, undef> is less defined than shuffle %0,
// poison, <0, 0, 0, 0>.
auto &&IsIdenticalOrLessDefined = [this](Instruction *I1, Instruction *I2,
SmallVectorImpl<int> &NewMask) {
if (I1->getType() != I2->getType())
return false;
auto *SI1 = dyn_cast<ShuffleVectorInst>(I1);
auto *SI2 = dyn_cast<ShuffleVectorInst>(I2);
if (!SI1 || !SI2)
return I1->isIdenticalTo(I2);
if (SI1->isIdenticalTo(SI2))
return true;
for (int I = 0, E = SI1->getNumOperands(); I < E; ++I)
if (SI1->getOperand(I) != SI2->getOperand(I))
return false;
// Check if the second instruction is more defined than the first one.
NewMask.assign(SI2->getShuffleMask().begin(), SI2->getShuffleMask().end());
ArrayRef<int> SM1 = SI1->getShuffleMask();
// Count trailing undefs in the mask to check the final number of used
// registers.
unsigned LastUndefsCnt = 0;
for (int I = 0, E = NewMask.size(); I < E; ++I) {
if (SM1[I] == PoisonMaskElem)
++LastUndefsCnt;
else
LastUndefsCnt = 0;
if (NewMask[I] != PoisonMaskElem && SM1[I] != PoisonMaskElem &&
NewMask[I] != SM1[I])
return false;
if (NewMask[I] == PoisonMaskElem)
NewMask[I] = SM1[I];
}
// Check if the last undefs actually change the final number of used vector
// registers.
return SM1.size() - LastUndefsCnt > 1 &&
TTI->getNumberOfParts(SI1->getType()) ==
TTI->getNumberOfParts(
FixedVectorType::get(SI1->getType()->getElementType(),
SM1.size() - LastUndefsCnt));
};
// Perform O(N^2) search over the gather/shuffle sequences and merge identical
// instructions. TODO: We can further optimize this scan if we split the
// instructions into different buckets based on the insert lane.
SmallVector<Instruction *, 16> Visited;
for (auto I = CSEWorkList.begin(), E = CSEWorkList.end(); I != E; ++I) {
assert(*I &&
(I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) &&
"Worklist not sorted properly!");
BasicBlock *BB = (*I)->getBlock();
// For all instructions in blocks containing gather sequences:
for (Instruction &In : llvm::make_early_inc_range(*BB)) {
if (isDeleted(&In))
continue;
if (!isa<InsertElementInst, ExtractElementInst, ShuffleVectorInst>(&In) &&
!GatherShuffleExtractSeq.contains(&In))
continue;
// Check if we can replace this instruction with any of the
// visited instructions.
bool Replaced = false;
for (Instruction *&V : Visited) {
SmallVector<int> NewMask;
if (IsIdenticalOrLessDefined(&In, V, NewMask) &&
DT->dominates(V->getParent(), In.getParent())) {
In.replaceAllUsesWith(V);
eraseInstruction(&In);
if (auto *SI = dyn_cast<ShuffleVectorInst>(V))
if (!NewMask.empty())
SI->setShuffleMask(NewMask);
Replaced = true;
break;
}
if (isa<ShuffleVectorInst>(In) && isa<ShuffleVectorInst>(V) &&
GatherShuffleExtractSeq.contains(V) &&
IsIdenticalOrLessDefined(V, &In, NewMask) &&
DT->dominates(In.getParent(), V->getParent())) {
In.moveAfter(V);
V->replaceAllUsesWith(&In);
eraseInstruction(V);
if (auto *SI = dyn_cast<ShuffleVectorInst>(&In))
if (!NewMask.empty())
SI->setShuffleMask(NewMask);
V = &In;
Replaced = true;
break;
}
}
if (!Replaced) {
assert(!is_contained(Visited, &In));
Visited.push_back(&In);
}
}
}
CSEBlocks.clear();
GatherShuffleExtractSeq.clear();
}
BoUpSLP::ScheduleData *
BoUpSLP::BlockScheduling::buildBundle(ArrayRef<Value *> VL) {
ScheduleData *Bundle = nullptr;
ScheduleData *PrevInBundle = nullptr;
for (Value *V : VL) {
if (doesNotNeedToBeScheduled(V))
continue;
ScheduleData *BundleMember = getScheduleData(V);
assert(BundleMember &&
"no ScheduleData for bundle member "
"(maybe not in same basic block)");
assert(BundleMember->isSchedulingEntity() &&
"bundle member already part of other bundle");
if (PrevInBundle) {
PrevInBundle->NextInBundle = BundleMember;
} else {
Bundle = BundleMember;
}
// Group the instructions to a bundle.
BundleMember->FirstInBundle = Bundle;
PrevInBundle = BundleMember;
}
assert(Bundle && "Failed to find schedule bundle");
return Bundle;
}
// Groups the instructions to a bundle (which is then a single scheduling entity)
// and schedules instructions until the bundle gets ready.
std::optional<BoUpSLP::ScheduleData *>
BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP,
const InstructionsState &S) {
// No need to schedule PHIs, insertelement, extractelement and extractvalue
// instructions.
if (isa<PHINode>(S.OpValue) || isVectorLikeInstWithConstOps(S.OpValue) ||
doesNotNeedToSchedule(VL))
return nullptr;
// Initialize the instruction bundle.
Instruction *OldScheduleEnd = ScheduleEnd;
LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n");
auto TryScheduleBundleImpl = [this, OldScheduleEnd, SLP](bool ReSchedule,
ScheduleData *Bundle) {
// The scheduling region got new instructions at the lower end (or it is a
// new region for the first bundle). This makes it necessary to
// recalculate all dependencies.
// It is seldom that this needs to be done a second time after adding the
// initial bundle to the region.
if (ScheduleEnd != OldScheduleEnd) {
for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode())
doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); });
ReSchedule = true;
}
if (Bundle) {
LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle
<< " in block " << BB->getName() << "\n");
calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP);
}
if (ReSchedule) {
resetSchedule();
initialFillReadyList(ReadyInsts);
}
// Now try to schedule the new bundle or (if no bundle) just calculate
// dependencies. As soon as the bundle is "ready" it means that there are no
// cyclic dependencies and we can schedule it. Note that's important that we
// don't "schedule" the bundle yet (see cancelScheduling).
while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) &&
!ReadyInsts.empty()) {
ScheduleData *Picked = ReadyInsts.pop_back_val();
assert(Picked->isSchedulingEntity() && Picked->isReady() &&
"must be ready to schedule");
schedule(Picked, ReadyInsts);
}
};
// Make sure that the scheduling region contains all
// instructions of the bundle.
for (Value *V : VL) {
if (doesNotNeedToBeScheduled(V))
continue;
if (!extendSchedulingRegion(V, S)) {
// If the scheduling region got new instructions at the lower end (or it
// is a new region for the first bundle). This makes it necessary to
// recalculate all dependencies.
// Otherwise the compiler may crash trying to incorrectly calculate
// dependencies and emit instruction in the wrong order at the actual
// scheduling.
TryScheduleBundleImpl(/*ReSchedule=*/false, nullptr);
return std::nullopt;
}
}
bool ReSchedule = false;
for (Value *V : VL) {
if (doesNotNeedToBeScheduled(V))
continue;
ScheduleData *BundleMember = getScheduleData(V);
assert(BundleMember &&
"no ScheduleData for bundle member (maybe not in same basic block)");
// Make sure we don't leave the pieces of the bundle in the ready list when
// whole bundle might not be ready.
ReadyInsts.remove(BundleMember);
if (!BundleMember->IsScheduled)
continue;
// A bundle member was scheduled as single instruction before and now
// needs to be scheduled as part of the bundle. We just get rid of the
// existing schedule.
LLVM_DEBUG(dbgs() << "SLP: reset schedule because " << *BundleMember
<< " was already scheduled\n");
ReSchedule = true;
}
auto *Bundle = buildBundle(VL);
TryScheduleBundleImpl(ReSchedule, Bundle);
if (!Bundle->isReady()) {
cancelScheduling(VL, S.OpValue);
return std::nullopt;
}
return Bundle;
}
void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL,
Value *OpValue) {
if (isa<PHINode>(OpValue) || isVectorLikeInstWithConstOps(OpValue) ||
doesNotNeedToSchedule(VL))
return;
if (doesNotNeedToBeScheduled(OpValue))
OpValue = *find_if_not(VL, doesNotNeedToBeScheduled);
ScheduleData *Bundle = getScheduleData(OpValue);
LLVM_DEBUG(dbgs() << "SLP: cancel scheduling of " << *Bundle << "\n");
assert(!Bundle->IsScheduled &&
"Can't cancel bundle which is already scheduled");
assert(Bundle->isSchedulingEntity() &&
(Bundle->isPartOfBundle() || needToScheduleSingleInstruction(VL)) &&
"tried to unbundle something which is not a bundle");
// Remove the bundle from the ready list.
if (Bundle->isReady())
ReadyInsts.remove(Bundle);
// Un-bundle: make single instructions out of the bundle.
ScheduleData *BundleMember = Bundle;
while (BundleMember) {
assert(BundleMember->FirstInBundle == Bundle && "corrupt bundle links");
BundleMember->FirstInBundle = BundleMember;
ScheduleData *Next = BundleMember->NextInBundle;
BundleMember->NextInBundle = nullptr;
BundleMember->TE = nullptr;
if (BundleMember->unscheduledDepsInBundle() == 0) {
ReadyInsts.insert(BundleMember);
}
BundleMember = Next;
}
}
BoUpSLP::ScheduleData *BoUpSLP::BlockScheduling::allocateScheduleDataChunks() {
// Allocate a new ScheduleData for the instruction.
if (ChunkPos >= ChunkSize) {
ScheduleDataChunks.push_back(std::make_unique<ScheduleData[]>(ChunkSize));
ChunkPos = 0;
}
return &(ScheduleDataChunks.back()[ChunkPos++]);
}
bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V,
const InstructionsState &S) {
if (getScheduleData(V, isOneOf(S, V)))
return true;
Instruction *I = dyn_cast<Instruction>(V);
assert(I && "bundle member must be an instruction");
assert(!isa<PHINode>(I) && !isVectorLikeInstWithConstOps(I) &&
!doesNotNeedToBeScheduled(I) &&
"phi nodes/insertelements/extractelements/extractvalues don't need to "
"be scheduled");
auto &&CheckScheduleForI = [this, &S](Instruction *I) -> bool {
ScheduleData *ISD = getScheduleData(I);
if (!ISD)
return false;
assert(isInSchedulingRegion(ISD) &&
"ScheduleData not in scheduling region");
ScheduleData *SD = allocateScheduleDataChunks();
SD->Inst = I;
SD->init(SchedulingRegionID, S.OpValue);
ExtraScheduleDataMap[I][S.OpValue] = SD;
return true;
};
if (CheckScheduleForI(I))
return true;
if (!ScheduleStart) {
// It's the first instruction in the new region.
initScheduleData(I, I->getNextNode(), nullptr, nullptr);
ScheduleStart = I;
ScheduleEnd = I->getNextNode();
if (isOneOf(S, I) != I)
CheckScheduleForI(I);
assert(ScheduleEnd && "tried to vectorize a terminator?");
LLVM_DEBUG(dbgs() << "SLP: initialize schedule region to " << *I << "\n");
return true;
}
// Search up and down at the same time, because we don't know if the new
// instruction is above or below the existing scheduling region.
BasicBlock::reverse_iterator UpIter =
++ScheduleStart->getIterator().getReverse();
BasicBlock::reverse_iterator UpperEnd = BB->rend();
BasicBlock::iterator DownIter = ScheduleEnd->getIterator();
BasicBlock::iterator LowerEnd = BB->end();
while (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I &&
&*DownIter != I) {
if (++ScheduleRegionSize > ScheduleRegionSizeLimit) {
LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n");
return false;
}
++UpIter;
++DownIter;
}
if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) {
assert(I->getParent() == ScheduleStart->getParent() &&
"Instruction is in wrong basic block.");
initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion);
ScheduleStart = I;
if (isOneOf(S, I) != I)
CheckScheduleForI(I);
LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I
<< "\n");
return true;
}
assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) &&
"Expected to reach top of the basic block or instruction down the "
"lower end.");
assert(I->getParent() == ScheduleEnd->getParent() &&
"Instruction is in wrong basic block.");
initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion,
nullptr);
ScheduleEnd = I->getNextNode();
if (isOneOf(S, I) != I)
CheckScheduleForI(I);
assert(ScheduleEnd && "tried to vectorize a terminator?");
LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n");
return true;
}
void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI,
Instruction *ToI,
ScheduleData *PrevLoadStore,
ScheduleData *NextLoadStore) {
ScheduleData *CurrentLoadStore = PrevLoadStore;
for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) {
// No need to allocate data for non-schedulable instructions.
if (doesNotNeedToBeScheduled(I))
continue;
ScheduleData *SD = ScheduleDataMap.lookup(I);
if (!SD) {
SD = allocateScheduleDataChunks();
ScheduleDataMap[I] = SD;
SD->Inst = I;
}
assert(!isInSchedulingRegion(SD) &&
"new ScheduleData already in scheduling region");
SD->init(SchedulingRegionID, I);
if (I->mayReadOrWriteMemory() &&
(!isa<IntrinsicInst>(I) ||
(cast<IntrinsicInst>(I)->getIntrinsicID() != Intrinsic::sideeffect &&
cast<IntrinsicInst>(I)->getIntrinsicID() !=
Intrinsic::pseudoprobe))) {
// Update the linked list of memory accessing instructions.
if (CurrentLoadStore) {
CurrentLoadStore->NextLoadStore = SD;
} else {
FirstLoadStoreInRegion = SD;
}
CurrentLoadStore = SD;
}
if (match(I, m_Intrinsic<Intrinsic::stacksave>()) ||
match(I, m_Intrinsic<Intrinsic::stackrestore>()))
RegionHasStackSave = true;
}
if (NextLoadStore) {
if (CurrentLoadStore)
CurrentLoadStore->NextLoadStore = NextLoadStore;
} else {
LastLoadStoreInRegion = CurrentLoadStore;
}
}
void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD,
bool InsertInReadyList,
BoUpSLP *SLP) {
assert(SD->isSchedulingEntity());
SmallVector<ScheduleData *, 10> WorkList;
WorkList.push_back(SD);
while (!WorkList.empty()) {
ScheduleData *SD = WorkList.pop_back_val();
for (ScheduleData *BundleMember = SD; BundleMember;
BundleMember = BundleMember->NextInBundle) {
assert(isInSchedulingRegion(BundleMember));
if (BundleMember->hasValidDependencies())
continue;
LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember
<< "\n");
BundleMember->Dependencies = 0;
BundleMember->resetUnscheduledDeps();
// Handle def-use chain dependencies.
if (BundleMember->OpValue != BundleMember->Inst) {
if (ScheduleData *UseSD = getScheduleData(BundleMember->Inst)) {
BundleMember->Dependencies++;
ScheduleData *DestBundle = UseSD->FirstInBundle;
if (!DestBundle->IsScheduled)
BundleMember->incrementUnscheduledDeps(1);
if (!DestBundle->hasValidDependencies())
WorkList.push_back(DestBundle);
}
} else {
for (User *U : BundleMember->Inst->users()) {
if (ScheduleData *UseSD = getScheduleData(cast<Instruction>(U))) {
BundleMember->Dependencies++;
ScheduleData *DestBundle = UseSD->FirstInBundle;
if (!DestBundle->IsScheduled)
BundleMember->incrementUnscheduledDeps(1);
if (!DestBundle->hasValidDependencies())
WorkList.push_back(DestBundle);
}
}
}
auto makeControlDependent = [&](Instruction *I) {
auto *DepDest = getScheduleData(I);
assert(DepDest && "must be in schedule window");
DepDest->ControlDependencies.push_back(BundleMember);
BundleMember->Dependencies++;
ScheduleData *DestBundle = DepDest->FirstInBundle;
if (!DestBundle->IsScheduled)
BundleMember->incrementUnscheduledDeps(1);
if (!DestBundle->hasValidDependencies())
WorkList.push_back(DestBundle);
};
// Any instruction which isn't safe to speculate at the beginning of the
// block is control dependend on any early exit or non-willreturn call
// which proceeds it.
if (!isGuaranteedToTransferExecutionToSuccessor(BundleMember->Inst)) {
for (Instruction *I = BundleMember->Inst->getNextNode();
I != ScheduleEnd; I = I->getNextNode()) {
if (isSafeToSpeculativelyExecute(I, &*BB->begin(), SLP->AC))
continue;
// Add the dependency
makeControlDependent(I);
if (!isGuaranteedToTransferExecutionToSuccessor(I))
// Everything past here must be control dependent on I.
break;
}
}
if (RegionHasStackSave) {
// If we have an inalloc alloca instruction, it needs to be scheduled
// after any preceeding stacksave. We also need to prevent any alloca
// from reordering above a preceeding stackrestore.
if (match(BundleMember->Inst, m_Intrinsic<Intrinsic::stacksave>()) ||
match(BundleMember->Inst, m_Intrinsic<Intrinsic::stackrestore>())) {
for (Instruction *I = BundleMember->Inst->getNextNode();
I != ScheduleEnd; I = I->getNextNode()) {
if (match(I, m_Intrinsic<Intrinsic::stacksave>()) ||
match(I, m_Intrinsic<Intrinsic::stackrestore>()))
// Any allocas past here must be control dependent on I, and I
// must be memory dependend on BundleMember->Inst.
break;
if (!isa<AllocaInst>(I))
continue;
// Add the dependency
makeControlDependent(I);
}
}
// In addition to the cases handle just above, we need to prevent
// allocas and loads/stores from moving below a stacksave or a
// stackrestore. Avoiding moving allocas below stackrestore is currently
// thought to be conservatism. Moving loads/stores below a stackrestore
// can lead to incorrect code.
if (isa<AllocaInst>(BundleMember->Inst) ||
BundleMember->Inst->mayReadOrWriteMemory()) {
for (Instruction *I = BundleMember->Inst->getNextNode();
I != ScheduleEnd; I = I->getNextNode()) {
if (!match(I, m_Intrinsic<Intrinsic::stacksave>()) &&
!match(I, m_Intrinsic<Intrinsic::stackrestore>()))
continue;
// Add the dependency
makeControlDependent(I);
break;
}
}
}
// Handle the memory dependencies (if any).
ScheduleData *DepDest = BundleMember->NextLoadStore;
if (!DepDest)
continue;
Instruction *SrcInst = BundleMember->Inst;
assert(SrcInst->mayReadOrWriteMemory() &&
"NextLoadStore list for non memory effecting bundle?");
MemoryLocation SrcLoc = getLocation(SrcInst);
bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory();
unsigned numAliased = 0;
unsigned DistToSrc = 1;
for ( ; DepDest; DepDest = DepDest->NextLoadStore) {
assert(isInSchedulingRegion(DepDest));
// We have two limits to reduce the complexity:
// 1) AliasedCheckLimit: It's a small limit to reduce calls to
// SLP->isAliased (which is the expensive part in this loop).
// 2) MaxMemDepDistance: It's for very large blocks and it aborts
// the whole loop (even if the loop is fast, it's quadratic).
// It's important for the loop break condition (see below) to
// check this limit even between two read-only instructions.
if (DistToSrc >= MaxMemDepDistance ||
((SrcMayWrite || DepDest->Inst->mayWriteToMemory()) &&
(numAliased >= AliasedCheckLimit ||
SLP->isAliased(SrcLoc, SrcInst, DepDest->Inst)))) {
// We increment the counter only if the locations are aliased
// (instead of counting all alias checks). This gives a better
// balance between reduced runtime and accurate dependencies.
numAliased++;
DepDest->MemoryDependencies.push_back(BundleMember);
BundleMember->Dependencies++;
ScheduleData *DestBundle = DepDest->FirstInBundle;
if (!DestBundle->IsScheduled) {
BundleMember->incrementUnscheduledDeps(1);
}
if (!DestBundle->hasValidDependencies()) {
WorkList.push_back(DestBundle);
}
}
// Example, explaining the loop break condition: Let's assume our
// starting instruction is i0 and MaxMemDepDistance = 3.
//
// +--------v--v--v
// i0,i1,i2,i3,i4,i5,i6,i7,i8
// +--------^--^--^
//
// MaxMemDepDistance let us stop alias-checking at i3 and we add
// dependencies from i0 to i3,i4,.. (even if they are not aliased).
// Previously we already added dependencies from i3 to i6,i7,i8
// (because of MaxMemDepDistance). As we added a dependency from
// i0 to i3, we have transitive dependencies from i0 to i6,i7,i8
// and we can abort this loop at i6.
if (DistToSrc >= 2 * MaxMemDepDistance)
break;
DistToSrc++;
}
}
if (InsertInReadyList && SD->isReady()) {
ReadyInsts.insert(SD);
LLVM_DEBUG(dbgs() << "SLP: gets ready on update: " << *SD->Inst
<< "\n");
}
}
}
void BoUpSLP::BlockScheduling::resetSchedule() {
assert(ScheduleStart &&
"tried to reset schedule on block which has not been scheduled");
for (Instruction *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) {
doForAllOpcodes(I, [&](ScheduleData *SD) {
assert(isInSchedulingRegion(SD) &&
"ScheduleData not in scheduling region");
SD->IsScheduled = false;
SD->resetUnscheduledDeps();
});
}
ReadyInsts.clear();
}
void BoUpSLP::scheduleBlock(BlockScheduling *BS) {
if (!BS->ScheduleStart)
return;
LLVM_DEBUG(dbgs() << "SLP: schedule block " << BS->BB->getName() << "\n");
// A key point - if we got here, pre-scheduling was able to find a valid
// scheduling of the sub-graph of the scheduling window which consists
// of all vector bundles and their transitive users. As such, we do not
// need to reschedule anything *outside of* that subgraph.
BS->resetSchedule();
// For the real scheduling we use a more sophisticated ready-list: it is
// sorted by the original instruction location. This lets the final schedule
// be as close as possible to the original instruction order.
// WARNING: If changing this order causes a correctness issue, that means
// there is some missing dependence edge in the schedule data graph.
struct ScheduleDataCompare {
bool operator()(ScheduleData *SD1, ScheduleData *SD2) const {
return SD2->SchedulingPriority < SD1->SchedulingPriority;
}
};
std::set<ScheduleData *, ScheduleDataCompare> ReadyInsts;
// Ensure that all dependency data is updated (for nodes in the sub-graph)
// and fill the ready-list with initial instructions.
int Idx = 0;
for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd;
I = I->getNextNode()) {
BS->doForAllOpcodes(I, [this, &Idx, BS](ScheduleData *SD) {
TreeEntry *SDTE = getTreeEntry(SD->Inst);
(void)SDTE;
assert((isVectorLikeInstWithConstOps(SD->Inst) ||
SD->isPartOfBundle() ==
(SDTE && !doesNotNeedToSchedule(SDTE->Scalars))) &&
"scheduler and vectorizer bundle mismatch");
SD->FirstInBundle->SchedulingPriority = Idx++;
if (SD->isSchedulingEntity() && SD->isPartOfBundle())
BS->calculateDependencies(SD, false, this);
});
}
BS->initialFillReadyList(ReadyInsts);
Instruction *LastScheduledInst = BS->ScheduleEnd;
// Do the "real" scheduling.
while (!ReadyInsts.empty()) {
ScheduleData *picked = *ReadyInsts.begin();
ReadyInsts.erase(ReadyInsts.begin());
// Move the scheduled instruction(s) to their dedicated places, if not
// there yet.
for (ScheduleData *BundleMember = picked; BundleMember;
BundleMember = BundleMember->NextInBundle) {
Instruction *pickedInst = BundleMember->Inst;
if (pickedInst->getNextNode() != LastScheduledInst)
pickedInst->moveBefore(LastScheduledInst);
LastScheduledInst = pickedInst;
}
BS->schedule(picked, ReadyInsts);
}
// Check that we didn't break any of our invariants.
#ifdef EXPENSIVE_CHECKS
BS->verify();
#endif
#if !defined(NDEBUG) || defined(EXPENSIVE_CHECKS)
// Check that all schedulable entities got scheduled
for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd; I = I->getNextNode()) {
BS->doForAllOpcodes(I, [&](ScheduleData *SD) {
if (SD->isSchedulingEntity() && SD->hasValidDependencies()) {
assert(SD->IsScheduled && "must be scheduled at this point");
}
});
}
#endif
// Avoid duplicate scheduling of the block.
BS->ScheduleStart = nullptr;
}
unsigned BoUpSLP::getVectorElementSize(Value *V) {
// If V is a store, just return the width of the stored value (or value
// truncated just before storing) without traversing the expression tree.
// This is the common case.
if (auto *Store = dyn_cast<StoreInst>(V))
return DL->getTypeSizeInBits(Store->getValueOperand()->getType());
if (auto *IEI = dyn_cast<InsertElementInst>(V))
return getVectorElementSize(IEI->getOperand(1));
auto E = InstrElementSize.find(V);
if (E != InstrElementSize.end())
return E->second;
// If V is not a store, we can traverse the expression tree to find loads
// that feed it. The type of the loaded value may indicate a more suitable
// width than V's type. We want to base the vector element size on the width
// of memory operations where possible.
SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist;
SmallPtrSet<Instruction *, 16> Visited;
if (auto *I = dyn_cast<Instruction>(V)) {
Worklist.emplace_back(I, I->getParent());
Visited.insert(I);
}
// Traverse the expression tree in bottom-up order looking for loads. If we
// encounter an instruction we don't yet handle, we give up.
auto Width = 0u;
while (!Worklist.empty()) {
Instruction *I;
BasicBlock *Parent;
std::tie(I, Parent) = Worklist.pop_back_val();
// We should only be looking at scalar instructions here. If the current
// instruction has a vector type, skip.
auto *Ty = I->getType();
if (isa<VectorType>(Ty))
continue;
// If the current instruction is a load, update MaxWidth to reflect the
// width of the loaded value.
if (isa<LoadInst, ExtractElementInst, ExtractValueInst>(I))
Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty));
// Otherwise, we need to visit the operands of the instruction. We only
// handle the interesting cases from buildTree here. If an operand is an
// instruction we haven't yet visited and from the same basic block as the
// user or the use is a PHI node, we add it to the worklist.
else if (isa<PHINode, CastInst, GetElementPtrInst, CmpInst, SelectInst,
BinaryOperator, UnaryOperator>(I)) {
for (Use &U : I->operands())
if (auto *J = dyn_cast<Instruction>(U.get()))
if (Visited.insert(J).second &&
(isa<PHINode>(I) || J->getParent() == Parent))
Worklist.emplace_back(J, J->getParent());
} else {
break;
}
}
// If we didn't encounter a memory access in the expression tree, or if we
// gave up for some reason, just return the width of V. Otherwise, return the
// maximum width we found.
if (!Width) {
if (auto *CI = dyn_cast<CmpInst>(V))
V = CI->getOperand(0);
Width = DL->getTypeSizeInBits(V->getType());
}
for (Instruction *I : Visited)
InstrElementSize[I] = Width;
return Width;
}
// Determine if a value V in a vectorizable expression Expr can be demoted to a
// smaller type with a truncation. We collect the values that will be demoted
// in ToDemote and additional roots that require investigating in Roots.
static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr,
SmallVectorImpl<Value *> &ToDemote,
SmallVectorImpl<Value *> &Roots) {
// We can always demote constants.
if (isa<Constant>(V)) {
ToDemote.push_back(V);
return true;
}
// If the value is not an instruction in the expression with only one use, it
// cannot be demoted.
auto *I = dyn_cast<Instruction>(V);
if (!I || !I->hasOneUse() || !Expr.count(I))
return false;
switch (I->getOpcode()) {
// We can always demote truncations and extensions. Since truncations can
// seed additional demotion, we save the truncated value.
case Instruction::Trunc:
Roots.push_back(I->getOperand(0));
break;
case Instruction::ZExt:
case Instruction::SExt:
if (isa<ExtractElementInst, InsertElementInst>(I->getOperand(0)))
return false;
break;
// We can demote certain binary operations if we can demote both of their
// operands.
case Instruction::Add:
case Instruction::Sub:
case Instruction::Mul:
case Instruction::And:
case Instruction::Or:
case Instruction::Xor:
if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) ||
!collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots))
return false;
break;
// We can demote selects if we can demote their true and false values.
case Instruction::Select: {
SelectInst *SI = cast<SelectInst>(I);
if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) ||
!collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots))
return false;
break;
}
// We can demote phis if we can demote all their incoming operands. Note that
// we don't need to worry about cycles since we ensure single use above.
case Instruction::PHI: {
PHINode *PN = cast<PHINode>(I);
for (Value *IncValue : PN->incoming_values())
if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots))
return false;
break;
}
// Otherwise, conservatively give up.
default:
return false;
}
// Record the value that we can demote.
ToDemote.push_back(V);
return true;
}
void BoUpSLP::computeMinimumValueSizes() {
// If there are no external uses, the expression tree must be rooted by a
// store. We can't demote in-memory values, so there is nothing to do here.
if (ExternalUses.empty())
return;
// We only attempt to truncate integer expressions.
auto &TreeRoot = VectorizableTree[0]->Scalars;
auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType());
if (!TreeRootIT)
return;
// If the expression is not rooted by a store, these roots should have
// external uses. We will rely on InstCombine to rewrite the expression in
// the narrower type. However, InstCombine only rewrites single-use values.
// This means that if a tree entry other than a root is used externally, it
// must have multiple uses and InstCombine will not rewrite it. The code
// below ensures that only the roots are used externally.
SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end());
for (auto &EU : ExternalUses)
if (!Expr.erase(EU.Scalar))
return;
if (!Expr.empty())
return;
// Collect the scalar values of the vectorizable expression. We will use this
// context to determine which values can be demoted. If we see a truncation,
// we mark it as seeding another demotion.
for (auto &EntryPtr : VectorizableTree)
Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end());
// Ensure the roots of the vectorizable tree don't form a cycle. They must
// have a single external user that is not in the vectorizable tree.
for (auto *Root : TreeRoot)
if (!Root->hasOneUse() || Expr.count(*Root->user_begin()))
return;
// Conservatively determine if we can actually truncate the roots of the
// expression. Collect the values that can be demoted in ToDemote and
// additional roots that require investigating in Roots.
SmallVector<Value *, 32> ToDemote;
SmallVector<Value *, 4> Roots;
for (auto *Root : TreeRoot)
if (!collectValuesToDemote(Root, Expr, ToDemote, Roots))
return;
// The maximum bit width required to represent all the values that can be
// demoted without loss of precision. It would be safe to truncate the roots
// of the expression to this width.
auto MaxBitWidth = 8u;
// We first check if all the bits of the roots are demanded. If they're not,
// we can truncate the roots to this narrower type.
for (auto *Root : TreeRoot) {
auto Mask = DB->getDemandedBits(cast<Instruction>(Root));
MaxBitWidth = std::max<unsigned>(Mask.getBitWidth() - Mask.countl_zero(),
MaxBitWidth);
}
// True if the roots can be zero-extended back to their original type, rather
// than sign-extended. We know that if the leading bits are not demanded, we
// can safely zero-extend. So we initialize IsKnownPositive to True.
bool IsKnownPositive = true;
// If all the bits of the roots are demanded, we can try a little harder to
// compute a narrower type. This can happen, for example, if the roots are
// getelementptr indices. InstCombine promotes these indices to the pointer
// width. Thus, all their bits are technically demanded even though the
// address computation might be vectorized in a smaller type.
//
// We start by looking at each entry that can be demoted. We compute the
// maximum bit width required to store the scalar by using ValueTracking to
// compute the number of high-order bits we can truncate.
if (MaxBitWidth == DL->getTypeSizeInBits(TreeRoot[0]->getType()) &&
llvm::all_of(TreeRoot, [](Value *R) {
assert(R->hasOneUse() && "Root should have only one use!");
return isa<GetElementPtrInst>(R->user_back());
})) {
MaxBitWidth = 8u;
// Determine if the sign bit of all the roots is known to be zero. If not,
// IsKnownPositive is set to False.
IsKnownPositive = llvm::all_of(TreeRoot, [&](Value *R) {
KnownBits Known = computeKnownBits(R, *DL);
return Known.isNonNegative();
});
// Determine the maximum number of bits required to store the scalar
// values.
for (auto *Scalar : ToDemote) {
auto NumSignBits = ComputeNumSignBits(Scalar, *DL, 0, AC, nullptr, DT);
auto NumTypeBits = DL->getTypeSizeInBits(Scalar->getType());
MaxBitWidth = std::max<unsigned>(NumTypeBits - NumSignBits, MaxBitWidth);
}
// If we can't prove that the sign bit is zero, we must add one to the
// maximum bit width to account for the unknown sign bit. This preserves
// the existing sign bit so we can safely sign-extend the root back to the
// original type. Otherwise, if we know the sign bit is zero, we will
// zero-extend the root instead.
//
// FIXME: This is somewhat suboptimal, as there will be cases where adding
// one to the maximum bit width will yield a larger-than-necessary
// type. In general, we need to add an extra bit only if we can't
// prove that the upper bit of the original type is equal to the
// upper bit of the proposed smaller type. If these two bits are the
// same (either zero or one) we know that sign-extending from the
// smaller type will result in the same value. Here, since we can't
// yet prove this, we are just making the proposed smaller type
// larger to ensure correctness.
if (!IsKnownPositive)
++MaxBitWidth;
}
// Round MaxBitWidth up to the next power-of-two.
MaxBitWidth = llvm::bit_ceil(MaxBitWidth);
// If the maximum bit width we compute is less than the with of the roots'
// type, we can proceed with the narrowing. Otherwise, do nothing.
if (MaxBitWidth >= TreeRootIT->getBitWidth())
return;
// If we can truncate the root, we must collect additional values that might
// be demoted as a result. That is, those seeded by truncations we will
// modify.
while (!Roots.empty())
collectValuesToDemote(Roots.pop_back_val(), Expr, ToDemote, Roots);
// Finally, map the values we can demote to the maximum bit with we computed.
for (auto *Scalar : ToDemote)
MinBWs[Scalar] = std::make_pair(MaxBitWidth, !IsKnownPositive);
}
PreservedAnalyses SLPVectorizerPass::run(Function &F, FunctionAnalysisManager &AM) {
auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F);
auto *TTI = &AM.getResult<TargetIRAnalysis>(F);
auto *TLI = AM.getCachedResult<TargetLibraryAnalysis>(F);
auto *AA = &AM.getResult<AAManager>(F);
auto *LI = &AM.getResult<LoopAnalysis>(F);
auto *DT = &AM.getResult<DominatorTreeAnalysis>(F);
auto *AC = &AM.getResult<AssumptionAnalysis>(F);
auto *DB = &AM.getResult<DemandedBitsAnalysis>(F);
auto *ORE = &AM.getResult<OptimizationRemarkEmitterAnalysis>(F);
bool Changed = runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE);
if (!Changed)
return PreservedAnalyses::all();
PreservedAnalyses PA;
PA.preserveSet<CFGAnalyses>();
return PA;
}
bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_,
TargetTransformInfo *TTI_,
TargetLibraryInfo *TLI_, AAResults *AA_,
LoopInfo *LI_, DominatorTree *DT_,
AssumptionCache *AC_, DemandedBits *DB_,
OptimizationRemarkEmitter *ORE_) {
if (!RunSLPVectorization)
return false;
SE = SE_;
TTI = TTI_;
TLI = TLI_;
AA = AA_;
LI = LI_;
DT = DT_;
AC = AC_;
DB = DB_;
DL = &F.getParent()->getDataLayout();
Stores.clear();
GEPs.clear();
bool Changed = false;
// If the target claims to have no vector registers don't attempt
// vectorization.
if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) {
LLVM_DEBUG(
dbgs() << "SLP: Didn't find any vector registers for target, abort.\n");
return false;
}
// Don't vectorize when the attribute NoImplicitFloat is used.
if (F.hasFnAttribute(Attribute::NoImplicitFloat))
return false;
LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n");
// Use the bottom up slp vectorizer to construct chains that start with
// store instructions.
BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_);
// A general note: the vectorizer must use BoUpSLP::eraseInstruction() to
// delete instructions.
// Update DFS numbers now so that we can use them for ordering.
DT->updateDFSNumbers();
// Scan the blocks in the function in post order.
for (auto *BB : post_order(&F.getEntryBlock())) {
// Start new block - clear the list of reduction roots.
R.clearReductionData();
collectSeedInstructions(BB);
// Vectorize trees that end at stores.
if (!Stores.empty()) {
LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size()
<< " underlying objects.\n");
Changed |= vectorizeStoreChains(R);
}
// Vectorize trees that end at reductions.
Changed |= vectorizeChainsInBlock(BB, R);
// Vectorize the index computations of getelementptr instructions. This
// is primarily intended to catch gather-like idioms ending at
// non-consecutive loads.
if (!GEPs.empty()) {
LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size()
<< " underlying objects.\n");
Changed |= vectorizeGEPIndices(BB, R);
}
}
if (Changed) {
R.optimizeGatherSequence();
LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n");
}
return Changed;
}
bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R,
unsigned Idx, unsigned MinVF) {
LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size()
<< "\n");
const unsigned Sz = R.getVectorElementSize(Chain[0]);
unsigned VF = Chain.size();
if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF)
return false;
LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx
<< "\n");
R.buildTree(Chain);
if (R.isTreeTinyAndNotFullyVectorizable())
return false;
if (R.isLoadCombineCandidate())
return false;
R.reorderTopToBottom();
R.reorderBottomToTop();
R.buildExternalUses();
R.computeMinimumValueSizes();
InstructionCost Cost = R.getTreeCost();
LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF=" << VF << "\n");
if (Cost < -SLPCostThreshold) {
LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n");
using namespace ore;
R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized",
cast<StoreInst>(Chain[0]))
<< "Stores SLP vectorized with cost " << NV("Cost", Cost)
<< " and with tree size "
<< NV("TreeSize", R.getTreeSize()));
R.vectorizeTree();
return true;
}
return false;
}
bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores,
BoUpSLP &R) {
// We may run into multiple chains that merge into a single chain. We mark the
// stores that we vectorized so that we don't visit the same store twice.
BoUpSLP::ValueSet VectorizedStores;
bool Changed = false;
int E = Stores.size();
SmallBitVector Tails(E, false);
int MaxIter = MaxStoreLookup.getValue();
SmallVector<std::pair<int, int>, 16> ConsecutiveChain(
E, std::make_pair(E, INT_MAX));
SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false));
int IterCnt;
auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter,
&CheckedPairs,
&ConsecutiveChain](int K, int Idx) {
if (IterCnt >= MaxIter)
return true;
if (CheckedPairs[Idx].test(K))
return ConsecutiveChain[K].second == 1 &&
ConsecutiveChain[K].first == Idx;
++IterCnt;
CheckedPairs[Idx].set(K);
CheckedPairs[K].set(Idx);
std::optional<int> Diff = getPointersDiff(
Stores[K]->getValueOperand()->getType(), Stores[K]->getPointerOperand(),
Stores[Idx]->getValueOperand()->getType(),
Stores[Idx]->getPointerOperand(), *DL, *SE, /*StrictCheck=*/true);
if (!Diff || *Diff == 0)
return false;
int Val = *Diff;
if (Val < 0) {
if (ConsecutiveChain[Idx].second > -Val) {
Tails.set(K);
ConsecutiveChain[Idx] = std::make_pair(K, -Val);
}
return false;
}
if (ConsecutiveChain[K].second <= Val)
return false;
Tails.set(Idx);
ConsecutiveChain[K] = std::make_pair(Idx, Val);
return Val == 1;
};
// Do a quadratic search on all of the given stores in reverse order and find
// all of the pairs of stores that follow each other.
for (int Idx = E - 1; Idx >= 0; --Idx) {
// If a store has multiple consecutive store candidates, search according
// to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ...
// This is because usually pairing with immediate succeeding or preceding
// candidate create the best chance to find slp vectorization opportunity.
const int MaxLookDepth = std::max(E - Idx, Idx + 1);
IterCnt = 0;
for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset)
if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) ||
(Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx)))
break;
}
// Tracks if we tried to vectorize stores starting from the given tail
// already.
SmallBitVector TriedTails(E, false);
// For stores that start but don't end a link in the chain:
for (int Cnt = E; Cnt > 0; --Cnt) {
int I = Cnt - 1;
if (ConsecutiveChain[I].first == E || Tails.test(I))
continue;
// We found a store instr that starts a chain. Now follow the chain and try
// to vectorize it.
BoUpSLP::ValueList Operands;
// Collect the chain into a list.
while (I != E && !VectorizedStores.count(Stores[I])) {
Operands.push_back(Stores[I]);
Tails.set(I);
if (ConsecutiveChain[I].second != 1) {
// Mark the new end in the chain and go back, if required. It might be
// required if the original stores come in reversed order, for example.
if (ConsecutiveChain[I].first != E &&
Tails.test(ConsecutiveChain[I].first) && !TriedTails.test(I) &&
!VectorizedStores.count(Stores[ConsecutiveChain[I].first])) {
TriedTails.set(I);
Tails.reset(ConsecutiveChain[I].first);
if (Cnt < ConsecutiveChain[I].first + 2)
Cnt = ConsecutiveChain[I].first + 2;
}
break;
}
// Move to the next value in the chain.
I = ConsecutiveChain[I].first;
}
assert(!Operands.empty() && "Expected non-empty list of stores.");
unsigned MaxVecRegSize = R.getMaxVecRegSize();
unsigned EltSize = R.getVectorElementSize(Operands[0]);
unsigned MaxElts = llvm::bit_floor(MaxVecRegSize / EltSize);
unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store),
MaxElts);
auto *Store = cast<StoreInst>(Operands[0]);
Type *StoreTy = Store->getValueOperand()->getType();
Type *ValueTy = StoreTy;
if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand()))
ValueTy = Trunc->getSrcTy();
unsigned MinVF = TTI->getStoreMinimumVF(
R.getMinVF(DL->getTypeSizeInBits(ValueTy)), StoreTy, ValueTy);
if (MaxVF <= MinVF) {
LLVM_DEBUG(dbgs() << "SLP: Vectorization infeasible as MaxVF (" << MaxVF << ") <= "
<< "MinVF (" << MinVF << ")\n");
}
// FIXME: Is division-by-2 the correct step? Should we assert that the
// register size is a power-of-2?
unsigned StartIdx = 0;
for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) {
for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) {
ArrayRef<Value *> Slice = ArrayRef(Operands).slice(Cnt, Size);
if (!VectorizedStores.count(Slice.front()) &&
!VectorizedStores.count(Slice.back()) &&
vectorizeStoreChain(Slice, R, Cnt, MinVF)) {
// Mark the vectorized stores so that we don't vectorize them again.
VectorizedStores.insert(Slice.begin(), Slice.end());
Changed = true;
// If we vectorized initial block, no need to try to vectorize it
// again.
if (Cnt == StartIdx)
StartIdx += Size;
Cnt += Size;
continue;
}
++Cnt;
}
// Check if the whole array was vectorized already - exit.
if (StartIdx >= Operands.size())
break;
}
}
return Changed;
}
void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) {
// Initialize the collections. We will make a single pass over the block.
Stores.clear();
GEPs.clear();
// Visit the store and getelementptr instructions in BB and organize them in
// Stores and GEPs according to the underlying objects of their pointer
// operands.
for (Instruction &I : *BB) {
// Ignore store instructions that are volatile or have a pointer operand
// that doesn't point to a scalar type.
if (auto *SI = dyn_cast<StoreInst>(&I)) {
if (!SI->isSimple())
continue;
if (!isValidElementType(SI->getValueOperand()->getType()))
continue;
Stores[getUnderlyingObject(SI->getPointerOperand())].<