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llvm / llvm / 6f3ed8cfcfac6d09a12cc6dee00c772bf8600e5a / . / 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/ArrayRef.h"
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/DenseSet.h"
#include "llvm/ADT/MapVector.h"
#include "llvm/ADT/None.h"
#include "llvm/ADT/Optional.h"
#include "llvm/ADT/PostOrderIterator.h"
#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/SmallPtrSet.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/SmallVector.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/CodeMetrics.h"
#include "llvm/Analysis/DemandedBits.h"
#include "llvm/Analysis/GlobalsModRef.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/DebugLoc.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/NoFolder.h"
#include "llvm/IR/Operator.h"
#include "llvm/IR/PassManager.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"
#include "llvm/IR/Verifier.h"
#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/KnownBits.h"
#include "llvm/Support/MathExtras.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Utils/LoopUtils.h"
#include "llvm/Transforms/Vectorize.h"
#include <algorithm>
#include <cassert>
#include <cstdint>
#include <iterator>
#include <memory>
#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");
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"));
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"));
/// 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"));
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 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;
BasicBlock *BB = I0->getParent();
for (int i = 1, e = VL.size(); i < e; i++) {
Instruction *I = dyn_cast<Instruction>(VL[i]);
if (!I)
return false;
if (BB != I->getParent())
return false;
}
return true;
}
/// \returns True if all of the values in \p VL are constants.
static bool allConstant(ArrayRef<Value *> VL) {
for (Value *i : VL)
if (!isa<Constant>(i))
return false;
return true;
}
/// \returns True if all of the values in \p VL are identical.
static bool isSplat(ArrayRef<Value *> VL) {
for (unsigned i = 1, e = VL.size(); i < e; ++i)
if (VL[i] != VL[0])
return false;
return true;
}
/// 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> undef, 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> undef, 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> undef, 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
/// TODO: Can we split off and reuse the shuffle mask detection from
/// TargetTransformInfo::getInstructionThroughput?
static Optional<TargetTransformInfo::ShuffleKind>
isShuffle(ArrayRef<Value *> VL) {
auto *EI0 = cast<ExtractElementInst>(VL[0]);
unsigned Size = EI0->getVectorOperandType()->getVectorNumElements();
Value *Vec1 = nullptr;
Value *Vec2 = nullptr;
enum ShuffleMode { Unknown, Select, Permute };
ShuffleMode CommonShuffleMode = Unknown;
for (unsigned I = 0, E = VL.size(); I < E; ++I) {
auto *EI = cast<ExtractElementInst>(VL[I]);
auto *Vec = EI->getVectorOperand();
// All vector operands must have the same number of vector elements.
if (Vec->getType()->getVectorNumElements() != Size)
return None;
auto *Idx = dyn_cast<ConstantInt>(EI->getIndexOperand());
if (!Idx)
return None;
// Undefined behavior if Idx is negative or >= Size.
if (Idx->getValue().uge(Size))
continue;
unsigned IntIdx = Idx->getValue().getZExtValue();
// We can extractelement from undef vector.
if (isa<UndefValue>(Vec))
continue;
// 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;
else
return None;
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;
}
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 getOpcode() != getAltOpcode(); }
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 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,
unsigned BaseIndex = 0) {
// 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]);
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.).
for (int Cnt = 0, E = VL.size(); Cnt < E; Cnt++) {
unsigned InstOpcode = cast<Instruction>(VL[Cnt])->getOpcode();
if (IsBinOp && isa<BinaryOperator>(VL[Cnt])) {
if (InstOpcode == Opcode || InstOpcode == AltOpcode)
continue;
if (Opcode == AltOpcode) {
AltOpcode = InstOpcode;
AltIndex = Cnt;
continue;
}
} else if (IsCastOp && isa<CastInst>(VL[Cnt])) {
Type *Ty0 = cast<Instruction>(VL[BaseIndex])->getOperand(0)->getType();
Type *Ty1 = cast<Instruction>(VL[Cnt])->getOperand(0)->getType();
if (Ty0 == Ty1) {
if (InstOpcode == Opcode || InstOpcode == AltOpcode)
continue;
if (Opcode == AltOpcode) {
AltOpcode = InstOpcode;
AltIndex = Cnt;
continue;
}
}
} else if (InstOpcode == Opcode || InstOpcode == AltOpcode)
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 Extract{Value,Element} instruction extracts element Idx.
static 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 None;
return CI->getZExtValue();
}
ExtractValueInst *EI = cast<ExtractValueInst>(E);
if (EI->getNumIndices() != 1)
return None;
return *EI->idx_begin();
}
/// \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->getNumArgOperands(); i != e; ++i) {
if (hasVectorInstrinsicScalarOpd(ID, i))
return (CI->getArgOperand(i) == Scalar);
}
LLVM_FALLTHROUGH;
}
default:
return false;
}
}
/// \returns the AA location that is being access by the instruction.
static MemoryLocation getLocation(Instruction *I, AliasAnalysis *AA) {
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;
}
namespace llvm {
namespace slpvectorizer {
/// Bottom Up SLP Vectorizer.
class BoUpSLP {
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>>;
BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti,
TargetLibraryInfo *TLi, AliasAnalysis *Aa, LoopInfo *Li,
DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB,
const DataLayout *DL, OptimizationRemarkEmitter *ORE)
: F(Func), SE(Se), TTI(Tti), TLI(TLi), AA(Aa), 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(true);
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.
Value *vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues);
/// \returns the cost incurred by unwanted spills and fills, caused by
/// holding live values over call sites.
int getSpillCost();
/// \returns the vectorization cost of the subtree that starts at \p VL.
/// A negative number means that this is profitable.
int getTreeCost();
/// 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,
ArrayRef<Value *> UserIgnoreLst = None);
/// Construct a vectorizable tree that starts at \p Roots, ignoring users for
/// the purpose of scheduling and extraction in the \p UserIgnoreLst taking
/// into account (anf updating it, if required) list of externally used
/// values stored in \p ExternallyUsedValues.
void buildTree(ArrayRef<Value *> Roots,
ExtraValueToDebugLocsMap &ExternallyUsedValues,
ArrayRef<Value *> UserIgnoreLst = None);
/// Clear the internal data structures that are created by 'buildTree'.
void deleteTree() {
VectorizableTree.clear();
ScalarToTreeEntry.clear();
MustGather.clear();
ExternalUses.clear();
NumOpsWantToKeepOrder.clear();
NumOpsWantToKeepOriginalOrder = 0;
for (auto &Iter : BlocksSchedules) {
BlockScheduling *BS = Iter.second.get();
BS->clear();
}
MinBWs.clear();
}
unsigned getTreeSize() const { return VectorizableTree.size(); }
/// Perform LICM and CSE on the newly generated gather sequences.
void optimizeGatherSequence();
/// \returns The best order of instructions for vectorization.
Optional<ArrayRef<unsigned>> bestOrder() const {
auto I = std::max_element(
NumOpsWantToKeepOrder.begin(), NumOpsWantToKeepOrder.end(),
[](const decltype(NumOpsWantToKeepOrder)::value_type &D1,
const decltype(NumOpsWantToKeepOrder)::value_type &D2) {
return D1.second < D2.second;
});
if (I == NumOpsWantToKeepOrder.end() ||
I->getSecond() <= NumOpsWantToKeepOriginalOrder)
return None;
return makeArrayRef(I->getFirst());
}
/// \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;
}
/// Check if ArrayType or StructType is isomorphic to some VectorType.
///
/// \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();
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;
/// The index of the user TreeEntry in VectorizableTree.
int Idx = -1;
/// 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:" << Idx << " EdgeIdx:" << EdgeIdx << "}";
}
LLVM_DUMP_METHOD void dump() const { dump(dbgs()); }
#endif
};
private:
struct TreeEntry;
/// Checks if all users of \p I are the part of the vectorization tree.
bool areAllUsersVectorized(Instruction *I) const;
/// \returns the cost of the vectorizable entry.
int getEntryCost(TreeEntry *E);
/// This is the recursive part of buildTree.
void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, 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, starting in \p VL.
Value *vectorizeTree(ArrayRef<Value *> VL);
/// \returns the scalarization cost for this type. Scalarization in this
/// context means the creation of vectors from a group of scalars.
int getGatherCost(Type *Ty, const DenseSet<unsigned> &ShuffledIndices);
/// \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.
int getGatherCost(ArrayRef<Value *> VL);
/// Set the Builder insert point to one after the last instruction in
/// the bundle
void setInsertPointAfterBundle(ArrayRef<Value *> VL,
const InstructionsState &S);
/// \returns a vector from a collection of scalars in \p VL.
Value *Gather(ArrayRef<Value *> VL, VectorType *Ty);
/// \returns whether the VectorizableTree is fully vectorizable and will
/// be beneficial even the tree height is tiny.
bool isFullyVectorizableTinyTree();
/// \reorder commutative operands in alt shuffle if they result in
/// vectorized code.
void reorderAltShuffleOperands(const InstructionsState &S,
ArrayRef<Value *> VL,
SmallVectorImpl<Value *> &Left,
SmallVectorImpl<Value *> &Right);
/// \reorder commutative operands to get better probability of
/// generating vectorized code.
void reorderInputsAccordingToOpcode(const InstructionsState &S,
ArrayRef<Value *> VL,
SmallVectorImpl<Value *> &Left,
SmallVectorImpl<Value *> &Right);
struct TreeEntry {
TreeEntry(std::vector<TreeEntry> &Container) : Container(Container) {}
/// \returns true if the scalars in VL are equal to this entry.
bool isSame(ArrayRef<Value *> VL) const {
if (VL.size() == Scalars.size())
return std::equal(VL.begin(), VL.end(), Scalars.begin());
return VL.size() == ReuseShuffleIndices.size() &&
std::equal(
VL.begin(), VL.end(), ReuseShuffleIndices.begin(),
[this](Value *V, unsigned Idx) { return V == Scalars[Idx]; });
}
/// A vector of scalars.
ValueList Scalars;
/// The Scalars are vectorized into this value. It is initialized to Null.
Value *VectorizedValue = nullptr;
/// Do we need to gather this sequence ?
bool NeedToGather = false;
/// Does this sequence require some shuffling?
SmallVector<unsigned, 4> ReuseShuffleIndices;
/// Does this entry require reordering?
ArrayRef<unsigned> 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.
std::vector<TreeEntry> &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;
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;
public:
/// Set this bundle's \p OpIdx'th operand to \p OpVL.
void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL,
ArrayRef<unsigned> ReuseShuffleIndices) {
if (Operands.size() < OpIdx + 1)
Operands.resize(OpIdx + 1);
assert(Operands[OpIdx].size() == 0 && "Already resized?");
Operands[OpIdx].resize(Scalars.size());
for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane)
Operands[OpIdx][Lane] = (!ReuseShuffleIndices.empty())
? OpVL[ReuseShuffleIndices[Lane]]
: OpVL[Lane];
}
/// If there is a user TreeEntry, then set its operand.
void trySetUserTEOperand(const EdgeInfo &UserTreeIdx,
ArrayRef<Value *> OpVL,
ArrayRef<unsigned> ReuseShuffleIndices) {
if (UserTreeIdx.Idx >= 0) {
auto &VectorizableTree = Container;
VectorizableTree[UserTreeIdx.Idx].setOperand(UserTreeIdx.EdgeIdx, OpVL,
ReuseShuffleIndices);
}
}
/// \returns the \p OpIdx operand of this TreeEntry.
ValueList &getOperand(unsigned OpIdx) {
assert(OpIdx < Operands.size() && "Off bounds");
return Operands[OpIdx];
}
/// \return the single \p OpIdx operand.
Value *getSingleOperand(unsigned OpIdx) const {
assert(OpIdx < Operands.size() && "Off bounds");
assert(!Operands[OpIdx].empty() && "No operand availabe");
return Operands[OpIdx][0];
}
#ifndef NDEBUG
/// Debug printer.
LLVM_DUMP_METHOD void dump() const {
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() << "NeedToGather: " << NeedToGather << "\n";
dbgs() << "VectorizedValue: ";
if (VectorizedValue)
dbgs() << *VectorizedValue;
else
dbgs() << "NULL";
dbgs() << "\n";
dbgs() << "ReuseShuffleIndices: ";
if (ReuseShuffleIndices.empty())
dbgs() << "Emtpy";
else
for (unsigned Idx : ReuseShuffleIndices)
dbgs() << Idx << ", ";
dbgs() << "\n";
dbgs() << "ReorderIndices: ";
for (unsigned Idx : ReorderIndices)
dbgs() << Idx << ", ";
dbgs() << "\n";
dbgs() << "UserTreeIndices: ";
for (const auto &EInfo : UserTreeIndices)
dbgs() << EInfo << ", ";
dbgs() << "\n";
}
#endif
};
/// Create a new VectorizableTree entry.
void newTreeEntry(ArrayRef<Value *> VL, bool Vectorized,
EdgeInfo &UserTreeIdx,
ArrayRef<unsigned> ReuseShuffleIndices = None,
ArrayRef<unsigned> ReorderIndices = None) {
VectorizableTree.emplace_back(VectorizableTree);
int idx = VectorizableTree.size() - 1;
TreeEntry *Last = &VectorizableTree[idx];
Last->Scalars.insert(Last->Scalars.begin(), VL.begin(), VL.end());
Last->NeedToGather = !Vectorized;
Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(),
ReuseShuffleIndices.end());
Last->ReorderIndices = ReorderIndices;
if (Vectorized) {
for (int i = 0, e = VL.size(); i != e; ++i) {
assert(!getTreeEntry(VL[i]) && "Scalar already in tree!");
ScalarToTreeEntry[VL[i]] = idx;
}
} else {
MustGather.insert(VL.begin(), VL.end());
}
if (UserTreeIdx.Idx >= 0)
Last->UserTreeIndices.push_back(UserTreeIdx);
Last->trySetUserTEOperand(UserTreeIdx, VL, ReuseShuffleIndices);
UserTreeIdx.Idx = idx;
}
/// -- Vectorization State --
/// Holds all of the tree entries.
std::vector<TreeEntry> VectorizableTree;
#ifndef NDEBUG
/// Debug printer.
LLVM_DUMP_METHOD void dumpVectorizableTree() const {
for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) {
dbgs() << Id << ".\n";
VectorizableTree[Id].dump();
dbgs() << "\n";
}
}
#endif
TreeEntry *getTreeEntry(Value *V) {
auto I = ScalarToTreeEntry.find(V);
if (I != ScalarToTreeEntry.end())
return &VectorizableTree[I->second];
return nullptr;
}
/// Maps a specific scalar to its tree entry.
SmallDenseMap<Value*, int> ScalarToTreeEntry;
/// A list of scalars that we found that we need to keep as scalars.
ValueSet MustGather;
/// 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);
Optional<bool> &result = AliasCache[key];
if (result.hasValue()) {
return result.getValue();
}
MemoryLocation Loc2 = getLocation(Inst2, AA);
bool aliased = true;
if (Loc1.Ptr && Loc2.Ptr && isSimple(Inst1) && isSimple(Inst2)) {
// Do the alias check.
aliased = AA->alias(Loc1, Loc2);
}
// 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, Optional<bool>> AliasCache;
/// 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.
/// This 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.
void eraseInstruction(Instruction *I) {
I->removeFromParent();
I->dropAllReferences();
DeletedInstructions.emplace_back(I);
}
/// Temporary store for deleted instructions. Instructions will be deleted
/// eventually when the BoUpSLP is destructed.
SmallVector<unique_value, 8> DeletedInstructions;
/// 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.
SetVector<Instruction *> GatherSeq;
/// 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;
UnscheduledDepsInBundle = UnscheduledDeps;
clearDependencies();
OpValue = OpVal;
}
/// Returns true if the dependency information has been calculated.
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;
}
/// 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, also updating it for
/// the whole bundle.
int incrementUnscheduledDeps(int Incr) {
UnscheduledDeps += Incr;
return FirstInBundle->UnscheduledDepsInBundle += Incr;
}
/// Sets the number of unscheduled dependencies to the number of
/// dependencies.
void resetUnscheduledDeps() {
incrementUnscheduledDeps(Dependencies - UnscheduledDeps);
}
/// Clears all dependency information.
void clearDependencies() {
Dependencies = InvalidDeps;
resetUnscheduledDeps();
MemoryDependencies.clear();
}
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;
/// 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;
/// 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;
/// The sum of UnscheduledDeps in a bundle. Equals to UnscheduledDeps for
/// single instructions.
int UnscheduledDepsInBundle = InvalidDeps;
/// True if this instruction is scheduled (or considered as scheduled in the
/// dry-run).
bool IsScheduled = false;
/// Opcode of the current instruction in the schedule data.
Value *OpValue = nullptr;
};
#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.
struct BlockScheduling {
BlockScheduling(BasicBlock *BB)
: BB(BB), ChunkSize(BB->size()), ChunkPos(ChunkSize) {}
void clear() {
ReadyInsts.clear();
ScheduleStart = nullptr;
ScheduleEnd = nullptr;
FirstLoadStoreInRegion = nullptr;
LastLoadStoreInRegion = nullptr;
// 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(Value *V) {
ScheduleData *SD = ScheduleDataMap[V];
if (SD && SD->SchedulingRegionID == SchedulingRegionID)
return SD;
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[Key];
if (SD && SD->SchedulingRegionID == SchedulingRegionID)
return SD;
}
return nullptr;
}
bool isInSchedulingRegion(ScheduleData *SD) {
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");
ScheduleData *BundleMember = SD;
while (BundleMember) {
if (BundleMember->Inst != BundleMember->OpValue) {
BundleMember = BundleMember->NextInBundle;
continue;
}
// Handle the def-use chain dependencies.
for (Use &U : BundleMember->Inst->operands()) {
auto *I = dyn_cast<Instruction>(U.get());
if (!I)
continue;
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");
}
});
}
// Handle the memory dependencies.
for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) {
if (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");
}
}
BundleMember = BundleMember->NextInBundle;
}
}
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 (P.second->SchedulingRegionID == SchedulingRegionID)
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->isReady()) {
ReadyList.insert(SD);
LLVM_DEBUG(dbgs()
<< "SLP: initially in ready list: " << *I << "\n");
}
});
}
}
/// 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.
bool 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<Value *, ScheduleData *> ScheduleDataMap;
/// Attaches ScheduleData to Instruction with the leading key.
DenseMap<Value *, SmallDenseMap<Value *, ScheduleData *>>
ExtraScheduleDataMap;
struct ReadyList : SmallVector<ScheduleData *, 8> {
void insert(ScheduleData *SD) { push_back(SD); }
};
/// The ready-list for scheduling (only used for the dry-run).
ReadyList 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;
/// 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.
ArrayRef<Value *> UserIgnoreList;
using OrdersType = SmallVector<unsigned, 4>;
/// 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;
}
};
/// Contains orders of operations along with the number of bundles that have
/// operations in this order. It stores only those orders that require
/// reordering, if reordering is not required it is counted using \a
/// NumOpsWantToKeepOriginalOrder.
DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo> NumOpsWantToKeepOrder;
/// Number of bundles that do not require reordering.
unsigned NumOpsWantToKeepOriginalOrder = 0;
// Analysis and block reference.
Function *F;
ScalarEvolution *SE;
TargetTransformInfo *TTI;
TargetLibraryInfo *TLI;
AliasAnalysis *AA;
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 *;
/// 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> {
std::vector<TreeEntry> &VectorizableTree;
ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W,
std::vector<TreeEntry> &VT)
: ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {}
NodeRef operator*() { return &VectorizableTree[I->Idx]; }
};
static NodeRef getEntryNode(BoUpSLP &R) { return &R.VectorizableTree[0]; }
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.
using nodes_iterator = pointer_iterator<std::vector<TreeEntry>::iterator>;
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);
if (isSplat(Entry->Scalars)) {
OS << "<splat> " << *Entry->Scalars[0];
return Str;
}
for (auto V : Entry->Scalars) {
OS << *V;
if (std::any_of(
R->ExternalUses.begin(), R->ExternalUses.end(),
[&](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->NeedToGather)
return "color=red";
return "";
}
};
} // end namespace llvm
void BoUpSLP::buildTree(ArrayRef<Value *> Roots,
ArrayRef<Value *> UserIgnoreLst) {
ExtraValueToDebugLocsMap ExternallyUsedValues;
buildTree(Roots, ExternallyUsedValues, UserIgnoreLst);
}
void BoUpSLP::buildTree(ArrayRef<Value *> Roots,
ExtraValueToDebugLocsMap &ExternallyUsedValues,
ArrayRef<Value *> UserIgnoreLst) {
deleteTree();
UserIgnoreList = UserIgnoreLst;
if (!allSameType(Roots))
return;
buildTree_rec(Roots, 0, EdgeInfo());
// Collect the values that we need to extract from the tree.
for (TreeEntry &EIdx : VectorizableTree) {
TreeEntry *Entry = &EIdx;
// No need to handle users of gathered values.
if (Entry->NeedToGather)
continue;
// For each lane:
for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) {
Value *Scalar = Entry->Scalars[Lane];
int FoundLane = Lane;
if (!Entry->ReuseShuffleIndices.empty()) {
FoundLane =
std::distance(Entry->ReuseShuffleIndices.begin(),
llvm::find(Entry->ReuseShuffleIndices, FoundLane));
}
// 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;
// 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 ||
!InTreeUserNeedToExtract(Scalar, UserInst, TLI)) {
LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U
<< ".\n");
assert(!UseEntry->NeedToGather && "Bad state");
continue;
}
}
// Ignore users in the user ignore list.
if (is_contained(UserIgnoreList, UserInst))
continue;
LLVM_DEBUG(dbgs() << "SLP: Need to extract:" << *U << " from lane "
<< Lane << " from " << *Scalar << ".\n");
ExternalUses.push_back(ExternalUser(Scalar, U, FoundLane));
}
}
}
}
void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth,
EdgeInfo UserTreeIdx) {
assert((allConstant(VL) || allSameType(VL)) && "Invalid types!");
InstructionsState S = getSameOpcode(VL);
if (Depth == RecursionMaxDepth) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n");
newTreeEntry(VL, false, UserTreeIdx);
return;
}
// Don't handle vectors.
if (S.OpValue->getType()->isVectorTy()) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n");
newTreeEntry(VL, false, 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, false, UserTreeIdx);
return;
}
// If all of the operands are identical or constant we have a simple solution.
if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode()) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n");
newTreeEntry(VL, false, UserTreeIdx);
return;
}
// We now know that this is a vector of instructions of the same type from
// the same block.
// Don't vectorize ephemeral values.
for (unsigned i = 0, e = VL.size(); i != e; ++i) {
if (EphValues.count(VL[i])) {
LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *VL[i]
<< ") is ephemeral.\n");
newTreeEntry(VL, false, 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");
newTreeEntry(VL, false, UserTreeIdx);
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");
E->trySetUserTEOperand(UserTreeIdx, VL, None);
return;
}
// Check that none of the instructions in the bundle are already in the tree.
for (unsigned i = 0, e = VL.size(); i != e; ++i) {
auto *I = dyn_cast<Instruction>(VL[i]);
if (!I)
continue;
if (getTreeEntry(I)) {
LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *VL[i]
<< ") is already in tree.\n");
newTreeEntry(VL, false, UserTreeIdx);
return;
}
}
// If any of the scalars is marked as a value that needs to stay scalar, then
// we need to gather the scalars.
// The reduction nodes (stored in UserIgnoreList) also should stay scalar.
for (unsigned i = 0, e = VL.size(); i != e; ++i) {
if (MustGather.count(VL[i]) || is_contained(UserIgnoreList, VL[i])) {
LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n");
newTreeEntry(VL, false, UserTreeIdx);
return;
}
}
// Check that all of the users of the scalars that we want to vectorize are
// schedulable.
auto *VL0 = cast<Instruction>(S.OpValue);
BasicBlock *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, false, UserTreeIdx);
return;
}
// Check that every instruction appears once in this bundle.
SmallVector<unsigned, 4> ReuseShuffleIndicies;
SmallVector<Value *, 4> UniqueValues;
DenseMap<Value *, unsigned> UniquePositions;
for (Value *V : VL) {
auto Res = UniquePositions.try_emplace(V, UniqueValues.size());
ReuseShuffleIndicies.emplace_back(Res.first->second);
if (Res.second)
UniqueValues.emplace_back(V);
}
if (UniqueValues.size() == VL.size()) {
ReuseShuffleIndicies.clear();
} else {
LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n");
if (UniqueValues.size() <= 1 || !llvm::isPowerOf2_32(UniqueValues.size())) {
LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n");
newTreeEntry(VL, false, UserTreeIdx);
return;
}
VL = UniqueValues;
}
auto &BSRef = BlocksSchedules[BB];
if (!BSRef)
BSRef = llvm::make_unique<BlockScheduling>(BB);
BlockScheduling &BS = *BSRef.get();
if (!BS.tryScheduleBundle(VL, this, S)) {
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, false, 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: {
PHINode *PH = dyn_cast<PHINode>(VL0);
// Check for terminator values (e.g. invoke).
for (unsigned j = 0; j < VL.size(); ++j)
for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) {
Instruction *Term = dyn_cast<Instruction>(
cast<PHINode>(VL[j])->getIncomingValueForBlock(
PH->getIncomingBlock(i)));
if (Term && Term->isTerminator()) {
LLVM_DEBUG(dbgs()
<< "SLP: Need to swizzle PHINodes (terminator use).\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
return;
}
}
newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n");
for (unsigned i = 0, e = PH->getNumIncomingValues(); i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *j : VL)
Operands.push_back(cast<PHINode>(j)->getIncomingValueForBlock(
PH->getIncomingBlock(i)));
UserTreeIdx.EdgeIdx = i;
buildTree_rec(Operands, Depth + 1, UserTreeIdx);
}
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");
++NumOpsWantToKeepOriginalOrder;
newTreeEntry(VL, /*Vectorized=*/true, 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, ReuseShuffleIndicies);
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";
});
// Insert new order with initial value 0, if it does not exist,
// otherwise return the iterator to the existing one.
auto StoredCurrentOrderAndNum =
NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first;
++StoredCurrentOrderAndNum->getSecond();
newTreeEntry(VL, /*Vectorized=*/true, UserTreeIdx, ReuseShuffleIndicies,
StoredCurrentOrderAndNum->getFirst());
// 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, ReuseShuffleIndicies);
return;
}
LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n");
newTreeEntry(VL, /*Vectorized=*/false, UserTreeIdx, ReuseShuffleIndicies);
BS.cancelScheduling(VL, VL0);
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.
Type *ScalarTy = VL0->getType();
if (DL->getTypeSizeInBits(ScalarTy) !=
DL->getTypeAllocSizeInBits(ScalarTy)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n");
return;
}
// Make sure all loads in the bundle are simple - we can't vectorize
// atomic or volatile loads.
SmallVector<Value *, 4> PointerOps(VL.size());
auto POIter = PointerOps.begin();
for (Value *V : VL) {
auto *L = cast<LoadInst>(V);
if (!L->isSimple()) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n");
return;
}
*POIter = L->getPointerOperand();
++POIter;
}
OrdersType CurrentOrder;
// Check the order of pointer operands.
if (llvm::sortPtrAccesses(PointerOps, *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()];
}
const SCEV *Scev0 = SE->getSCEV(Ptr0);
const SCEV *ScevN = SE->getSCEV(PtrN);
const auto *Diff =
dyn_cast<SCEVConstant>(SE->getMinusSCEV(ScevN, Scev0));
uint64_t Size = DL->getTypeAllocSize(ScalarTy);
// Check that the sorted loads are consecutive.
if (Diff && Diff->getAPInt().getZExtValue() == (VL.size() - 1) * Size) {
if (CurrentOrder.empty()) {
// Original loads are consecutive and does not require reordering.
++NumOpsWantToKeepOriginalOrder;
newTreeEntry(VL, /*Vectorized=*/true, UserTreeIdx,
ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n");
} else {
// Need to reorder.
auto I = NumOpsWantToKeepOrder.try_emplace(CurrentOrder).first;
++I->getSecond();
newTreeEntry(VL, /*Vectorized=*/true, UserTreeIdx,
ReuseShuffleIndicies, I->getFirst());
LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n");
}
return;
}
}
LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
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 (unsigned i = 0; i < VL.size(); ++i) {
Type *Ty = cast<Instruction>(VL[i])->getOperand(0)->getType();
if (Ty != SrcTy || !isValidElementType(Ty)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs()
<< "SLP: Gathering casts with different src types.\n");
return;
}
}
newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n");
for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *j : VL)
Operands.push_back(cast<Instruction>(j)->getOperand(i));
UserTreeIdx.EdgeIdx = i;
buildTree_rec(Operands, Depth + 1, UserTreeIdx);
}
return;
}
case Instruction::ICmp:
case Instruction::FCmp: {
// Check that all of the compares have the same predicate.
CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate();
Type *ComparedTy = VL0->getOperand(0)->getType();
for (unsigned i = 1, e = VL.size(); i < e; ++i) {
CmpInst *Cmp = cast<CmpInst>(VL[i]);
if (Cmp->getPredicate() != P0 ||
Cmp->getOperand(0)->getType() != ComparedTy) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs()
<< "SLP: Gathering cmp with different predicate.\n");
return;
}
}
newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n");
for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *j : VL)
Operands.push_back(cast<Instruction>(j)->getOperand(i));
UserTreeIdx.EdgeIdx = i;
buildTree_rec(Operands, Depth + 1, UserTreeIdx);
}
return;
}
case Instruction::Select:
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:
newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of 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(S, VL, Left, Right);
UserTreeIdx.EdgeIdx = 0;
buildTree_rec(Left, Depth + 1, UserTreeIdx);
UserTreeIdx.EdgeIdx = 1;
buildTree_rec(Right, Depth + 1, UserTreeIdx);
return;
}
for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *j : VL)
Operands.push_back(cast<Instruction>(j)->getOperand(i));
UserTreeIdx.EdgeIdx = i;
buildTree_rec(Operands, Depth + 1, UserTreeIdx);
}
return;
case Instruction::GetElementPtr: {
// We don't combine GEPs with complicated (nested) indexing.
for (unsigned j = 0; j < VL.size(); ++j) {
if (cast<Instruction>(VL[j])->getNumOperands() != 2) {
LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
return;
}
}
// We can't combine several GEPs into one vector if they operate on
// different types.
Type *Ty0 = VL0->getOperand(0)->getType();
for (unsigned j = 0; j < VL.size(); ++j) {
Type *CurTy = cast<Instruction>(VL[j])->getOperand(0)->getType();
if (Ty0 != CurTy) {
LLVM_DEBUG(dbgs()
<< "SLP: not-vectorizable GEP (different types).\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
return;
}
}
// We don't combine GEPs with non-constant indexes.
for (unsigned j = 0; j < VL.size(); ++j) {
auto Op = cast<Instruction>(VL[j])->getOperand(1);
if (!isa<ConstantInt>(Op)) {
LLVM_DEBUG(dbgs()
<< "SLP: not-vectorizable GEP (non-constant indexes).\n");
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
return;
}
}
newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n");
for (unsigned i = 0, e = 2; i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *j : VL)
Operands.push_back(cast<Instruction>(j)->getOperand(i));
UserTreeIdx.EdgeIdx = i;
buildTree_rec(Operands, Depth + 1, UserTreeIdx);
}
return;
}
case Instruction::Store: {
// Check if the stores are consecutive or of we need to swizzle them.
for (unsigned i = 0, e = VL.size() - 1; i < e; ++i)
if (!isConsecutiveAccess(VL[i], VL[i + 1], *DL, *SE)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n");
return;
}
newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n");
ValueList Operands;
for (Value *j : VL)
Operands.push_back(cast<Instruction>(j)->getOperand(0));
UserTreeIdx.EdgeIdx = 0;
buildTree_rec(Operands, Depth + 1, UserTreeIdx);
return;
}
case Instruction::Call: {
// Check if the calls are all to the same vectorizable intrinsic.
CallInst *CI = cast<CallInst>(VL0);
// Check if this is an Intrinsic call or something that can be
// represented by an intrinsic call
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
if (!isTriviallyVectorizable(ID)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n");
return;
}
Function *Int = CI->getCalledFunction();
unsigned NumArgs = CI->getNumArgOperands();
SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr);
for (unsigned j = 0; j != NumArgs; ++j)
if (hasVectorInstrinsicScalarOpd(ID, j))
ScalarArgs[j] = CI->getArgOperand(j);
for (unsigned i = 1, e = VL.size(); i != e; ++i) {
CallInst *CI2 = dyn_cast<CallInst>(VL[i]);
if (!CI2 || CI2->getCalledFunction() != Int ||
getVectorIntrinsicIDForCall(CI2, TLI) != ID ||
!CI->hasIdenticalOperandBundleSchema(*CI2)) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *VL[i]
<< "\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 (hasVectorInstrinsicScalarOpd(ID, j)) {
Value *A1J = CI2->getArgOperand(j);
if (ScalarArgs[j] != A1J) {
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, 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, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:"
<< *CI << "!=" << *VL[i] << '\n');
return;
}
}
newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies);
for (unsigned i = 0, e = CI->getNumArgOperands(); i != e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *j : VL) {
CallInst *CI2 = dyn_cast<CallInst>(j);
Operands.push_back(CI2->getArgOperand(i));
}
UserTreeIdx.EdgeIdx = i;
buildTree_rec(Operands, Depth + 1, UserTreeIdx);
}
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, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n");
return;
}
newTreeEntry(VL, true, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n");
// Reorder operands if reordering would enable vectorization.
if (isa<BinaryOperator>(VL0)) {
ValueList Left, Right;
reorderAltShuffleOperands(S, VL, Left, Right);
UserTreeIdx.EdgeIdx = 0;
buildTree_rec(Left, Depth + 1, UserTreeIdx);
UserTreeIdx.EdgeIdx = 1;
buildTree_rec(Right, Depth + 1, UserTreeIdx);
return;
}
for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) {
ValueList Operands;
// Prepare the operand vector.
for (Value *j : VL)
Operands.push_back(cast<Instruction>(j)->getOperand(i));
UserTreeIdx.EdgeIdx = i;
buildTree_rec(Operands, Depth + 1, UserTreeIdx);
}
return;
default:
BS.cancelScheduling(VL, VL0);
newTreeEntry(VL, false, UserTreeIdx, ReuseShuffleIndicies);
LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n");
return;
}
}
unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const {
unsigned N;
Type *EltTy;
auto *ST = dyn_cast<StructType>(T);
if (ST) {
N = ST->getNumElements();
EltTy = *ST->element_begin();
} else {
N = cast<ArrayType>(T)->getNumElements();
EltTy = cast<ArrayType>(T)->getElementType();
}
if (!isValidElementType(EltTy))
return 0;
uint64_t VTSize = DL.getTypeStoreSizeInBits(VectorType::get(EltTy, N));
if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T))
return 0;
if (ST) {
// Check that struct is homogeneous.
for (const auto *Ty : ST->elements())
if (Ty != EltTy)
return 0;
}
return N;
}
bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue,
SmallVectorImpl<unsigned> &CurrentOrder) const {
Instruction *E0 = cast<Instruction>(OpValue);
assert(E0->getOpcode() == Instruction::ExtractElement ||
E0->getOpcode() == Instruction::ExtractValue);
assert(E0->getOpcode() == getSameOpcode(VL).getOpcode() && "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 = Vec->getType()->getVectorNumElements();
}
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 + 1);
unsigned I = 0;
for (; I < E; ++I) {
auto *Inst = cast<Instruction>(VL[I]);
if (Inst->getOperand(0) != Vec)
break;
Optional<unsigned> Idx = getExtractIndex(Inst);
if (!Idx)
break;
const unsigned ExtIdx = *Idx;
if (ExtIdx != I) {
if (ExtIdx >= E || CurrentOrder[ExtIdx] != E + 1)
break;
ShouldKeepOrder = false;
CurrentOrder[ExtIdx] = I;
} else {
if (CurrentOrder[I] != E + 1)
break;
CurrentOrder[I] = I;
}
}
if (I < E) {
CurrentOrder.clear();
return false;
}
return ShouldKeepOrder;
}
bool BoUpSLP::areAllUsersVectorized(Instruction *I) const {
return I->hasOneUse() ||
std::all_of(I->user_begin(), I->user_end(), [this](User *U) {
return ScalarToTreeEntry.count(U) > 0;
});
}
int BoUpSLP::getEntryCost(TreeEntry *E) {
ArrayRef<Value*> VL = E->Scalars;
Type *ScalarTy = VL[0]->getType();
if (StoreInst *SI = dyn_cast<StoreInst>(VL[0]))
ScalarTy = SI->getValueOperand()->getType();
else if (CmpInst *CI = dyn_cast<CmpInst>(VL[0]))
ScalarTy = CI->getOperand(0)->getType();
VectorType *VecTy = VectorType::get(ScalarTy, VL.size());
// 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 = VectorType::get(
IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size());
unsigned ReuseShuffleNumbers = E->ReuseShuffleIndices.size();
bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty();
int ReuseShuffleCost = 0;
if (NeedToShuffleReuses) {
ReuseShuffleCost =
TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, VecTy);
}
if (E->NeedToGather) {
if (allConstant(VL))
return 0;
if (isSplat(VL)) {
return ReuseShuffleCost +
TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy, 0);
}
if (getSameOpcode(VL).getOpcode() == Instruction::ExtractElement &&
allSameType(VL) && allSameBlock(VL)) {
Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = isShuffle(VL);
if (ShuffleKind.hasValue()) {
int Cost = TTI->getShuffleCost(ShuffleKind.getValue(), VecTy);
for (auto *V : VL) {
// 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.
if (areAllUsersVectorized(cast<Instruction>(V)) &&
!ScalarToTreeEntry.count(V)) {
auto *IO = cast<ConstantInt>(
cast<ExtractElementInst>(V)->getIndexOperand());
Cost -= TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy,
IO->getZExtValue());
}
}
return ReuseShuffleCost + Cost;
}
}
return ReuseShuffleCost + getGatherCost(VL);
}
InstructionsState S = getSameOpcode(VL);
assert(S.getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL");
Instruction *VL0 = cast<Instruction>(S.OpValue);
unsigned ShuffleOrOp = S.isAltShuffle() ?
(unsigned) Instruction::ShuffleVector : S.getOpcode();
switch (ShuffleOrOp) {
case Instruction::PHI:
return 0;
case Instruction::ExtractValue:
case Instruction::ExtractElement:
if (NeedToShuffleReuses) {
unsigned Idx = 0;
for (unsigned I : E->ReuseShuffleIndices) {
if (ShuffleOrOp == Instruction::ExtractElement) {
auto *IO = cast<ConstantInt>(
cast<ExtractElementInst>(VL[I])->getIndexOperand());
Idx = IO->getZExtValue();
ReuseShuffleCost -= TTI->getVectorInstrCost(
Instruction::ExtractElement, VecTy, Idx);
} else {
ReuseShuffleCost -= TTI->getVectorInstrCost(
Instruction::ExtractElement, VecTy, Idx);
++Idx;
}
}
Idx = ReuseShuffleNumbers;
for (Value *V : VL) {
if (ShuffleOrOp == Instruction::ExtractElement) {
auto *IO = cast<ConstantInt>(
cast<ExtractElementInst>(V)->getIndexOperand());
Idx = IO->getZExtValue();
} else {
--Idx;
}
ReuseShuffleCost +=
TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, Idx);
}
}
if (!E->NeedToGather) {
int DeadCost = ReuseShuffleCost;
if (!E->ReorderIndices.empty()) {
// TODO: Merge this shuffle with the ReuseShuffleCost.
DeadCost += TTI->getShuffleCost(
TargetTransformInfo::SK_PermuteSingleSrc, VecTy);
}
for (unsigned i = 0, e = VL.size(); i < e; ++i) {
Instruction *E = cast<Instruction>(VL[i]);
// If all users are going to be vectorized, instruction can be
// considered as dead.
// The same, if have only one user, it will be vectorized for sure.
if (areAllUsersVectorized(E)) {
// Take credit for instruction that will become dead.
if (E->hasOneUse()) {
Instruction *Ext = E->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.
DeadCost -= TTI->getExtractWithExtendCost(
Ext->getOpcode(), Ext->getType(), VecTy, i);
// Add back the cost of s|zext which is subtracted separately.
DeadCost += TTI->getCastInstrCost(
Ext->getOpcode(), Ext->getType(), E->getType(), Ext);
continue;
}
}
DeadCost -=
TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, i);
}
}
return DeadCost;
}
return ReuseShuffleCost + getGatherCost(VL);
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();
int ScalarEltCost =
TTI->getCastInstrCost(S.getOpcode(), ScalarTy, SrcTy, VL0);
if (NeedToShuffleReuses) {
ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
}
// Calculate the cost of this instruction.
int ScalarCost = VL.size() * ScalarEltCost;
VectorType *SrcVecTy = VectorType::get(SrcTy, VL.size());
int VecCost = 0;
// Check if the values are candidates to demote.
if (!MinBWs.count(VL0) || VecTy != SrcVecTy) {
VecCost = ReuseShuffleCost +
TTI->getCastInstrCost(S.getOpcode(), VecTy, SrcVecTy, VL0);
}
return VecCost - ScalarCost;
}
case Instruction::FCmp:
case Instruction::ICmp:
case Instruction::Select: {
// Calculate the cost of this instruction.
int ScalarEltCost = TTI->getCmpSelInstrCost(S.getOpcode(), ScalarTy,
Builder.getInt1Ty(), VL0);
if (NeedToShuffleReuses) {
ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
}
VectorType *MaskTy = VectorType::get(Builder.getInt1Ty(), VL.size());
int ScalarCost = VecTy->getNumElements() * ScalarEltCost;
int VecCost = TTI->getCmpSelInstrCost(S.getOpcode(), VecTy, MaskTy, VL0);
return ReuseShuffleCost + VecCost - ScalarCost;
}
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: {
// Certain instructions can be cheaper to vectorize if they have a
// constant second vector operand.
TargetTransformInfo::OperandValueKind Op1VK =
TargetTransformInfo::OK_AnyValue;
TargetTransformInfo::OperandValueKind Op2VK =
TargetTransformInfo::OK_UniformConstantValue;
TargetTransformInfo::OperandValueProperties Op1VP =
TargetTransformInfo::OP_None;
TargetTransformInfo::OperandValueProperties Op2VP =
TargetTransformInfo::OP_PowerOf2;
// If all operands are exactly the same ConstantInt then set the
// operand kind to OK_UniformConstantValue.
// If instead not all operands are constants, then set the operand kind
// to OK_AnyValue. If all operands are constants but not the same,
// then set the operand kind to OK_NonUniformConstantValue.
ConstantInt *CInt0 = nullptr;
for (unsigned i = 0, e = VL.size(); i < e; ++i) {
const Instruction *I = cast<Instruction>(VL[i]);
ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(1));
if (!CInt) {
Op2VK = TargetTransformInfo::OK_AnyValue;
Op2VP = TargetTransformInfo::OP_None;
break;
}
if (Op2VP == TargetTransformInfo::OP_PowerOf2 &&
!CInt->getValue().isPowerOf2())
Op2VP = TargetTransformInfo::OP_None;
if (i == 0) {
CInt0 = CInt;
continue;
}
if (CInt0 != CInt)
Op2VK = TargetTransformInfo::OK_NonUniformConstantValue;
}
SmallVector<const Value *, 4> Operands(VL0->operand_values());
int ScalarEltCost = TTI->getArithmeticInstrCost(
S.getOpcode(), ScalarTy, Op1VK, Op2VK, Op1VP, Op2VP, Operands);
if (NeedToShuffleReuses) {
ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
}
int ScalarCost = VecTy->getNumElements() * ScalarEltCost;
int VecCost = TTI->getArithmeticInstrCost(S.getOpcode(), VecTy, Op1VK,
Op2VK, Op1VP, Op2VP, Operands);
return ReuseShuffleCost + VecCost - ScalarCost;
}
case Instruction::GetElementPtr: {
TargetTransformInfo::OperandValueKind Op1VK =
TargetTransformInfo::OK_AnyValue;
TargetTransformInfo::OperandValueKind Op2VK =
TargetTransformInfo::OK_UniformConstantValue;
int ScalarEltCost =
TTI->getArithmeticInstrCost(Instruction::Add, ScalarTy, Op1VK, Op2VK);
if (NeedToShuffleReuses) {
ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
}
int ScalarCost = VecTy->getNumElements() * ScalarEltCost;
int VecCost =
TTI->getArithmeticInstrCost(Instruction::Add, VecTy, Op1VK, Op2VK);
return ReuseShuffleCost + VecCost - ScalarCost;
}
case Instruction::Load: {
// Cost of wide load - cost of scalar loads.
unsigned alignment = cast<LoadInst>(VL0)->getAlignment();
int ScalarEltCost =
TTI->getMemoryOpCost(Instruction::Load, ScalarTy, alignment, 0, VL0);
if (NeedToShuffleReuses) {
ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
}
int ScalarLdCost = VecTy->getNumElements() * ScalarEltCost;
int VecLdCost =
TTI->getMemoryOpCost(Instruction::Load, VecTy, alignment, 0, VL0);
if (!E->ReorderIndices.empty()) {
// TODO: Merge this shuffle with the ReuseShuffleCost.
VecLdCost += TTI->getShuffleCost(
TargetTransformInfo::SK_PermuteSingleSrc, VecTy);
}
return ReuseShuffleCost + VecLdCost - ScalarLdCost;
}
case Instruction::Store: {
// We know that we can merge the stores. Calculate the cost.
unsigned alignment = cast<StoreInst>(VL0)->getAlignment();
int ScalarEltCost =
TTI->getMemoryOpCost(Instruction::Store, ScalarTy, alignment, 0, VL0);
if (NeedToShuffleReuses) {
ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
}
int ScalarStCost = VecTy->getNumElements() * ScalarEltCost;
int VecStCost =
TTI->getMemoryOpCost(Instruction::Store, VecTy, alignment, 0, VL0);
return ReuseShuffleCost + VecStCost - ScalarStCost;
}
case Instruction::Call: {
CallInst *CI = cast<CallInst>(VL0);
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
// Calculate the cost of the scalar and vector calls.
SmallVector<Type *, 4> ScalarTys;
for (unsigned op = 0, opc = CI->getNumArgOperands(); op != opc; ++op)
ScalarTys.push_back(CI->getArgOperand(op)->getType());
FastMathFlags FMF;
if (auto *FPMO = dyn_cast<FPMathOperator>(CI))
FMF = FPMO->getFastMathFlags();
int ScalarEltCost =
TTI->getIntrinsicInstrCost(ID, ScalarTy, ScalarTys, FMF);
if (NeedToShuffleReuses) {
ReuseShuffleCost -= (ReuseShuffleNumbers - VL.size()) * ScalarEltCost;
}
int ScalarCallCost = VecTy->getNumElements() * ScalarEltCost;
SmallVector<Value *, 4> Args(CI->arg_operands());
int VecCallCost = TTI->getIntrinsicInstrCost(ID, CI->getType(), Args, FMF,
VecTy->getNumElements());
LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost
<< " (" << VecCallCost << "-" << ScalarCallCost << ")"
<< " for " << *CI << "\n");
return ReuseShuffleCost + VecCallCost - ScalarCallCost;
}
case Instruction::ShuffleVector: {
assert(S.isAltShuffle() &&
((Instruction::isBinaryOp(S.getOpcode()) &&
Instruction::isBinaryOp(S.getAltOpcode())) ||
(Instruction::isCast(S.getOpcode()) &&
Instruction::isCast(S.getAltOpcode()))) &&
"Invalid Shuffle Vector Operand");
int ScalarCost = 0;
if (NeedToShuffleReuses) {
for (unsigned Idx : E->ReuseShuffleIndices) {
Instruction *I = cast<Instruction>(VL[Idx]);
ReuseShuffleCost -= TTI->getInstructionCost(
I, TargetTransformInfo::TCK_RecipThroughput);
}
for (Value *V : VL) {
Instruction *I = cast<Instruction>(V);
ReuseShuffleCost += TTI->getInstructionCost(
I, TargetTransformInfo::TCK_RecipThroughput);
}
}
for (Value *i : VL) {
Instruction *I = cast<Instruction>(i);
assert(S.isOpcodeOrAlt(I) && "Unexpected main/alternate opcode");
ScalarCost += TTI->getInstructionCost(
I, TargetTransformInfo::TCK_RecipThroughput);
}
// VecCost is equal to sum of the cost of creating 2 vectors
// and the cost of creating shuffle.
int VecCost = 0;
if (Instruction::isBinaryOp(S.getOpcode())) {
VecCost = TTI->getArithmeticInstrCost(S.getOpcode(), VecTy);
VecCost += TTI->getArithmeticInstrCost(S.getAltOpcode(), VecTy);
} else {
Type *Src0SclTy = S.MainOp->getOperand(0)->getType();
Type *Src1SclTy = S.AltOp->getOperand(0)->getType();
VectorType *Src0Ty = VectorType::get(Src0SclTy, VL.size());
VectorType *Src1Ty = VectorType::get(Src1SclTy, VL.size());
VecCost = TTI->getCastInstrCost(S.getOpcode(), VecTy, Src0Ty);
VecCost += TTI->getCastInstrCost(S.getAltOpcode(), VecTy, Src1Ty);
}
VecCost += TTI->getShuffleCost(TargetTransformInfo::SK_Select, VecTy, 0);
return ReuseShuffleCost + VecCost - ScalarCost;
}
default:
llvm_unreachable("Unknown instruction");
}
}
bool BoUpSLP::isFullyVectorizableTinyTree() {
LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height "
<< VectorizableTree.size() << " is fully vectorizable .\n");
// We only handle trees of heights 1 and 2.
if (VectorizableTree.size() == 1 && !VectorizableTree[0].NeedToGather)
return true;
if (VectorizableTree.size() != 2)
return false;
// Handle splat and all-constants stores.
if (!VectorizableTree[0].NeedToGather &&
(allConstant(VectorizableTree[1].Scalars) ||
isSplat(VectorizableTree[1].Scalars)))
return true;
// Gathering cost would be too much for tiny trees.
if (VectorizableTree[0].NeedToGather || VectorizableTree[1].NeedToGather)
return false;
return true;
}
bool BoUpSLP::isTreeTinyAndNotFullyVectorizable() {
// 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())
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;
}
int BoUpSLP::getSpillCost() {
// 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();
int Cost = 0;
SmallPtrSet<Instruction*, 4> LiveValues;
Instruction *PrevInst = nullptr;
for (const auto &N : VectorizableTree) {
Instruction *Inst = dyn_cast<Instruction>(N.Scalars[0]);
if (!Inst)
continue;
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.
BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(),
PrevInstIt =
PrevInst->getIterator().getReverse();
while (InstIt != PrevInstIt) {
if (PrevInstIt == PrevInst->getParent()->rend()) {
PrevInstIt = Inst->getParent()->rbegin();
continue;
}
// Debug informations don't impact spill cost.
if ((isa<CallInst>(&*PrevInstIt) &&
!isa<DbgInfoIntrinsic>(&*PrevInstIt)) &&
&*PrevInstIt != PrevInst) {
SmallVector<Type*, 4> V;
for (auto *II : LiveValues)
V.push_back(VectorType::get(II->getType(), BundleWidth));
Cost += TTI->getCostOfKeepingLiveOverCall(V);
}
++PrevInstIt;
}
PrevInst = Inst;
}
return Cost;
}
int BoUpSLP::getTreeCost() {
int Cost = 0;
LLVM_DEBUG(dbgs() << "SLP: Calculating cost for tree of size "
<< VectorizableTree.size() << ".\n");
unsigned BundleWidth = VectorizableTree[0].Scalars.size();
for (unsigned I = 0, E = VectorizableTree.size(); I < E; ++I) {
TreeEntry &TE = VectorizableTree[I];
// We create duplicate tree entries for gather sequences that have multiple
// uses. However, we should not compute the cost of duplicate sequences.
// For example, if we have a build vector (i.e., insertelement sequence)
// that is used by more than one vector instruction, we only need to
// compute the cost of the insertelement instructions once. The redundant
// instructions will be eliminated by CSE.
//
// We should consider not creating duplicate tree entries for gather
// sequences, and instead add additional edges to the tree representing
// their uses. Since such an approach results in fewer total entries,
// existing heuristics based on tree size may yield different results.
//
if (TE.NeedToGather &&
std::any_of(std::next(VectorizableTree.begin(), I + 1),
VectorizableTree.end(), [TE](TreeEntry &Entry) {
return Entry.NeedToGather && Entry.isSame(TE.Scalars);
}))
continue;
int C = getEntryCost(&TE);
LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C
<< " for bundle that starts with " << *TE.Scalars[0]
<< ".\n");
Cost += C;
}
SmallPtrSet<Value *, 16> ExtractCostCalculated;
int ExtractCost = 0;
for (ExternalUser &EU : ExternalUses) {
// We only add extract cost once for the same scalar.
if (!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;
// 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 = VectorType::get(EU.Scalar->getType(), BundleWidth);
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 = VectorType::get(MinTy, BundleWidth);
ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(),
VecTy, EU.Lane);
} else {
ExtractCost +=
TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane);
}
}
int SpillCost = getSpillCost();
Cost += SpillCost + ExtractCost;
std::string Str;
{
raw_string_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);
return Cost;
}
int BoUpSLP::getGatherCost(Type *Ty,
const DenseSet<unsigned> &ShuffledIndices) {
int Cost = 0;
for (unsigned i = 0, e = cast<VectorType>(Ty)->getNumElements(); i < e; ++i)
if (!ShuffledIndices.count(i))
Cost += TTI->getVectorInstrCost(Instruction::InsertElement, Ty, i);
if (!ShuffledIndices.empty())
Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty);
return Cost;
}
int BoUpSLP::getGatherCost(ArrayRef<Value *> VL) {
// 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();
VectorType *VecTy = VectorType::get(ScalarTy, VL.size());
// 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.
DenseSet<unsigned> ShuffledElements;
DenseSet<Value *> UniqueElements;
// Iterate in reverse order to consider insert elements with the high cost.
for (unsigned I = VL.size(); I > 0; --I) {
unsigned Idx = I - 1;
if (!UniqueElements.insert(VL[Idx]).second)
ShuffledElements.insert(Idx);
}
return getGatherCost(VecTy, ShuffledElements);
}
// Reorder commutative operations in alternate shuffle if the resulting vectors
// are consecutive loads. This would allow us to vectorize the tree.
// If we have something like-
// load a[0] - load b[0]
// load b[1] + load a[1]
// load a[2] - load b[2]
// load a[3] + load b[3]
// Reordering the second load b[1] load a[1] would allow us to vectorize this
// code.
void BoUpSLP::reorderAltShuffleOperands(const InstructionsState &S,
ArrayRef<Value *> VL,
SmallVectorImpl<Value *> &Left,
SmallVectorImpl<Value *> &Right) {
// Push left and right operands of binary operation into Left and Right
for (Value *V : VL) {
auto *I = cast<Instruction>(V);
assert(S.isOpcodeOrAlt(I) && "Incorrect instruction in vector");
Left.push_back(I->getOperand(0));
Right.push_back(I->getOperand(1));
}
// Reorder if we have a commutative operation and consecutive access
// are on either side of the alternate instructions.
for (unsigned j = 0, e = VL.size() - 1; j < e; ++j) {
if (LoadInst *L = dyn_cast<LoadInst>(Left[j])) {
if (LoadInst *L1 = dyn_cast<LoadInst>(Right[j + 1])) {
Instruction *VL1 = cast<Instruction>(VL[j]);
Instruction *VL2 = cast<Instruction>(VL[j + 1]);
if (VL1->isCommutative() && isConsecutiveAccess(L, L1, *DL, *SE)) {
std::swap(Left[j], Right[j]);
continue;
} else if (VL2->isCommutative() &&
isConsecutiveAccess(L, L1, *DL, *SE)) {
std::swap(Left[j + 1], Right[j + 1]);
continue;
}
// else unchanged
}
}
if (LoadInst *L = dyn_cast<LoadInst>(Right[j])) {
if (LoadInst *L1 = dyn_cast<LoadInst>(Left[j + 1])) {
Instruction *VL1 = cast<Instruction>(VL[j]);
Instruction *VL2 = cast<Instruction>(VL[j + 1]);
if (VL1->isCommutative() && isConsecutiveAccess(L, L1, *DL, *SE)) {
std::swap(Left[j], Right[j]);
continue;
} else if (VL2->isCommutative() &&
isConsecutiveAccess(L, L1, *DL, *SE)) {
std::swap(Left[j + 1], Right[j + 1]);
continue;
}
// else unchanged
}
}
}
}
// Return true if I should be commuted before adding it's left and right
// operands to the arrays Left and Right.
//
// The vectorizer is trying to either have all elements one side being
// instruction with the same opcode to enable further vectorization, or having
// a splat to lower the vectorizing cost.
static bool shouldReorderOperands(int i, Instruction &I, ArrayRef<Value *> Left,
ArrayRef<Value *> Right,
bool AllSameOpcodeLeft,
bool AllSameOpcodeRight, bool SplatLeft,
bool SplatRight, Value *&VLeft,
Value *&VRight) {
VLeft = I.getOperand(0);
VRight = I.getOperand(1);
// If we have "SplatRight", try to see if commuting is needed to preserve it.
if (SplatRight) {
if (VRight == Right[i - 1])
// Preserve SplatRight
return false;
if (VLeft == Right[i - 1]) {
// Commuting would preserve SplatRight, but we don't want to break
// SplatLeft either, i.e. preserve the original order if possible.
// (FIXME: why do we care?)
if (SplatLeft && VLeft == Left[i - 1])
return false;
return true;
}
}
// Symmetrically handle Right side.
if (SplatLeft) {
if (VLeft == Left[i - 1])
// Preserve SplatLeft
return false;
if (VRight == Left[i - 1])
return true;
}
Instruction *ILeft = dyn_cast<Instruction>(VLeft);
Instruction *IRight = dyn_cast<Instruction>(VRight);
// If we have "AllSameOpcodeRight", try to see if the left operands preserves
// it and not the right, in this case we want to commute.
if (AllSameOpcodeRight) {
unsigned RightPrevOpcode = cast<Instruction>(Right[i - 1])->getOpcode();
if (IRight && RightPrevOpcode == IRight->getOpcode())
// Do not commute, a match on the right preserves AllSameOpcodeRight
return false;
if (ILeft && RightPrevOpcode == ILeft->getOpcode()) {
// We have a match and may want to commute, but first check if there is
// not also a match on the existing operands on the Left to preserve
// AllSameOpcodeLeft, i.e. preserve the original order if possible.
// (FIXME: why do we care?)
if (AllSameOpcodeLeft && ILeft &&
cast<Instruction>(Left[i - 1])->getOpcode() == ILeft->getOpcode())
return false;
return true;
}
}
// Symmetrically handle Left side.
if (AllSameOpcodeLeft) {
unsigned LeftPrevOpcode = cast<Instruction>(Left[i - 1])->getOpcode();
if (ILeft && LeftPrevOpcode == ILeft->getOpcode())
return false;
if (IRight && LeftPrevOpcode == IRight->getOpcode())
return true;
}
return false;
}
void BoUpSLP::reorderInputsAccordingToOpcode(const InstructionsState &S,
ArrayRef<Value *> VL,
SmallVectorImpl<Value *> &Left,
SmallVectorImpl<Value *> &Right) {
if (!VL.empty()) {
// Peel the first iteration out of the loop since there's nothing
// interesting to do anyway and it simplifies the checks in the loop.
auto *I = cast<Instruction>(VL[0]);
Value *VLeft = I->getOperand(0);
Value *VRight = I->getOperand(1);
if (!isa<Instruction>(VRight) && isa<Instruction>(VLeft))
// Favor having instruction to the right. FIXME: why?
std::swap(VLeft, VRight);
Left.push_back(VLeft);
Right.push_back(VRight);
}
// Keep track if we have instructions with all the same opcode on one side.
bool AllSameOpcodeLeft = isa<Instruction>(Left[0]);
bool AllSameOpcodeRight = isa<Instruction>(Right[0]);
// Keep track if we have one side with all the same value (broadcast).
bool SplatLeft = true;
bool SplatRight = true;
for (unsigned i = 1, e = VL.size(); i != e; ++i) {
Instruction *I = cast<Instruction>(VL[i]);
assert(((I->getOpcode() == S.getOpcode() && I->isCommutative()) ||
(I->getOpcode() != S.getOpcode() &&
Instruction::isCommutative(S.getOpcode()))) &&
"Can only process commutative instruction");
// Commute to favor either a splat or maximizing having the same opcodes on
// one side.
Value *VLeft;
Value *VRight;
if (shouldReorderOperands(i, *I, Left, Right, AllSameOpcodeLeft,
AllSameOpcodeRight, SplatLeft, SplatRight, VLeft,
VRight)) {
Left.push_back(VRight);
Right.push_back(VLeft);
} else {
Left.push_back(VLeft);
Right.push_back(VRight);
}
// Update Splat* and AllSameOpcode* after the insertion.
SplatRight = SplatRight && (Right[i - 1] == Right[i]);
SplatLeft = SplatLeft && (Left[i - 1] == Left[i]);
AllSameOpcodeLeft = AllSameOpcodeLeft && isa<Instruction>(Left[i]) &&
(cast<Instruction>(Left[i - 1])->getOpcode() ==
cast<Instruction>(Left[i])->getOpcode());
AllSameOpcodeRight = AllSameOpcodeRight && isa<Instruction>(Right[i]) &&
(cast<Instruction>(Right[i - 1])->getOpcode() ==
cast<Instruction>(Right[i])->getOpcode());
}
// If one operand end up being broadcast, return this operand order.
if (SplatRight || SplatLeft)
return;
// Finally check if we can get longer vectorizable chain by reordering
// without breaking the good operand order detected above.
// E.g. If we have something like-
// load a[0] load b[0]
// load b[1] load a[1]
// load a[2] load b[2]
// load a[3] load b[3]
// Reordering the second load b[1] load a[1] would allow us to vectorize
// this code and we still retain AllSameOpcode property.
// FIXME: This load reordering might break AllSameOpcode in some rare cases
// such as-
// add a[0],c[0] load b[0]
// add a[1],c[2] load b[1]
// b[2] load b[2]
// add a[3],c[3] load b[3]
for (unsigned j = 0, e = VL.size() - 1; j < e; ++j) {
if (LoadInst *L = dyn_cast<LoadInst>(Left[j])) {
if (LoadInst *L1 = dyn_cast<LoadInst>(Right[j + 1])) {
if (isConsecutiveAccess(L, L1, *DL, *SE)) {
std::swap(Left[j + 1], Right[j + 1]);
continue;
}
}
}
if (LoadInst *L = dyn_cast<LoadInst>(Right[j])) {
if (LoadInst *L1 = dyn_cast<LoadInst>(Left[j + 1])) {
if (isConsecutiveAccess(L, L1, *DL, *SE)) {
std::swap(Left[j + 1], Right[j + 1]);
continue;
}
}
}
// else unchanged
}
}
void BoUpSLP::setInsertPointAfterBundle(ArrayRef<Value *> VL,
const InstructionsState &S) {
// Get the basic block this bundle is in. All instructions in the bundle
// should be in this block.
auto *Front = cast<Instruction>(S.OpValue);
auto *BB = Front->getParent();
assert(llvm::all_of(make_range(VL.begin(), VL.end()), [=](Value *V) -> bool {
auto *I = cast<Instruction>(V);
return !S.isOpcodeOrAlt(I) || I->getParent() == BB;
}));
// 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)) {
auto *Bundle =
BlocksSchedules[BB]->getScheduleData(isOneOf(S, VL.back()));
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) {
SmallPtrSet<Value *, 16> Bundle(VL.begin(), VL.end());
for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) {
if (Bundle.erase(&I) && S.isOpcodeOrAlt(&I))
LastInst = &I;
if (Bundle.empty())
break;
}
}
// Set the insertion point after the last instruction in the bundle. Set the
// debug location to Front.
Builder.SetInsertPoint(BB, ++LastInst->getIterator());
Builder.SetCurrentDebugLocation(Front->getDebugLoc());
}
Value *BoUpSLP::Gather(ArrayRef<Value *> VL, VectorType *Ty) {
Value *Vec = UndefValue::get(Ty);
// Generate the 'InsertElement' instruction.
for (unsigned i = 0; i < Ty->getNumElements(); ++i) {
Vec = Builder.CreateInsertElement(Vec, VL[i], Builder.getInt32(i));
if (Instruction *Insrt = dyn_cast<Instruction>(Vec)) {
GatherSeq.insert(Insrt);
CSEBlocks.insert(Insrt->getParent());
// Add to our 'need-to-extract' list.
if (TreeEntry *E = getTreeEntry(VL[i])) {
// Find which lane we need to extract.
int FoundLane = -1;
for (unsigned Lane = 0, LE = E->Scalars.size(); Lane != LE; ++Lane) {
// Is this the lane of the scalar that we are looking for ?
if (E->Scalars[Lane] == VL[i]) {
FoundLane = Lane;
break;
}
}
assert(FoundLane >= 0 && "Could not find the correct lane");
if (!E->ReuseShuffleIndices.empty()) {
FoundLane =
std::distance(E->ReuseShuffleIndices.begin(),
llvm::find(E->ReuseShuffleIndices, FoundLane));
}
ExternalUses.push_back(ExternalUser(VL[i], Insrt, FoundLane));
}
}
}
return Vec;
}
Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) {
InstructionsState S = getSameOpcode(VL);
if (S.getOpcode()) {
if (TreeEntry *E = getTreeEntry(S.OpValue)) {
if (E->isSame(VL)) {
Value *V = vectorizeTree(E);
if (VL.size() == E->Scalars.size() && !E->ReuseShuffleIndices.empty()) {
// We need to get the vectorized value but without shuffle.
if (auto *SV = dyn_cast<ShuffleVectorInst>(V)) {
V = SV->getOperand(0);
} else {
// Reshuffle to get only unique values.
SmallVector<unsigned, 4> UniqueIdxs;
SmallSet<unsigned, 4> UsedIdxs;
for(unsigned Idx : E->ReuseShuffleIndices)
if (UsedIdxs.insert(Idx).second)
UniqueIdxs.emplace_back(Idx);
V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()),
UniqueIdxs);
}
}
return V;
}
}
}
Type *ScalarTy = S.OpValue->getType();
if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue))
ScalarTy = SI->getValueOperand()->getType();
// Check that every instruction appears once in this bundle.
SmallVector<unsigned, 4> ReuseShuffleIndicies;
SmallVector<Value *, 4> UniqueValues;
if (VL.size() > 2) {
DenseMap<Value *, unsigned> UniquePositions;
for (Value *V : VL) {
auto Res = UniquePositions.try_emplace(V, UniqueValues.size());
ReuseShuffleIndicies.emplace_back(Res.first->second);
if (Res.second || isa<Constant>(V))
UniqueValues.emplace_back(V);
}
// Do not shuffle single element or if number of unique values is not power
// of 2.
if (UniqueValues.size() == VL.size() || UniqueValues.size() <= 1 ||
!llvm::isPowerOf2_32(UniqueValues.size()))
ReuseShuffleIndicies.clear();
else
VL = UniqueValues;
}
VectorType *VecTy = VectorType::get(ScalarTy, VL.size());
Value *V = Gather(VL, VecTy);
if (!ReuseShuffleIndicies.empty()) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
ReuseShuffleIndicies, "shuffle");
if (auto *I = dyn_cast<Instruction>(V)) {
GatherSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
}
return V;
}
static void inversePermutation(ArrayRef<unsigned> Indices,
SmallVectorImpl<unsigned> &Mask) {
Mask.clear();
const unsigned E = Indices.size();
Mask.resize(E);
for (unsigned I = 0; I < E; ++I)
Mask[Indices[I]] = I;
}
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;
}
InstructionsState S = getSameOpcode(E->Scalars);
Instruction *VL0 = cast<Instruction>(S.OpValue);
Type *ScalarTy = VL0->getType();
if (StoreInst *SI = dyn_cast<StoreInst>(VL0))
ScalarTy = SI->getValueOperand()->getType();
VectorType *VecTy = VectorType::get(ScalarTy, E->Scalars.size());
bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty();
if (E->NeedToGather) {
setInsertPointAfterBundle(E->Scalars, S);
auto *V = Gather(E->Scalars, VecTy);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
if (auto *I = dyn_cast<Instruction>(V)) {
GatherSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
}
E->VectorizedValue = V;
return V;
}
unsigned ShuffleOrOp = S.isAltShuffle() ?
(unsigned) Instruction::ShuffleVector : S.getOpcode();
switch (ShuffleOrOp) {
case Instruction::PHI: {
PHINode *PH = dyn_cast<PHINode>(VL0);
Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI());
Builder.SetCurrentDebugLocation(PH->getDebugLoc());
PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues());
Value *V = NewPhi;
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
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);
if (!VisitedBBs.insert(IBB).second) {
NewPhi->addIncoming(NewPhi->getIncomingValueForBlock(IBB), IBB);
continue;
}
Builder.SetInsertPoint(IBB->getTerminator());
Builder.SetCurrentDebugLocation(PH->getDebugLoc());
Value *Vec = vectorizeTree(E->getOperand(i));
NewPhi->addIncoming(Vec, IBB);
}
assert(NewPhi->getNumIncomingValues() == PH->getNumIncomingValues() &&
"Invalid number of incoming values");
return V;
}
case Instruction::ExtractElement: {
if (!E->NeedToGather) {
Value *V = E->getSingleOperand(0);
if (!E->ReorderIndices.empty()) {
OrdersType Mask;
inversePermutation(E->ReorderIndices, Mask);
Builder.SetInsertPoint(VL0);
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy), Mask,
"reorder_shuffle");
}
if (NeedToShuffleReuses) {
// TODO: Merge this shuffle with the ReorderShuffleMask.
if (E->ReorderIndices.empty())
Builder.SetInsertPoint(VL0);
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = V;
return V;
}
setInsertPointAfterBundle(E->Scalars, S);
auto *V = Gather(E->Scalars, VecTy);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
if (auto *I = dyn_cast<Instruction>(V)) {
GatherSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
}
E->VectorizedValue = V;
return V;
}
case Instruction::ExtractValue: {
if (!E->NeedToGather) {
LoadInst *LI = cast<LoadInst>(E->getSingleOperand(0));
Builder.SetInsertPoint(LI);
PointerType *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace());
Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy);
LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlignment());
Value *NewV = propagateMetadata(V, E->Scalars);
if (!E->ReorderIndices.empty()) {
OrdersType Mask;
inversePermutation(E->ReorderIndices, Mask);
NewV = Builder.CreateShuffleVector(NewV, UndefValue::get(VecTy), Mask,
"reorder_shuffle");
}
if (NeedToShuffleReuses) {
// TODO: Merge this shuffle with the ReorderShuffleMask.
NewV = Builder.CreateShuffleVector(
NewV, UndefValue::get(VecTy), E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = NewV;
return NewV;
}
setInsertPointAfterBundle(E->Scalars, S);
auto *V = Gather(E->Scalars, VecTy);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
if (auto *I = dyn_cast<Instruction>(V)) {
GatherSeq.insert(I);
CSEBlocks.insert(I->getParent());
}
}
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->Scalars, S);
Value *InVec = vectorizeTree(E->getOperand(0));
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
CastInst *CI = dyn_cast<CastInst>(VL0);
Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::FCmp:
case Instruction::ICmp: {
setInsertPointAfterBundle(E->Scalars, S);
Value *L = vectorizeTree(E->getOperand(0));
Value *R = vectorizeTree(E->getOperand(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;
if (S.getOpcode() == Instruction::FCmp)
V = Builder.CreateFCmp(P0, L, R);
else
V = Builder.CreateICmp(P0, L, R);
propagateIRFlags(V, E->Scalars, VL0);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::Select: {
setInsertPointAfterBundle(E->Scalars, S);
Value *Cond = vectorizeTree(E->getOperand(0));
Value *True = vectorizeTree(E->getOperand(1));
Value *False = vectorizeTree(E->getOperand(2));
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *V = Builder.CreateSelect(Cond, True, False);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
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->Scalars, S);
Value *LHS = vectorizeTree(E->getOperand(0));
Value *RHS = vectorizeTree(E->getOperand(1));
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *V = Builder.CreateBinOp(
static_cast<Instruction::BinaryOps>(S.getOpcode()), LHS, RHS);
propagateIRFlags(V, E->Scalars, VL0);
if (auto *I = dyn_cast<Instruction>(V))
V = propagateMetadata(I, E->Scalars);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
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.
bool IsReorder = !E->ReorderIndices.empty();
if (IsReorder) {
S = getSameOpcode(E->Scalars, E->ReorderIndices.front());
VL0 = cast<Instruction>(S.OpValue);
}
setInsertPointAfterBundle(E->Scalars, S);
LoadInst *LI = cast<LoadInst>(VL0);
Type *ScalarLoadTy = LI->getType();
unsigned AS = LI->getPointerAddressSpace();
Value *VecPtr = Builder.CreateBitCast(LI->getPointerOperand(),
VecTy->getPointerTo(AS));
// The pointer operand uses an in-tree scalar so we add the new BitCast to
// ExternalUses list to make sure that an extract will be generated in the
// future.
Value *PO = LI->getPointerOperand();
if (getTreeEntry(PO))
ExternalUses.push_back(ExternalUser(PO, cast<User>(VecPtr), 0));
unsigned Alignment = LI->getAlignment();
LI = Builder.CreateLoad(VecTy, VecPtr);
if (!Alignment) {
Alignment = DL->getABITypeAlignment(ScalarLoadTy);
}
LI->setAlignment(Alignment);
Value *V = propagateMetadata(LI, E->Scalars);
if (IsReorder) {
OrdersType Mask;
inversePermutation(E->ReorderIndices, Mask);
V = Builder.CreateShuffleVector(V, UndefValue::get(V->getType()),
Mask, "reorder_shuffle");
}
if (NeedToShuffleReuses) {
// TODO: Merge this shuffle with the ReorderShuffleMask.
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::Store: {
StoreInst *SI = cast<StoreInst>(VL0);
unsigned Alignment = SI->getAlignment();
unsigned AS = SI->getPointerAddressSpace();
setInsertPointAfterBundle(E->Scalars, S);
Value *VecValue = vectorizeTree(E->getOperand(0));
Value *ScalarPtr = SI->getPointerOperand();
Value *VecPtr = Builder.CreateBitCast(ScalarPtr, VecTy->getPointerTo(AS));
StoreInst *ST = Builder.CreateStore(VecValue, VecPtr);
// The pointer operand uses an in-tree scalar, so add the new BitCast to
// ExternalUses to make sure that an extract will be generated in the
// future.
if (getTreeEntry(ScalarPtr))
ExternalUses.push_back(ExternalUser(ScalarPtr, cast<User>(VecPtr), 0));
if (!Alignment)
Alignment = DL->getABITypeAlignment(SI->getValueOperand()->getType());
ST->setAlignment(Alignment);
Value *V = propagateMetadata(ST, E->Scalars);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::GetElementPtr: {
setInsertPointAfterBundle(E->Scalars, S);
Value *Op0 = vectorizeTree(E->getOperand(0));
std::vector<Value *> OpVecs;
for (int j = 1, e = cast<GetElementPtrInst>(VL0)->getNumOperands(); j < e;
++j) {
Value *OpVec = vectorizeTree(E->getOperand(j));
OpVecs.push_back(OpVec);
}
Value *V = Builder.CreateGEP(
cast<GetElementPtrInst>(VL0)->getSourceElementType(), Op0, OpVecs);
if (Instruction *I = dyn_cast<Instruction>(V))
V = propagateMetadata(I, E->Scalars);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::Call: {
CallInst *CI = cast<CallInst>(VL0);
setInsertPointAfterBundle(E->Scalars, S);
Function *FI;
Intrinsic::ID IID = Intrinsic::not_intrinsic;
Value *ScalarArg = nullptr;
if (CI && (FI = CI->getCalledFunction())) {
IID = FI->getIntrinsicID();
}
std::vector<Value *> OpVecs;
for (int j = 0, e = CI->getNumArgOperands(); j < e; ++j) {
ValueList OpVL;
// Some intrinsics have scalar arguments. This argument should not be
// vectorized.
if (hasVectorInstrinsicScalarOpd(IID, j)) {
CallInst *CEI = cast<CallInst>(VL0);
ScalarArg = CEI->getArgOperand(j);
OpVecs.push_back(CEI->getArgOperand(j));
continue;
}
Value *OpVec = vectorizeTree(E->getOperand(j));
LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n");
OpVecs.push_back(OpVec);
}
Module *M = F->getParent();
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
Type *Tys[] = { VectorType::get(CI->getType(), E->Scalars.size()) };
Function *CF = Intrinsic::getDeclaration(M, ID, Tys);
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 && getTreeEntry(ScalarArg))
ExternalUses.push_back(ExternalUser(ScalarArg, cast<User>(V), 0));
propagateIRFlags(V, E->Scalars, VL0);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
case Instruction::ShuffleVector: {
assert(S.isAltShuffle() &&
((Instruction::isBinaryOp(S.getOpcode()) &&
Instruction::isBinaryOp(S.getAltOpcode())) ||
(Instruction::isCast(S.getOpcode()) &&
Instruction::isCast(S.getAltOpcode()))) &&
"Invalid Shuffle Vector Operand");
Value *LHS, *RHS;
if (Instruction::isBinaryOp(S.getOpcode())) {
setInsertPointAfterBundle(E->Scalars, S);
LHS = vectorizeTree(E->getOperand(0));
RHS = vectorizeTree(E->getOperand(1));
} else {
setInsertPointAfterBundle(E->Scalars, S);
LHS = vectorizeTree(E->getOperand(0));
}
if (E->VectorizedValue) {
LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n");
return E->VectorizedValue;
}
Value *V0, *V1;
if (Instruction::isBinaryOp(S.getOpcode())) {
V0 = Builder.CreateBinOp(
static_cast<Instruction::BinaryOps>(S.getOpcode()), LHS, RHS);
V1 = Builder.CreateBinOp(
static_cast<Instruction::BinaryOps>(S.getAltOpcode()), LHS, RHS);
} else {
V0 = Builder.CreateCast(
static_cast<Instruction::CastOps>(S.getOpcode()), LHS, VecTy);
V1 = Builder.CreateCast(
static_cast<Instruction::CastOps>(S.getAltOpcode()), LHS, VecTy);
}
// 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;
unsigned e = E->Scalars.size();
SmallVector<Constant *, 8> Mask(e);
for (unsigned i = 0; i < e; ++i) {
auto *OpInst = cast<Instruction>(E->Scalars[i]);
assert(S.isOpcodeOrAlt(OpInst) && "Unexpected main/alternate opcode");
if (OpInst->getOpcode() == S.getAltOpcode()) {
Mask[i] = Builder.getInt32(e + i);
AltScalars.push_back(E->Scalars[i]);
} else {
Mask[i] = Builder.getInt32(i);
OpScalars.push_back(E->Scalars[i]);
}
}
Value *ShuffleMask = ConstantVector::get(Mask);
propagateIRFlags(V0, OpScalars);
propagateIRFlags(V1, AltScalars);
Value *V = Builder.CreateShuffleVector(V0, V1, ShuffleMask);
if (Instruction *I = dyn_cast<Instruction>(V))
V = propagateMetadata(I, E->Scalars);
if (NeedToShuffleReuses) {
V = Builder.CreateShuffleVector(V, UndefValue::get(VecTy),
E->ReuseShuffleIndices, "shuffle");
}
E->VectorizedValue = V;
++NumVectorInstructions;
return V;
}
default:
llvm_unreachable("unknown inst");
}
return nullptr;
}
Value *BoUpSLP::vectorizeTree() {
ExtraValueToDebugLocsMap ExternallyUsedValues;
return vectorizeTree(ExternallyUsedValues);
}
Value *
BoUpSLP::vectorizeTree(ExtraValueToDebugLocsMap &ExternallyUsedValues) {
// All blocks must be scheduled before any instructions are inserted.
for (auto &BSIter : BlocksSchedules) {
scheduleBlock(BSIter.second.get());
}
Builder.SetInsertPoint(&F->getEntryBlock().front());
auto *VectorRoot = vectorizeTree(&VectorizableTree[0]);
// 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))
Builder.SetInsertPoint(&*++BasicBlock::iterator(I));
auto BundleWidth = VectorizableTree[0].Scalars.size();
auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first);
auto *VecTy = VectorType::get(MinTy, BundleWidth);
auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy);
VectorizableTree[0].VectorizedValue = Trunc;
}
LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size()
<< " values .\n");
// If necessary, sign-extend or zero-extend ScalarRoot to the larger type
// specified by ScalarType.
auto extend = [&](Value *ScalarRoot, Value *Ex, Type *ScalarType) {
if (!MinBWs.count(ScalarRoot))
return Ex;
if (MinBWs[ScalarRoot].second)
return Builder.CreateSExt(Ex, ScalarType);
return Builder.CreateZExt(Ex, ScalarType);
};
// 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->NeedToGather && "Extracting from a gather list");
Value *Vec = E->VectorizedValue;
assert(Vec && "Can't find vectorizable value");
Value *Lane = Builder.getInt32(ExternalUse.Lane);
// 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)) {
Builder.SetInsertPoint(VecI->getParent(),
std::next(VecI->getIterator()));
} else {
Builder.SetInsertPoint(&F->getEntryBlock().front());
}
Value *Ex = Builder.CreateExtractElement(Vec, Lane);
Ex = extend(ScalarRoot, Ex, Scalar->getType());
CSEBlocks.insert(cast<Instruction>(Scalar)->getParent());
auto &Locs = ExternallyUsedValues[Scalar];
ExternallyUsedValues.insert({Ex, Locs});
ExternallyUsedValues.erase(Scalar);
// Required to update internally referenced instructions.
Scalar->replaceAllUsesWith(Ex);
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 *Ex = Builder.CreateExtractElement(Vec, Lane);
Ex = extend(ScalarRoot, Ex, Scalar->getType());
CSEBlocks.insert(PH->getIncomingBlock(i));
PH->setOperand(i, Ex);
}
}
} else {
Builder.SetInsertPoint(cast<Instruction>(User));
Value *Ex = Builder.CreateExtractElement(Vec, Lane);
Ex = extend(ScalarRoot, Ex, Scalar->getType());
CSEBlocks.insert(cast<Instruction>(User)->getParent());
User->replaceUsesOfWith(Scalar, Ex);
}
} else {
Builder.SetInsertPoint(&F->getEntryBlock().front());
Value *Ex = Builder.CreateExtractElement(Vec, Lane);
Ex = extend(ScalarRoot, Ex, Scalar->getType());
CSEBlocks.insert(&F->getEntryBlock());
User->replaceUsesOfWith(Scalar, Ex);
}
LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n");
}
// For each vectorized value:
for (TreeEntry &EIdx : VectorizableTree) {
TreeEntry *Entry = &EIdx;
// No need to handle users of gathered values.
if (Entry->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];
Type *Ty = Scalar->getType();
if (!Ty->isVoidTy()) {
#ifndef NDEBUG
for (User *U : Scalar->users()) {
LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n");
// It is legal to replace users in the ignorelist by undef.
assert((getTreeEntry(U) || is_contained(UserIgnoreList, U)) &&
"Replacing out-of-tree value with undef");
}
#endif
Value *Undef = UndefValue::get(Ty);
Scalar->replaceAllUsesWith(Undef);
}
LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n");
eraseInstruction(cast<Instruction>(Scalar));
}
}
Builder.ClearInsertionPoint();
return VectorizableTree[0].VectorizedValue;
}
void BoUpSLP::optimizeGatherSequence() {
LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherSeq.size()
<< " gather sequences instructions.\n");
// LICM InsertElementInst sequences.
for (Instruction *I : GatherSeq) {
if (!isa<InsertElementInst>(I) && !isa<ShuffleVectorInst>(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.
auto *Op0 = dyn_cast<Instruction>(I->getOperand(0));
auto *Op1 = dyn_cast<Instruction>(I->getOperand(1));
if (Op0 && L->contains(Op0))
continue;
if (Op1 && L->contains(Op1))
continue;
// We can hoist this instruction. Move it to the pre-header.
I->moveBefore(PreHeader->getTerminator());
}
// 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.
std::stable_sort(CSEWorkList.begin(), CSEWorkList.end(),
[this](const DomTreeNode *A, const DomTreeNode *B) {
return DT->properlyDominates(A, B);
});
// Perform O(N^2) search over the gather 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 == 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 (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e;) {
Instruction *In = &*it++;
if (!isa<InsertElementInst>(In) && !isa<ExtractElementInst>(In))
continue;
// Check if we can replace this instruction with any of the
// visited instructions.
for (Instruction *v : Visited) {
if (In->isIdenticalTo(v) &&
DT->dominates(v->getParent(), In->getParent())) {
In->replaceAllUsesWith(v);
eraseInstruction(In);
In = nullptr;
break;
}
}
if (In) {
assert(!is_contained(Visited, In));
Visited.push_back(In);
}
}
}
CSEBlocks.clear();
GatherSeq.clear();
}
// Groups the instructions to a bundle (which is then a single scheduling entity)
// and schedules instructions until the bundle gets ready.
bool BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL,
BoUpSLP *SLP,
const InstructionsState &S) {
if (isa<PHINode>(S.OpValue))
return true;
// Initialize the instruction bundle.
Instruction *OldScheduleEnd = ScheduleEnd;
ScheduleData *PrevInBundle = nullptr;
ScheduleData *Bundle = nullptr;
bool ReSchedule = false;
LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n");
// Make sure that the scheduling region contains all
// instructions of the bundle.
for (Value *V : VL) {
if (!extendSchedulingRegion(V, S))
return false;
}
for (Value *V : VL) {
ScheduleData *BundleMember = getScheduleData(V);
assert(BundleMember &&
"no ScheduleData for bundle member (maybe not in same basic block)");
if (BundleMember->IsScheduled) {
// 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;
}
assert(BundleMember->isSchedulingEntity() &&
"bundle member already part of other bundle");
if (PrevInBundle) {
PrevInBundle->NextInBundle = BundleMember;
} else {
Bundle = BundleMember;
}
BundleMember->UnscheduledDepsInBundle = 0;
Bundle->UnscheduledDepsInBundle += BundleMember->UnscheduledDeps;
// Group the instructions to a bundle.
BundleMember->FirstInBundle = Bundle;
PrevInBundle = BundleMember;
}
if (ScheduleEnd != OldScheduleEnd) {
// 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.
for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) {
doForAllOpcodes(I, [](ScheduleData *SD) {
SD->clearDependencies();
});
}
ReSchedule = true;
}
if (ReSchedule) {
resetSchedule();
initialFillReadyList(ReadyInsts);
}
LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle << " in block "
<< BB->getName() << "\n");
calculateDependencies(Bundle, true, SLP);
// Now try to schedule the new bundle. 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->isReady() && !ReadyInsts.empty()) {
ScheduleData *pickedSD = ReadyInsts.back();
ReadyInsts.pop_back();
if (pickedSD->isSchedulingEntity() && pickedSD->isReady()) {
schedule(pickedSD, ReadyInsts);
}
}
if (!Bundle->isReady()) {
cancelScheduling(VL, S.OpValue);
return false;
}
return true;
}
void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL,
Value *OpValue) {
if (isa<PHINode>(OpValue))
return;
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() &&
"tried to unbundle something which is not a 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->UnscheduledDepsInBundle = BundleMember->UnscheduledDeps;
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(llvm::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) && "phi nodes don't need to be scheduled");
auto &&CheckSheduleForI = [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 (CheckSheduleForI(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)
CheckSheduleForI(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 (true) {
if (++ScheduleRegionSize > ScheduleRegionSizeLimit) {
LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n");
return false;
}
if (UpIter != UpperEnd) {
if (&*UpIter == I) {
initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion);
ScheduleStart = I;
if (isOneOf(S, I) != I)
CheckSheduleForI(I);
LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I
<< "\n");
return true;
}
UpIter++;
}
if (DownIter != LowerEnd) {
if (&*DownIter == I) {
initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion,
nullptr);
ScheduleEnd = I->getNextNode();
if (isOneOf(S, I) != I)
CheckSheduleForI(I);
assert(ScheduleEnd && "tried to vectorize a terminator?");
LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I
<< "\n");
return true;
}
DownIter++;
}
assert((UpIter != UpperEnd || DownIter != LowerEnd) &&
"instruction not found in block");
}
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()) {
ScheduleData *SD = ScheduleDataMap[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)) {
// Update the linked list of memory accessing instructions.
if (CurrentLoadStore) {
CurrentLoadStore->NextLoadStore = SD;
} else {
FirstLoadStoreInRegion = SD;
}
CurrentLoadStore = SD;
}
}
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.back();
WorkList.pop_back();
ScheduleData *BundleMember = SD;
while (BundleMember) {
assert(isInSchedulingRegion(BundleMember));
if (!BundleMember->hasValidDependencies()) {
LLVM_DEBUG(dbgs() << "SLP: update deps of " << *BundleMember
<< "\n");
BundleMember->Dependencies = 0;
BundleMember->resetUnscheduledDeps();
// Handle def-use chain dependencies.
if (BundleMember->OpValue != BundleMember->Inst) {
ScheduleData *UseSD = getScheduleData(BundleMember->Inst);
if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) {
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 (isa<Instruction>(U)) {
ScheduleData *UseSD = getScheduleData(U);
if (UseSD && isInSchedulingRegion(UseSD->FirstInBundle)) {
BundleMember->Dependencies++;
ScheduleData *DestBundle = UseSD->FirstInBundle;
if (!DestBundle->IsScheduled)
BundleMember->incrementUnscheduledDeps(1);
if (!DestBundle->hasValidDependencies())
WorkList.push_back(DestBundle);
}
} else {
// I'm not sure if this can ever happen. But we need to be safe.
// This lets the instruction/bundle never be scheduled and
// eventually disable vectorization.
BundleMember->Dependencies++;
BundleMember->incrementUnscheduledDeps(1);
}
}
}
// Handle the memory dependencies.
ScheduleData *DepDest = BundleMember->NextLoadStore;
if (DepDest) {
Instruction *SrcInst = BundleMember->Inst;
MemoryLocation SrcLoc = getLocation(SrcInst, SLP->AA);
bool SrcMayWrite = BundleMember->Inst->mayWriteToMemory();
unsigned numAliased = 0;
unsigned DistToSrc = 1;
while (DepDest) {
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);
}
}
DepDest = DepDest->NextLoadStore;
// 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++;
}
}
}
BundleMember = BundleMember->NextInBundle;
}
if (InsertInReadyList && SD->isReady()) {
ReadyInsts.push_back(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");
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.
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 and fill the ready-list with
// initial instructions.
int Idx = 0;
int NumToSchedule = 0;
for (auto *I = BS->ScheduleStart; I != BS->ScheduleEnd;
I = I->getNextNode()) {
BS->doForAllOpcodes(I, [this, &Idx, &NumToSchedule, BS](ScheduleData *SD) {
assert(SD->isPartOfBundle() ==
(getTreeEntry(SD->Inst) != nullptr) &&
"scheduler and vectorizer bundle mismatch");
SD->FirstInBundle->SchedulingPriority = Idx++;
if (SD->isSchedulingEntity()) {
BS->calculateDependencies(SD, false, this);
NumToSchedule++;
}
});
}
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.
ScheduleData *BundleMember = picked;
while (BundleMember) {
Instruction *pickedInst = BundleMember->Inst;
if (LastScheduledInst->getNextNode() != pickedInst) {
BS->BB->getInstList().remove(pickedInst);
BS->BB->getInstList().insert(LastScheduledInst->getIterator(),
pickedInst);
}
LastScheduledInst = pickedInst;
BundleMember = BundleMember->NextInBundle;
}
BS->schedule(picked, ReadyInsts);
NumToSchedule--;
}
assert(NumToSchedule == 0 && "could not schedule all instructions");
// 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 without
// traversing the expression tree. This is the common case.
if (auto *Store = dyn_cast<StoreInst>(V))
return DL->getTypeSizeInBits(Store->getValueOperand()->getType());
// 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<Instruction *, 16> Worklist;
SmallPtrSet<Instruction *, 16> Visited;
if (auto *I = dyn_cast<Instruction>(V))
Worklist.push_back(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 MaxWidth = 0u;
auto FoundUnknownInst = false;
while (!Worklist.empty() && !FoundUnknownInst) {
auto *I = Worklist.pop_back_val();
Visited.insert(I);
// We should only be looking at scalar instructions here. If the current
// instruction has a vector type, give up.
auto *Ty = I->getType();
if (isa<VectorType>(Ty))
FoundUnknownInst = true;
// If the current instruction is a load, update MaxWidth to reflect the
// width of the loaded value.
else if (isa<LoadInst>(I))
MaxWidth = std::max<unsigned>(MaxWidth, 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, we add it to the worklist.
else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) ||
isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I)) {
for (Use &U : I->operands())
if (auto *J = dyn_cast<Instruction>(U.get()))
if (!Visited.count(J))
Worklist.push_back(J);
}
// If we don't yet handle the instruction, give up.
else
FoundUnknownInst = true;
}
// 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.
if (!MaxWidth || FoundUnknownInst)
return DL->getTypeSizeInBits(V->getType());
// Otherwise, return the maximum width we found.
return MaxWidth;
}
// 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:
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 &Entry : VectorizableTree)
Expr.insert(Entry.Scalars.begin(), Entry.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.countLeadingZeros(), 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.
if (!isPowerOf2_64(MaxBitWidth))
MaxBitWidth = NextPowerOf2(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);
}
namespace {
/// The SLPVectorizer Pass.
struct SLPVectorizer : public FunctionPass {
SLPVectorizerPass Impl;
/// Pass identification, replacement for typeid
static char ID;
explicit SLPVectorizer() : FunctionPass(ID) {
initializeSLPVectorizerPass(*PassRegistry::getPassRegistry());
}
bool doInitialization(Module &M) override {
return false;
}
bool runOnFunction(Function &F) override {
if (skipFunction(F))
return false;
auto *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
auto *TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>();
auto *TLI = TLIP ? &TLIP->getTLI() : nullptr;
auto *AA = &getAnalysis<AAResultsWrapperPass>().getAAResults();
auto *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
auto *DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
auto *DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits();
auto *ORE = &getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE();
return Impl.runImpl(F, SE, TTI, TLI, AA, LI, DT, AC, DB, ORE);
}
void getAnalysisUsage(AnalysisUsage &AU) const override {
FunctionPass::getAnalysisUsage(AU);
AU.addRequired<AssumptionCacheTracker>();
AU.addRequired<ScalarEvolutionWrapperPass>();
AU.addRequired<AAResultsWrapperPass>();
AU.addRequired<TargetTransformInfoWrapperPass>();
AU.addRequired<LoopInfoWrapperPass>();
AU.addRequired<DominatorTreeWrapperPass>();
AU.addRequired<DemandedBitsWrapperPass>();
AU.addRequired<OptimizationRemarkEmitterWrapperPass>();
AU.addPreserved<LoopInfoWrapperPass>();
AU.addPreserved<DominatorTreeWrapperPass>();
AU.addPreserved<AAResultsWrapperPass>();
AU.addPreserved<GlobalsAAWrapperPass>();
AU.setPreservesCFG();
}
};
} // end anonymous namespace
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>();
PA.preserve<AAManager>();
PA.preserve<GlobalsAA>();
return PA;
}
bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_,
TargetTransformInfo *TTI_,
TargetLibraryInfo *TLI_, AliasAnalysis *AA_,
LoopInfo *LI_, DominatorTree *DT_,
AssumptionCache *AC_, DemandedBits *DB_,
OptimizationRemarkEmitter *ORE_) {
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(true))
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.
// Scan the blocks in the function in post order.
for (auto BB : post_order(&F.getEntryBlock())) {
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");
LLVM_DEBUG(verifyFunction(F));
}
return Changed;
}
/// Check that the Values in the slice in VL array are still existent in
/// the WeakTrackingVH array.
/// Vectorization of part of the VL array may cause later values in the VL array
/// to become invalid. We track when this has happened in the WeakTrackingVH
/// array.
static bool hasValueBeenRAUWed(ArrayRef<Value *> VL,
ArrayRef<WeakTrackingVH> VH, unsigned SliceBegin,
unsigned SliceSize) {
VL = VL.slice(SliceBegin, SliceSize);
VH = VH.slice(SliceBegin, SliceSize);
return !std::equal(VL.begin(), VL.end(), VH.begin());
}
bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R,
unsigned VecRegSize) {
const unsigned ChainLen = Chain.size();
LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << ChainLen
<< "\n");
const unsigned Sz = R.getVectorElementSize(Chain[0]);
const unsigned VF = VecRegSize / Sz;
if (!isPowerOf2_32(Sz) || VF < 2)
return false;
// Keep track of values that were deleted by vectorizing in the loop below.
const SmallVector<WeakTrackingVH, 8> TrackValues(Chain.begin(), Chain.end());
bool Changed = false;
// Look for profitable vectorizable trees at all offsets, starting at zero.
for (unsigned i = 0, e = ChainLen; i + VF <= e; ++i) {
// Check that a previous iteration of this loop did not delete the Value.
if (hasValueBeenRAUWed(Chain, TrackValues, i, VF))
continue;
LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << i
<< "\n");
ArrayRef<Value *> Operands = Chain.slice(i, VF);
R.buildTree(Operands);
if (R.isTreeTinyAndNotFullyVectorizable())
continue;
R.computeMinimumValueSizes();
int 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[i]))
<< "Stores SLP vectorized with cost " << NV("Cost", Cost)
<< " and with tree size "
<< NV("TreeSize", R.getTreeSize()));
R.vectorizeTree();
// Move to the next bundle.
i += VF - 1;
Changed = true;
}
}
return Changed;
}
bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores,
BoUpSLP &R) {
SetVector<StoreInst *> Heads;
SmallDenseSet<StoreInst *> Tails;
SmallDenseMap<StoreInst *, StoreInst *> ConsecutiveChain;
// 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;
auto &&FindConsecutiveAccess =
[this, &Stores, &Heads, &Tails, &ConsecutiveChain] (int K, int Idx) {
if (!isConsecutiveAccess(Stores[K], Stores[Idx], *DL, *SE))
return false;
Tails.insert(Stores[Idx]);
Heads.insert(Stores[K]);
ConsecutiveChain[Stores[K]] = Stores[Idx];
return true;
};
// 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.
int E = Stores.size();
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.
for (int Offset = 1, F = std::max(E - Idx, Idx + 1); Offset < F; ++Offset)
if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) ||
(Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx)))
break;
}
// For stores that start but don't end a link in the chain:
for (auto *SI : llvm::reverse(Heads)) {
if (Tails.count(SI))
continue;
// We found a store instr that starts a chain. Now follow the chain and try
// to vectorize it.
BoUpSLP::ValueList Operands;
StoreInst *I = SI;
// Collect the chain into a list.
while ((Tails.count(I) || Heads.count(I)) && !VectorizedStores.count(I)) {
Operands.push_back(I);
// Move to the next value in the chain.
I = ConsecutiveChain[I];
}
// FIXME: Is division-by-2 the correct step? Should we assert that the
// register size is a power-of-2?
for (unsigned Size = R.getMaxVecRegSize(); Size >= R.getMinVecRegSize();
Size /= 2) {
if (vectorizeStoreChain(Operands, R, Size)) {
// Mark the vectorized stores so that we don't vectorize them again.
VectorizedStores.insert(Operands.begin(), Operands.end());
Changed = true;
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(), *DL)].push_back(SI);
}
// Ignore getelementptr instructions that have more than one index, a
// constant index, or a pointer operand that doesn't point to a scalar
// type.
else if (auto *GEP = dyn_cast<GetElementPtrInst>(&I)) {
auto Idx = GEP->idx_begin()->get();
if (GEP->getNumIndices() > 1 || isa<Constant>(Idx))
continue;
if (!isValidElementType(Idx->getType()))
continue;
if (GEP->getType()->isVectorTy())
continue;
GEPs[GEP->getPointerOperand()].push_back(GEP);
}
}
}
bool SLPVectorizerPass::tryToVectorizePair(Value *A, Value *B, BoUpSLP &R) {
if (!A || !B)
return false;
Value *VL[] = { A, B };
return tryToVectorizeList(VL, R, /*UserCost=*/0, true);
}
bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R,
int UserCost, bool AllowReorder) {
if (VL.size() < 2)
return false;
LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize a list of length = "
<< VL.size() << ".\n");
// Check that all of the parts are scalar instructions of the same type,
// we permit an alternate opcode via InstructionsState.
InstructionsState S = getSameOpcode(VL);
if (!S.getOpcode())
return false;
Instruction *I0 = cast<Instruction>(S.OpValue);
unsigned Sz = R.getVectorElementSize(I0);
unsigned MinVF = std::max(2U, R.getMinVecRegSize() / Sz);
unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF);
if (MaxVF < 2) {
R.getORE()->emit([&]() {
return OptimizationRemarkMissed(SV_NAME, "SmallVF", I0)
<< "Cannot SLP vectorize list: vectorization factor "
<< "less than 2 is not supported";
});
return false;
}
for (Value *V : VL) {
Type *Ty = V->getType();
if (!isValidElementType(Ty)) {
// NOTE: the following will give user internal llvm type name, which may
// not be useful.
R.getORE()->emit([&]() {
std::string type_str;
llvm::raw_string_ostream rso(type_str);
Ty->print(rso);
return OptimizationRemarkMissed(SV_NAME, "UnsupportedType", I0)
<< "Cannot SLP vectorize list: type "
<< rso.str() + " is unsupported by vectorizer";
});
return false;
}
}
bool Changed = false;
bool CandidateFound = false;
int MinCost = SLPCostThreshold;
// Keep track of values that were deleted by vectorizing in the loop below.
SmallVector<WeakTrackingVH, 8> TrackValues(VL.begin(), VL.end());
unsigned NextInst = 0, MaxInst = VL.size();
for (unsigned VF = MaxVF; NextInst + 1 < MaxInst && VF >= MinVF;
VF /= 2) {
// No actual vectorization should happen, if number of parts is the same as
// provided vectorization factor (i.e. the scalar type is used for vector
// code during codegen).
auto *VecTy = VectorType::get(VL[0]->getType(), VF);
if (TTI->getNumberOfParts(VecTy) == VF)
continue;
for (unsigned I = NextInst; I < MaxInst; ++I) {
unsigned OpsWidth = 0;
if (I + VF > MaxInst)
OpsWidth = MaxInst - I;
else
OpsWidth = VF;
if (!isPowerOf2_32(OpsWidth) || OpsWidth < 2)
break;
// Check that a previous iteration of this loop did not delete the Value.
if (hasValueBeenRAUWed(VL, TrackValues, I, OpsWidth))
continue;
LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations "
<< "\n");
ArrayRef<Value *> Ops = VL.slice(I, OpsWidth);
R.buildTree(Ops);
Optional<ArrayRef<unsigned>> Order = R.bestOrder();
// TODO: check if we can allow reordering for more cases.
if (AllowReorder && Order) {
// TODO: reorder tree nodes without tree rebuilding.
// Conceptually, there is nothing actually preventing us from trying to
// reorder a larger list. In fact, we do exactly this when vectorizing
// reductions. However, at this point, we only expect to get here when
// there are exactly two operations.
assert(Ops.size() == 2);
Value *ReorderedOps[] = {Ops[1], Ops[0]};
R.buildTree(ReorderedOps, None);
}
if (R.isTreeTinyAndNotFullyVectorizable())
continue;
R.computeMinimumValueSizes();
int Cost = R.getTreeCost() - UserCost;
CandidateFound = true;
MinCost = std::min(MinCost, Cost);
if (Cost < -SLPCostThreshold) {
LLVM_DEBUG(dbgs() << "SLP: Vectorizing list at cost:" << Cost << ".\n");
R.getORE()->emit(OptimizationRemark(SV_NAME, "VectorizedList",
cast<Instruction>(Ops[0]))
<< "SLP vectorized with cost " << ore::NV("Cost", Cost)
<< " and with tree size "
<< ore::NV("TreeSize", R.getTreeSize()));
R.vectorizeTree();
// Move to the next bundle.
I += VF - 1;
NextInst = I + 1;
Changed = true;
}
}
}
if (!Changed && CandidateFound) {
R.getORE()->emit([&]() {
return OptimizationRemarkMissed(SV_NAME, "NotBeneficial", I0)
<< "List vectorization was possible but not beneficial with cost "
<< ore::NV("Cost", MinCost) << " >= "
<< ore::NV("Treshold", -SLPCostThreshold);
});
} else if (!Changed) {
R.getORE()->emit([&]() {
return OptimizationRemarkMissed(SV_NAME, "NotPossible", I0)
<< "Cannot SLP vectorize list: vectorization was impossible"
<< " with available vectorization factors";
});
}
return Changed;
}
bool SLPVectorizerPass::tryToVectorize(Instruction *I, BoUpSLP &R) {
if (!I)
return false;
if (!isa<BinaryOperator>(I) && !isa<CmpInst>(I))
return false;
Value *P = I->getParent();
// Vectorize in current basic block only.
auto *Op0 = dyn_cast<Instruction>(I->getOperand(0));
auto *Op1 = dyn_cast<Instruction>(I->getOperand(1));
if (!Op0 || !Op1 || Op0->getParent() != P || Op1->getParent() != P)
return false;
// Try to vectorize V.
if (tryToVectorizePair(Op0, Op1, R))
return true;
auto *A = dyn_cast<BinaryOperator>(Op0);
auto *B = dyn_cast<BinaryOperator>(Op1);
// Try to skip B.
if (B && B->hasOneUse()) {
auto *B0 = dyn_cast<BinaryOperator>(B->getOperand(0));
auto *B1 = dyn_cast<BinaryOperator>(B->getOperand(1));
if (B0 && B0->getParent() == P && tryToVectorizePair(A, B0, R))
return true;
if (B1 && B1->getParent() == P && tryToVectorizePair(A, B1, R))
return true;
}
// Try to skip A.
if (A && A->hasOneUse()) {
auto *A0 = dyn_cast<BinaryOperator>(A->getOperand(0));
auto *A1 = dyn_cast<BinaryOperator>(A->getOperand(1));
if (A0 && A0->getParent() == P && tryToVectorizePair(A0, B, R))
return true;
if (A1 && A1->getParent() == P && tryToVectorizePair(A1, B, R))
return true;
}
return false;
}
/// Generate a shuffle mask to be used in a reduction tree.
///
/// \param VecLen The length of the vector to be reduced.
/// \param NumEltsToRdx The number of elements that should be reduced in the
/// vector.
/// \param IsPairwise Whether the reduction is a pairwise or splitting
/// reduction. A pairwise reduction will generate a mask of
/// <0,2,...> or <1,3,..> while a splitting reduction will generate
/// <2,3, undef,undef> for a vector of 4 and NumElts = 2.
/// \param IsLeft True will generate a mask of even elements, odd otherwise.
static Value *createRdxShuffleMask(unsigned VecLen, unsigned NumEltsToRdx,
bool IsPairwise, bool IsLeft,
IRBuilder<> &Builder) {
assert((IsPairwise || !IsLeft) && "Don't support a <0,1,undef,...> mask");
SmallVector<Constant *, 32> ShuffleMask(
VecLen, UndefValue::get(Builder.getInt32Ty()));
if (IsPairwise)
// Build a mask of 0, 2, ... (left) or 1, 3, ... (right).
for (unsigned i = 0; i != NumEltsToRdx; ++i)
ShuffleMask[i] = Builder.getInt32(2 * i + !IsLeft);
else
// Move the upper half of the vector to the lower half.
for (unsigned i = 0; i != NumEltsToRdx; ++i)
ShuffleMask[i] = Builder.getInt32(NumEltsToRdx + i);
return ConstantVector::get(ShuffleMask);
}
namespace {
/// Model horizontal reductions.
///
/// A horizontal reduction is a tree of reduction operations (currently add and
/// fadd) that has operations that can be put into a vector as its leaf.
/// For example, this tree:
///
/// mul mul mul mul
/// \ / \ /
/// + +
/// \ /
/// +
/// This tree has "mul" as its reduced values and "+" as its reduction
/// operations. A reduction might be feeding into a store or a binary operation
/// feeding a phi.
/// ...
/// \ /
/// +
/// |
/// phi +=
///
/// Or:
/// ...
/// \ /
/// +
/// |
/// *p =
///
class HorizontalReduction {
using ReductionOpsType = SmallVector<Value *, 16>;
using ReductionOpsListType = SmallVector<ReductionOpsType, 2>;
ReductionOpsListType ReductionOps;
SmallVector<Value *, 32> ReducedVals;
// Use map vector to make stable output.
MapVector<Instruction *, Value *> ExtraArgs;
/// Kind of the reduction data.
enum ReductionKind {
RK_None, /// Not a reduction.
RK_Arithmetic, /// Binary reduction data.
RK_Min, /// Minimum reduction data.
RK_UMin, /// Unsigned minimum reduction data.
RK_Max, /// Maximum reduction data.
RK_UMax, /// Unsigned maximum reduction data.
};
/// Contains info about operation, like its opcode, left and right operands.
class OperationData {
/// Opcode of the instruction.
unsigned Opcode = 0;
/// Left operand of the reduction operation.
Value *LHS = nullptr;
/// Right operand of the reduction operation.
Value *RHS = nullptr;
/// Kind of the reduction operation.
ReductionKind Kind = RK_None;
/// True if float point min/max reduction has no NaNs.
bool NoNaN = false;
/// Checks if the reduction operation can be vectorized.
bool isVectorizable() const {
return LHS && RHS &&
// We currently only support add/mul/logical && min/max reductions.
((Kind == RK_Arithmetic &&
(Opcode == Instruction::Add || Opcode == Instruction::FAdd ||
Opcode == Instruction::Mul || Opcode == Instruction::FMul ||
Opcode == Instruction::And || Opcode == Instruction::Or ||
Opcode == Instruction::Xor)) ||
((Opcode == Instruction::ICmp || Opcode == Instruction::FCmp) &&
(Kind == RK_Min || Kind == RK_Max)) ||
(Opcode == Instruction::ICmp &&
(Kind == RK_UMin || Kind == RK_UMax)));
}
/// Creates reduction operation with the current opcode.
Value *createOp(IRBuilder<> &Builder, const Twine &Name) const {
assert(isVectorizable() &&
"Expected add|fadd or min/max reduction operation.");
Value *Cmp;
switch (Kind) {
case RK_Arithmetic:
return Builder.CreateBinOp((Instruction::BinaryOps)Opcode, LHS, RHS,
Name);
case RK_Min:
Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSLT(LHS, RHS)
: Builder.CreateFCmpOLT(LHS, RHS);
break;
case RK_Max:
Cmp = Opcode == Instruction::ICmp ? Builder.CreateICmpSGT(LHS, RHS)
: Builder.CreateFCmpOGT(LHS, RHS);
break;
case RK_UMin:
assert(Opcode == Instruction::ICmp && "Expected integer types.");
Cmp = Builder.CreateICmpULT(LHS, RHS);
break;
case RK_UMax:
assert(Opcode == Instruction::ICmp && "Expected integer types.");
Cmp = Builder.CreateICmpUGT(LHS, RHS);
break;
case RK_None:
llvm_unreachable("Unknown reduction operation.");
}
return Builder.CreateSelect(Cmp, LHS, RHS, Name);
}
public:
explicit OperationData() = default;
/// Construction for reduced values. They are identified by opcode only and
/// don't have associated LHS/RHS values.
explicit OperationData(Value *V) {
if (auto *I = dyn_cast<Instruction>(V))
Opcode = I->getOpcode();
}
/// Constructor for reduction operations with opcode and its left and
/// right operands.
OperationData(unsigned Opcode, Value *LHS, Value *RHS, ReductionKind Kind,
bool NoNaN = false)
: Opcode(Opcode), LHS(LHS), RHS(RHS), Kind(Kind), NoNaN(NoNaN) {
assert(Kind != RK_None && "One of the reduction operations is expected.");
}
explicit operator bool() const { return Opcode; }
/// Get the index of the first operand.
unsigned getFirstOperandIndex() const {
assert(!!*this && "The opcode is not set.");
switch (Kind) {
case RK_Min:
case RK_UMin:
case RK_Max:
case RK_UMax:
return 1;
case RK_Arithmetic:
case RK_None:
break;
}
return 0;
}
/// Total number of operands in the reduction operation.
unsigned getNumberOfOperands() const {
assert(Kind != RK_None && !!*this && LHS && RHS &&
"Expected reduction operation.");
switch (Kind) {
case RK_Arithmetic:
return 2;
case RK_Min:
case RK_UMin:
case RK_Max:
case RK_UMax:
return 3;
case RK_None:
break;
}
llvm_unreachable("Reduction kind is not set");
}
/// Checks if the operation has the same parent as \p P.
bool hasSameParent(Instruction *I, Value *P, bool IsRedOp) const {
assert(Kind != RK_None && !!*this && LHS && RHS &&
"Expected reduction operation.");
if (!IsRedOp)
return I->getParent() == P;
switch (Kind) {
case RK_Arithmetic:
// Arithmetic reduction operation must be used once only.
return I->getParent() == P;
case RK_Min:
case RK_UMin:
case RK_Max:
case RK_UMax: {
// SelectInst must be used twice while the condition op must have single
// use only.
auto *Cmp = cast<Instruction>(cast<SelectInst>(I)->getCondition());
return I->getParent() == P && Cmp && Cmp->getParent() == P;
}
case RK_None:
break;
}
llvm_unreachable("Reduction kind is not set");
}
/// Expected number of uses for reduction operations/reduced values.
bool hasRequiredNumberOfUses(Instruction *I, bool IsReductionOp) const {
assert(Kind != RK_None && !!*this && LHS && RHS &&
"Expected reduction operation.");
switch (Kind) {
case RK_Arithmetic:
return I->hasOneUse();
case RK_Min:
case RK_UMin:
case RK_Max:
case RK_UMax:
return I->hasNUses(2) &&
(!IsReductionOp ||
cast<SelectInst>(I)->getCondition()->hasOneUse());
case RK_None:
break;
}
llvm_unreachable("Reduction kind is not set");
}
/// Initializes the list of reduction operations.
void initReductionOps(ReductionOpsListType &ReductionOps) {
assert(Kind != RK_None && !!*this && LHS && RHS &&
"Expected reduction operation.");
switch (Kind) {
case RK_Arithmetic:
ReductionOps.assign(1, ReductionOpsType());
break;
case RK_Min:
case RK_UMin:
case RK_Max:
case RK_UMax:
ReductionOps.assign(2, ReductionOpsType());
break;
case RK_None:
llvm_unreachable("Reduction kind is not set");
}
}
/// Add all reduction operations for the reduction instruction \p I.
void addReductionOps(Instruction *I, ReductionOpsListType &ReductionOps) {
assert(Kind != RK_None && !!*this && LHS && RHS &&
"Expected reduction operation.");
switch (Kind) {
case RK_Arithmetic:
ReductionOps[0].emplace_back(I);
break;
case RK_Min:
case RK_UMin:
case RK_Max:
case RK_UMax:
ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition());
ReductionOps[1].emplace_back(I);
break;
case RK_None:
llvm_unreachable("Reduction kind is not set");
}
}
/// Checks if instruction is associative and can be vectorized.
bool isAssociative(Instruction *I) const {
assert(Kind != RK_None && *this && LHS && RHS &&
"Expected reduction operation.");
switch (Kind) {
case RK_Arithmetic:
return I->isAssociative();
case RK_Min:
case RK_Max:
return Opcode == Instruction::ICmp ||
cast<Instruction>(I->getOperand(0))->isFast();
case RK_UMin:
case RK_UMax:
assert(Opcode == Instruction::ICmp &&
"Only integer compare operation is expected.");
return true;
case RK_None:
break;
}
llvm_unreachable("Reduction kind is not set");
}
/// Checks if the reduction operation can be vectorized.
bool isVectorizable(Instruction *I) const {
return isVectorizable() && isAssociative(I);
}
/// Checks if two operation data are both a reduction op or both a reduced
/// value.
bool operator==(const OperationData &OD) {
assert(((Kind != OD.Kind) || ((!LHS == !OD.LHS) && (!RHS == !OD.RHS))) &&
"One of the comparing operations is incorrect.");
return this == &OD || (Kind == OD.Kind && Opcode == OD.Opcode);
}
bool operator!=(const OperationData &OD) { return !(*this == OD); }
void clear() {
Opcode = 0;
LHS = nullptr;
RHS = nullptr;
Kind = RK_None;
NoNaN = false;
}
/// Get the opcode of the reduction operation.
unsigned getOpcode() const {
assert(isVectorizable() && "Expected vectorizable operation.");
return Opcode;
}
/// Get kind of reduction data.
ReductionKind getKind() const { return Kind; }
Value *getLHS() const { return LHS; }
Value *getRHS() const { return RHS; }
Type *getConditionType() const {
switch (Kind) {
case RK_Arithmetic:
return nullptr;
case RK_Min:
case RK_Max:
case RK_UMin:
case RK_UMax:
return CmpInst::makeCmpResultType(LHS->getType());
case RK_None:
break;
}
llvm_unreachable("Reduction kind is not set");
}
/// Creates reduction operation with the current opcode with the IR flags
/// from \p ReductionOps.
Value *createOp(IRBuilder<> &Builder, const Twine &Name,
const ReductionOpsListType &ReductionOps) const {
assert(isVectorizable() &&
"Expected add|fadd or min/max reduction operation.");
auto *Op = createOp(Builder, Name);
switch (Kind) {
case RK_Arithmetic:
propagateIRFlags(Op, ReductionOps[0]);
return Op;
case RK_Min:
case RK_Max:
case RK_UMin:
case RK_UMax:
if (auto *SI = dyn_cast<SelectInst>(Op))
propagateIRFlags(SI->getCondition(), ReductionOps[0]);
propagateIRFlags(Op, ReductionOps[1]);
return Op;
case RK_None:
break;
}
llvm_unreachable("Unknown reduction operation.");
}
/// Creates reduction operation with the current opcode with the IR flags
/// from \p I.
Value *createOp(IRBuilder<> &Builder, const Twine &Name,
Instruction *I) const {
assert(isVectorizable() &&
"Expected add|fadd or min/max reduction operation.");
auto *Op = createOp(Builder, Name);
switch (Kind) {
case RK_Arithmetic:
propagateIRFlags(Op, I);
return Op;
case RK_Min:
case RK_Max:
case RK_UMin:
case RK_UMax:
if (auto *SI = dyn_cast<SelectInst>(Op)) {
propagateIRFlags(SI->getCondition(),
cast<SelectInst>(I)->getCondition());
}
propagateIRFlags(Op, I);
return Op;
case RK_None:
break;
}
llvm_unreachable("Unknown reduction operation.");
}
TargetTransformInfo::ReductionFlags getFlags() const {
TargetTransformInfo::ReductionFlags Flags;
Flags.NoNaN = NoNaN;
switch (Kind) {
case RK_Arithmetic:
break;
case RK_Min:
Flags.IsSigned = Opcode == Instruction::ICmp;
Flags.IsMaxOp = false;
break;
case RK_Max:
Flags.IsSigned = Opcode == Instruction::ICmp;
Flags.IsMaxOp = true;
break;
case RK_UMin:
Flags.IsSigned = false;
Flags.IsMaxOp = false;
break;
case RK_UMax:
Flags.IsSigned = false;
Flags.IsMaxOp = true;
break;
case RK_None:
llvm_unreachable("Reduction kind is not set");
}
return Flags;
}
};
WeakTrackingVH ReductionRoot;
/// The operation data of the reduction operation.
OperationData ReductionData;
/// The operation data of the values we perform a reduction on.
OperationData ReducedValueData;
/// Should we model this reduction as a pairwise reduction tree or a tree that
/// splits the vector in halves and adds those halves.
bool IsPairwiseReduction = false;
/// Checks if the ParentStackElem.first should be marked as a reduction
/// operation with an extra argument or as extra argument itself.
void markExtraArg(std::pair<Instruction *, unsigned> &ParentStackElem,
Value *ExtraArg) {
if (ExtraArgs.count(ParentStackElem.first)) {
ExtraArgs[ParentStackElem.first] = nullptr;
// We ran into something like:
// ParentStackElem.first = ExtraArgs[ParentStackElem.first] + ExtraArg.
// The whole ParentStackElem.first should be considered as an extra value
// in this case.
// Do not perform analysis of remaining operands of ParentStackElem.first
// instruction, this whole instruction is an extra argument.
ParentStackElem.second = ParentStackElem.first->getNumOperands();
} else {
// We ran into something like:
// ParentStackElem.first += ... + ExtraArg + ...
ExtraArgs[ParentStackElem.first] = ExtraArg;
}
}
static OperationData getOperationData(Value *V) {
if (!V)
return OperationData();
Value *LHS;
Value *RHS;
if (m_BinOp(m_Value(LHS), m_Value(RHS)).match(V)) {
return OperationData(cast<BinaryOperator>(V)->getOpcode(), LHS, RHS,
RK_Arithmetic);
}
if (auto *Select = dyn_cast<SelectInst>(V)) {
// Look for a min/max pattern.
if (m_UMin(m_Value(LHS), m_Value(RHS)).match(Select)) {
return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin);
} else if (m_SMin(m_Value(LHS), m_Value(RHS)).match(Select)) {
return OperationData(Instruction::ICmp, LHS, RHS, RK_Min);
} else if (m_OrdFMin(m_Value(LHS), m_Value(RHS)).match(Select) ||
m_UnordFMin(m_Value(LHS), m_Value(RHS)).match(Select)) {
return OperationData(
Instruction::FCmp, LHS, RHS, RK_Min,
cast<Instruction>(Select->getCondition())->hasNoNaNs());
} else if (m_UMax(m_Value(LHS), m_Value(RHS)).match(Select)) {
return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax);
} else if (m_SMax(m_Value(LHS), m_Value(RHS)).match(Select)) {
return OperationData(Instruction::ICmp, LHS, RHS, RK_Max);
} else if (m_OrdFMax(m_Value(LHS), m_Value(RHS)).match(Select) ||
m_UnordFMax(m_Value(LHS), m_Value(RHS)).match(Select)) {
return OperationData(
Instruction::FCmp, LHS, RHS, RK_Max,
cast<Instruction>(Select->getCondition())->hasNoNaNs());
} else {
// Try harder: look for min/max pattern based on instructions producing
// same values such as: select ((cmp Inst1, Inst2), Inst1, Inst2).
// During the intermediate stages of SLP, it's very common to have
// pattern like this (since optimizeGatherSequence is run only once
// at the end):
// %1 = extractelement <2 x i32> %a, i32 0
// %2 = extractelement <2 x i32> %a, i32 1
// %cond = icmp sgt i32 %1, %2
// %3 = extractelement <2 x i32> %a, i32 0
// %4 = extractelement <2 x i32> %a, i32 1
// %select = select i1 %cond, i32 %3, i32 %4
CmpInst::Predicate Pred;
Instruction *L1;
Instruction *L2;
LHS = Select->getTrueValue();
RHS = Select->getFalseValue();
Value *Cond = Select->getCondition();
// TODO: Support inverse predicates.
if (match(Cond, m_Cmp(Pred, m_Specific(LHS), m_Instruction(L2)))) {
if (!isa<ExtractElementInst>(RHS) ||
!L2->isIdenticalTo(cast<Instruction>(RHS)))
return OperationData(V);
} else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) {
if (!isa<ExtractElementInst>(LHS) ||
!L1->isIdenticalTo(cast<Instruction>(LHS)))
return OperationData(V);
} else {
if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS))
return OperationData(V);
if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) ||
!L1->isIdenticalTo(cast<Instruction>(LHS)) ||
!L2->isIdenticalTo(cast<Instruction>(RHS)))
return OperationData(V);
}
switch (Pred) {
default:
return OperationData(V);
case CmpInst::ICMP_ULT:
case CmpInst::ICMP_ULE:
return OperationData(Instruction::ICmp, LHS, RHS, RK_UMin);
case CmpInst::ICMP_SLT:
case CmpInst::ICMP_SLE:
return OperationData(Instruction::ICmp, LHS, RHS, RK_Min);
case CmpInst::FCMP_OLT:
case CmpInst::FCMP_OLE:
case CmpInst::FCMP_ULT:
case CmpInst::FCMP_ULE:
return OperationData(Instruction::FCmp, LHS, RHS, RK_Min,
cast<Instruction>(Cond)->hasNoNaNs());
case CmpInst::ICMP_UGT:
case CmpInst::ICMP_UGE:
return OperationData(Instruction::ICmp, LHS, RHS, RK_UMax);
case CmpInst::ICMP_SGT:
case CmpInst::ICMP_SGE:
return OperationData(Instruction::ICmp, LHS, RHS, RK_Max);
case CmpInst::FCMP_OGT:
case CmpInst::FCMP_OGE:
case CmpInst::FCMP_UGT:
case CmpInst::FCMP_UGE:
return OperationData(Instruction::FCmp, LHS, RHS, RK_Max,
cast<Instruction>(Cond)->hasNoNaNs());
}
}
}
return OperationData(V);
}
public:
HorizontalReduction() = default;
/// Try to find a reduction tree.
bool matchAssociativeReduction(PHINode *Phi, Instruction *B) {
assert((!Phi || is_contained(Phi->operands(), B)) &&
"Thi phi needs to use the binary operator");
ReductionData = getOperationData(B);
// We could have a initial reductions that is not an add.
// r *= v1 + v2 + v3 + v4
// In such a case start looking for a tree rooted in the first '+'.
if (Phi) {
if (ReductionData.getLHS() == Phi) {
Phi = nullptr;
B = dyn_cast<Instruction>(ReductionData.getRHS());
ReductionData = getOperationData(B);
} else if (ReductionData.getRHS() == Phi) {
Phi = nullptr;
B = dyn_cast<Instruction>(ReductionData.getLHS());
ReductionData = getOperationData(B);
}
}
if (!ReductionData.isVectorizable(B))
return false;
Type *Ty = B->getType();
if (!isValidElementType(Ty))
return false;
if (!Ty->isIntOrIntVectorTy() && !Ty->isFPOrFPVectorTy())
return false;
ReducedValueData.clear();
ReductionRoot = B;
// Post order traverse the reduction tree starting at B. We only handle true
// trees containing only binary operators.
SmallVector<std::pair<Instruction *, unsigned>, 32> Stack;
Stack.push_back(std::make_pair(B, ReductionData.getFirstOperandIndex()));
ReductionData.initReductionOps(ReductionOps);
while (!Stack.empty()) {
Instruction *TreeN = Stack.back().first;
unsigned EdgeToVist = Stack.back().second++;
OperationData OpData = getOperationData(TreeN);
bool IsReducedValue = OpData != ReductionData;
// Postorder vist.
if (IsReducedValue || EdgeToVist == OpData.getNumberOfOperands()) {
if (IsReducedValue)
ReducedVals.push_back(TreeN);
else {
auto I = ExtraArgs.find(TreeN);
if (I != ExtraArgs.end() && !I->second) {
// Check if TreeN is an extra argument of its parent operation.
if (Stack.size() <= 1) {
// TreeN can't be an extra argument as it is a root reduction
// operation.
return false;
}
// Yes, TreeN is an extra argument, do not add it to a list of
// reduction operations.
// Stack[Stack.size() - 2] always points to the parent operation.
markExtraArg(Stack[Stack.size() - 2], TreeN);
ExtraArgs.erase(TreeN);
} else
ReductionData.addReductionOps(TreeN, ReductionOps);
}
// Retract.
Stack.pop_back();
continue;
}
// Visit left or right.
Value *NextV = TreeN->getOperand(EdgeToVist);
if (NextV != Phi) {
auto *I = dyn_cast<Instruction>(NextV);
OpData = getOperationData(I);
// Continue analysis if the next operand is a reduction operation or
// (possibly) a reduced value. If the reduced value opcode is not set,
// the first met operation != reduction operation is considered as the
// reduced value class.
if (I && (!ReducedValueData || OpData == ReducedValueData ||
OpData == ReductionData)) {
const bool IsReductionOperation = OpData == ReductionData;
// Only handle trees in the current basic block.
if (!ReductionData.hasSameParent(I, B->getParent(),
IsReductionOperation)) {
// I is an extra argument for TreeN (its parent operation).
markExtraArg(Stack.back(), I);
continue;
}
// Each tree node needs to have minimal number of users except for the
// ultimate reduction.
if (!ReductionData.hasRequiredNumberOfUses(I,
OpData == ReductionData) &&
I != B) {
// I is an extra argument for TreeN (its parent operation).
markExtraArg(Stack.back(), I);
continue;
}
if (IsReductionOperation) {
// We need to be able to reassociate the reduction operations.
if (!OpData.isAssociative(I)) {
// I is an extra argument for TreeN (its parent operation).
markExtraArg(Stack.back(), I);
continue;
}
} else if (ReducedValueData &&
ReducedValueData != OpData) {
// Make sure that the opcodes of the operations that we are going to
// reduce match.
// I is an extra argument for TreeN (its parent operation).
markExtraArg(Stack.back(), I);
continue;
} else if (!ReducedValueData)
ReducedValueData = OpData;
Stack.push_back(std::make_pair(I, OpData.getFirstOperandIndex()));
continue;
}
}
// NextV is an extra argument for TreeN (its parent operation).
markExtraArg(Stack.back(), NextV);
}
return true;
}
/// Attempt to vectorize the tree found by
/// matchAssociativeReduction.
bool tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) {
if (ReducedVals.empty())
return false;
// If there is a sufficient number of reduction values, reduce
// to a nearby power-of-2. Can safely generate oversized
// vectors and rely on the backend to split them to legal sizes.
unsigned NumReducedVals = ReducedVals.size();
if (NumReducedVals < 4)
return false;
unsigned ReduxWidth = PowerOf2Floor(NumReducedVals);
Value *VectorizedTree = nullptr;
IRBuilder<> Builder(cast<Instruction>(ReductionRoot));
FastMathFlags Unsafe;
Unsafe.setFast();
Builder.setFastMathFlags(Unsafe);
unsigned i = 0;
BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues;
// The same extra argument may be used several time, so log each attempt
// to use it.
for (auto &Pair : ExtraArgs) {
assert(Pair.first && "DebugLoc must be set.");
ExternallyUsedValues[Pair.second].push_back(Pair.first);
}
// The reduction root is used as the insertion point for new instructions,
// so set it as externally used to prevent it from being deleted.
ExternallyUsedValues[ReductionRoot];
SmallVector<Value *, 16> IgnoreList;
for (auto &V : ReductionOps)
IgnoreList.append(V.begin(), V.end());
while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) {
auto VL = makeArrayRef(&ReducedVals[i], ReduxWidth);
V.buildTree(VL, ExternallyUsedValues, IgnoreList);
Optional<ArrayRef<unsigned>> Order = V.bestOrder();
// TODO: Handle orders of size less than number of elements in the vector.
if (Order && Order->size() == VL.size()) {
// TODO: reorder tree nodes without tree rebuilding.
SmallVector<Value *, 4> ReorderedOps(VL.size());
llvm::transform(*Order, ReorderedOps.begin(),
[VL](const unsigned Idx) { return VL[Idx]; });
V.buildTree(ReorderedOps, ExternallyUsedValues, IgnoreList);
}
if (V.isTreeTinyAndNotFullyVectorizable())
break;
V.computeMinimumValueSizes();
// Estimate cost.
int TreeCost = V.getTreeCost();
int ReductionCost = getReductionCost(TTI, ReducedVals[i], ReduxWidth);
int Cost = TreeCost + ReductionCost;
if (Cost >= -SLPCostThreshold) {
V.getORE()->emit([&]() {
return OptimizationRemarkMissed(
SV_NAME, "HorSLPNotBeneficial", cast<Instruction>(VL[0]))
<< "Vectorizing horizontal reduction is possible"
<< "but not beneficial with cost "
<< ore::NV("Cost", Cost) << " and threshold "
<< ore::NV("Threshold", -SLPCostThreshold);
});
break;
}
LLVM_DEBUG(dbgs() << "SLP: Vectorizing horizontal reduction at cost:"
<< Cost << ". (HorRdx)\n");
V.getORE()->emit([&]() {
return OptimizationRemark(
SV_NAME, "VectorizedHorizontalReduction", cast<Instruction>(VL[0]))
<< "Vectorized horizontal reduction with cost "
<< ore::NV("Cost", Cost) << " and with tree size "
<< ore::NV("TreeSize", V.getTreeSize());
});
// Vectorize a tree.
DebugLoc Loc = cast<Instruction>(ReducedVals[i])->getDebugLoc();
Value *VectorizedRoot = V.vectorizeTree(ExternallyUsedValues);
// Emit a reduction.
Builder.SetInsertPoint(cast<Instruction>(ReductionRoot));
Value *ReducedSubTree =
emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI);
if (VectorizedTree) {
Builder.SetCurrentDebugLocation(Loc);
OperationData VectReductionData(ReductionData.getOpcode(),
VectorizedTree, ReducedSubTree,
ReductionData.getKind());
VectorizedTree =
VectReductionData.createOp(Builder, "op.rdx", ReductionOps);
} else
VectorizedTree = ReducedSubTree;
i += ReduxWidth;
ReduxWidth = PowerOf2Floor(NumReducedVals - i);
}
if (VectorizedTree) {
// Finish the reduction.
for (; i < NumReducedVals; ++i) {
auto *I = cast<Instruction>(ReducedVals[i]);
Builder.SetCurrentDebugLocation(I->getDebugLoc());
OperationData VectReductionData(ReductionData.getOpcode(),
VectorizedTree, I,
ReductionData.getKind());
VectorizedTree = VectReductionData.createOp(Builder, "", ReductionOps);
}
for (auto &Pair : ExternallyUsedValues) {
// Add each externally used value to the final reduction.
for (auto *I : Pair.second) {
Builder.SetCurrentDebugLocation(I->getDebugLoc());
OperationData VectReductionData(ReductionData.getOpcode(),
VectorizedTree, Pair.first,
ReductionData.getKind());
VectorizedTree = VectReductionData.createOp(Builder, "op.extra", I);
}
}
// Update users.
ReductionRoot->replaceAllUsesWith(VectorizedTree);
}
return VectorizedTree != nullptr;
}
unsigned numReductionValues() const {
return ReducedVals.size();
}
private:
/// Calculate the cost of a reduction.
int getReductionCost(TargetTransformInfo *TTI, Value *FirstReducedVal,
unsigned ReduxWidth) {
Type *ScalarTy = FirstReducedVal->getType();
Type *VecTy = VectorType::get(ScalarTy, ReduxWidth);
int PairwiseRdxCost;
int SplittingRdxCost;
switch (ReductionData.getKind()) {
case RK_Arithmetic:
PairwiseRdxCost =
TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy,
/*IsPairwiseForm=*/true);
SplittingRdxCost =
TTI->getArithmeticReductionCost(ReductionData.getOpcode(), VecTy,
/*IsPairwiseForm=*/false);
break;
case RK_Min:
case RK_Max:
case RK_UMin:
case RK_UMax: {
Type *VecCondTy = CmpInst::makeCmpResultType(VecTy);
bool IsUnsigned = ReductionData.getKind() == RK_UMin ||
ReductionData.getKind() == RK_UMax;
PairwiseRdxCost =
TTI->getMinMaxReductionCost(VecTy, VecCondTy,
/*IsPairwiseForm=*/true, IsUnsigned);
SplittingRdxCost =
TTI->getMinMaxReductionCost(VecTy, VecCondTy,
/*IsPairwiseForm=*/false, IsUnsigned);
break;
}
case RK_None:
llvm_unreachable("Expected arithmetic or min/max reduction operation");
}
IsPairwiseReduction = PairwiseRdxCost < SplittingRdxCost;
int VecReduxCost = IsPairwiseReduction ? PairwiseRdxCost : SplittingRdxCost;
int ScalarReduxCost;
switch (ReductionData.getKind()) {
case RK_Arithmetic:
ScalarReduxCost =
TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy);
break;
case RK_Min:
case RK_Max:
case RK_UMin:
case RK_UMax:
ScalarReduxCost =
TTI->getCmpSelInstrCost(ReductionData.getOpcode(), ScalarTy) +
TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy,
CmpInst::makeCmpResultType(ScalarTy));
break;
case RK_None:
llvm_unreachable("Expected arithmetic or min/max reduction operation");
}
ScalarReduxCost *= (ReduxWidth - 1);
LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VecReduxCost - ScalarReduxCost
<< " for reduction that starts with " << *FirstReducedVal
<< " (It is a "
<< (IsPairwiseReduction ? "pairwise" : "splitting")
<< " reduction)\n");
return VecReduxCost - ScalarReduxCost;
}
/// Emit a horizontal reduction of the vectorized value.
Value *emitReduction(Value *VectorizedValue, IRBuilder<> &Builder,
unsigned ReduxWidth, const TargetTransformInfo *TTI) {
assert(VectorizedValue && "Need to have a vectorized tree node");
assert(isPowerOf2_32(ReduxWidth) &&
"We only handle power-of-two reductions for now");
if (!IsPairwiseReduction)
return createSimpleTargetReduction(
Builder, TTI, ReductionData.getOpcode(), VectorizedValue,
ReductionData.getFlags(), FastMathFlags::getFast(),
ReductionOps.back());
Value *TmpVec = VectorizedValue;
for (unsigned i = ReduxWidth / 2; i != 0; i >>= 1) {
Value *LeftMask =
createRdxShuffleMask(ReduxWidth, i, true, true, Builder);
Value *RightMask =
createRdxShuffleMask(ReduxWidth, i, true, false, Builder);
Value *LeftShuf = Builder.CreateShuffleVector(
TmpVec, UndefValue::get(TmpVec->getType()), LeftMask, "rdx.shuf.l");
Value *RightShuf = Builder.CreateShuffleVector(
TmpVec, UndefValue::get(TmpVec->getType()), (RightMask),
"rdx.shuf.r");
OperationData VectReductionData(ReductionData.getOpcode(), LeftShuf,
RightShuf, ReductionData.getKind());
TmpVec = VectReductionData.createOp(Builder, "op.rdx", ReductionOps);
}
// The result is in the first element of the vector.
return Builder.CreateExtractElement(TmpVec, Builder.getInt32(0));
}
};
} // end anonymous namespace
/// Recognize construction of vectors like
/// %ra = insertelement <4 x float> undef, float %s0, i32 0
/// %rb = insertelement <4 x float> %ra, float %s1, i32 1
/// %rc = insertelement <4 x float> %rb, float %s2, i32 2
/// %rd = insertelement <4 x float> %rc, float %s3, i32 3
/// starting from the last insertelement instruction.
///
/// Returns true if it matches
static bool findBuildVector(InsertElementInst *LastInsertElem,
TargetTransformInfo *TTI,
SmallVectorImpl<Value *> &BuildVectorOpds,
int &UserCost) {
UserCost = 0;
Value *V = nullptr;
do {
if (auto *CI = dyn_cast<ConstantInt>(LastInsertElem->getOperand(2))) {
UserCost += TTI->getVectorInstrCost(Instruction::InsertElement,
LastInsertElem->getType(),
CI->getZExtValue());
}
BuildVectorOpds.push_back(LastInsertElem->getOperand(1));
V = LastInsertElem->getOperand(0);
if (isa<UndefValue>(V))
break;
LastInsertElem = dyn_cast<InsertElementInst>(V);
if (!LastInsertElem || !LastInsertElem->hasOneUse())
return false;
} while (true);
std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end());
return true;
}
/// Like findBuildVector, but looks for construction of aggregate.
///
/// \return true if it matches.
static bool findBuildAggregate(InsertValueInst *IV,
SmallVectorImpl<Value *> &BuildVectorOpds) {
Value *V;
do {
BuildVectorOpds.push_back(IV->getInsertedValueOperand());
V = IV->getAggregateOperand();
if (isa<UndefValue>(V))
break;
IV = dyn_cast<InsertValueInst>(V);
if (!IV || !IV->hasOneUse())
return false;
} while (true);
std::reverse(BuildVectorOpds.begin(), BuildVectorOpds.end());
return true;
}
static bool PhiTypeSorterFunc(Value *V, Value *V2) {
return V->getType() < V2->getType();
}
/// Try and get a reduction value from a phi node.
///
/// Given a phi node \p P in a block \p ParentBB, consider possible reductions
/// if they come from either \p ParentBB or a containing loop latch.
///
/// \returns A candidate reduction value if possible, or \code nullptr \endcode
/// if not possible.
static Value *getReductionValue(const DominatorTree *DT, PHINode *P,
BasicBlock *ParentBB, LoopInfo *LI) {
// There are situations where the reduction value is not dominated by the
// reduction phi. Vectorizing such cases has been reported to cause
// miscompiles. See PR25787.
auto DominatedReduxValue = [&](Value *R) {
return isa<Instruction>(R) &&
DT->dominates(P->getParent(), cast<Instruction>(R)->getParent());
};
Value *Rdx = nullptr;
// Return the incoming value if it comes from the same BB as the phi node.
if (P->getIncomingBlock(0) == ParentBB) {
Rdx = P->getIncomingValue(0);
} else if (P->getIncomingBlock(1) == ParentBB) {
Rdx = P->getIncomingValue(1);
}
if (Rdx && DominatedReduxValue(Rdx))
return Rdx;
// Otherwise, check whether we have a loop latch to look at.
Loop *BBL = LI->getLoopFor(ParentBB);
if (!BBL)
return nullptr;
BasicBlock *BBLatch = BBL->getLoopLatch();
if (!BBLatch)
return nullptr;
// There is a loop latch, return the incoming value if it comes from
// that. This reduction pattern occasionally turns up.
if (P->getIncomingBlock(0) == BBLatch) {
Rdx = P->getIncomingValue(0);
} else if (P->getIncomingBlock(1) == BBLatch) {
Rdx = P->getIncomingValue(1);
}
if (Rdx && DominatedReduxValue(Rdx))
return Rdx;
return nullptr;
}
/// Attempt to reduce a horizontal reduction.
/// If it is legal to match a horizontal reduction feeding the phi node \a P
/// with reduction operators \a Root (or one of its operands) in a basic block
/// \a BB, then check if it can be done. If horizontal reduction is not found
/// and root instruction is a binary operation, vectorization of the operands is
/// attempted.
/// \returns true if a horizontal reduction was matched and reduced or operands
/// of one of the binary instruction were vectorized.
/// \returns false if a horizontal reduction was not matched (or not possible)
/// or no vectorization of any binary operation feeding \a Root instruction was
/// performed.
static bool tryToVectorizeHorReductionOrInstOperands(
PHINode *P, Instruction *Root, BasicBlock *BB, BoUpSLP &R,
TargetTransformInfo *TTI,
const function_ref<bool(Instruction *, BoUpSLP &)> Vectorize) {
if (!ShouldVectorizeHor)
return false;
if (!Root)
return false;
if (Root->getParent() != BB || isa<PHINode>(Root))
return false;
// Start analysis starting from Root instruction. If horizontal reduction is
// found, try to vectorize it. If it is not a horizontal reduction or
// vectorization is not possible or not effective, and currently analyzed
// instruction is a binary operation, try to vectorize the operands, using
// pre-order DFS traversal order. If the operands were not vectorized, repeat
// the same procedure considering each operand as a possible root of the
// horizontal reduction.
// Interrupt the process if the Root instruction itself was vectorized or all
// sub-trees not higher that RecursionMaxDepth were analyzed/vectorized.
SmallVector<std::pair<WeakTrackingVH, unsigned>, 8> Stack(1, {Root, 0});
SmallPtrSet<Value *, 8> VisitedInstrs;
bool Res = false;
while (!Stack.empty()) {
Value *V;
unsigned Level;
std::tie(V, Level) = Stack.pop_back_val();
if (!V)
continue;
auto *Inst = dyn_cast<Instruction>(V);
if (!Inst)
continue;
auto *BI = dyn_cast<BinaryOperator>(Inst);
auto *SI = dyn_cast<SelectInst>(Inst);
if (BI || SI) {
HorizontalReduction HorRdx;
if (HorRdx.matchAssociativeReduction(P, Inst)) {
if (HorRdx.tryToReduce(R, TTI)) {
Res = true;
// Set P to nullptr to avoid re-analysis of phi node in
// matchAssociativeReduction function unless this is the root node.
P = nullptr;
continue;
}
}
if (P && BI) {
Inst = dyn_cast<Instruction>(BI->getOperand(0));
if (Inst == P)
Inst = dyn_cast<Instruction>(BI->getOperand(1));
if (!Inst) {
// Set P to nullptr to avoid re-analysis of phi node in
// matchAssociativeReduction function unless this is the root node.
P = nullptr;
continue;
}
}
}
// Set P to nullptr to avoid re-analysis of phi node in
// matchAssociativeReduction function unless this is the root node.
P = nullptr;
if (Vectorize(Inst, R)) {
Res = true;
continue;
}
// Try to vectorize operands.
// Continue analysis for the instruction from the same basic block only to
// save compile time.
if (++Level < RecursionMaxDepth)
for (auto *Op : Inst->operand_values())
if (VisitedInstrs.insert(Op).second)
if (auto *I = dyn_cast<Instruction>(Op))
if (!isa<PHINode>(I) && I->getParent() == BB)
Stack.emplace_back(Op, Level);
}
return Res;
}
bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V,
BasicBlock *BB, BoUpSLP &R,
TargetTransformInfo *TTI) {
if (!V)
return false;
auto *I = dyn_cast<Instruction>(V);
if (!I)
return false;
if (!isa<BinaryOperator>(I))
P = nullptr;
// Try to match and vectorize a horizontal reduction.
auto &&ExtraVectorization = [this](Instruction *I, BoUpSLP &R) -> bool {
return tryToVectorize(I, R);
};
return tryToVectorizeHorReductionOrInstOperands(P, I, BB, R, TTI,
ExtraVectorization);
}
bool SLPVectorizerPass::vectorizeInsertValueInst(InsertValueInst *IVI,
BasicBlock *BB, BoUpSLP &R) {
const DataLayout &DL = BB->getModule()->getDataLayout();
if (!R.canMapToVector(IVI->getType(), DL))
return false;
SmallVector<Value *, 16> BuildVectorOpds;
if (!findBuildAggregate(IVI, BuildVectorOpds))
return false;
LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IVI << "\n");
// Aggregate value is unlikely to be processed in vector register, we need to
// extract scalars into scalar registers, so NeedExtraction is set true.
return tryToVectorizeList(BuildVectorOpds, R);
}
bool SLPVectorizerPass::vectorizeInsertElementInst(InsertElementInst *IEI,
BasicBlock *BB, BoUpSLP &R) {
int UserCost;
SmallVector<Value *, 16> BuildVectorOpds;
if (!findBuildVector(IEI, TTI, BuildVectorOpds, UserCost) ||
(llvm::all_of(BuildVectorOpds,
[](Value *V) { return isa<ExtractElementInst>(V); }) &&
isShuffle(BuildVectorOpds)))
return false;
// Vectorize starting with the build vector operands ignoring the BuildVector
// instructions for the purpose of scheduling and user extraction.
return tryToVectorizeList(BuildVectorOpds, R, UserCost);
}
bool SLPVectorizerPass::vectorizeCmpInst(CmpInst *CI, BasicBlock *BB,
BoUpSLP &R) {
if (tryToVectorizePair(CI->getOperand(0), CI->getOperand(1), R))
return true;
bool OpsChanged = false;
for (int Idx = 0; Idx < 2; ++Idx) {
OpsChanged |=
vectorizeRootInstruction(nullptr, CI->getOperand(Idx), BB, R, TTI);
}
return OpsChanged;
}
bool SLPVectorizerPass::vectorizeSimpleInstructions(
SmallVectorImpl<WeakVH> &Instructions, BasicBlock *BB, BoUpSLP &R) {
bool OpsChanged = false;
for (auto &VH : reverse(Instructions)) {
auto *I = dyn_cast_or_null<Instruction>(VH);
if (!I)
continue;
if (auto *LastInsertValue = dyn_cast<InsertValueInst>(I))
OpsChanged |= vectorizeInsertValueInst(LastInsertValue, BB, R);
else if (auto *LastInsertElem = dyn_cast<InsertElementInst>(I))
OpsChanged |= vectorizeInsertElementInst(LastInsertElem, BB, R);
else if (auto *CI = dyn_cast<CmpInst>(I))
OpsChanged |= vectorizeCmpInst(CI, BB, R);
}
Instructions.clear();
return OpsChanged;
}
bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) {
bool Changed = false;
SmallVector<Value *, 4> Incoming;
SmallPtrSet<Value *, 16> VisitedInstrs;
bool HaveVectorizedPhiNodes = true;
while (HaveVectorizedPhiNodes) {
HaveVectorizedPhiNodes = false;
// Collect the incoming values from the PHIs.
Incoming.clear();
for (Instruction &I : *BB) {
PHINode *P = dyn_cast<PHINode>(&I);
if (!P)
break;
if (!VisitedInstrs.count(P))
Incoming.push_back(P);
}
// Sort by type.
std::stable_sort(Incoming.begin(), Incoming.end(), PhiTypeSorterFunc);
// Try to vectorize elements base on their type.
for (SmallVector<Value *, 4>::iterator IncIt = Incoming.begin(),
E = Incoming.end();
IncIt != E;) {
// Look for the next elements with the same type.
SmallVector<Value *, 4>::iterator SameTypeIt = IncIt;
while (SameTypeIt != E &&
(*SameTypeIt)->getType() == (*IncIt)->getType()) {
VisitedInstrs.insert(*SameTypeIt);
++SameTypeIt;
}
// Try to vectorize them.
unsigned NumElts = (SameTypeIt - IncIt);
LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at PHIs ("
<< NumElts << ")\n");
// The order in which the phi nodes appear in the program does not matter.
// So allow tryToVectorizeList to reorder them if it is beneficial. This
// is done when there are exactly two elements since tryToVectorizeList
// asserts that there are only two values when AllowReorder is true.
bool AllowReorder = NumElts == 2;
if (NumElts > 1 && tryToVectorizeList(makeArrayRef(IncIt, NumElts), R,
/*UserCost=*/0, AllowReorder)) {
// Success start over because instructions might have been changed.
HaveVectorizedPhiNodes = true;
Changed = true;
break;
}
// Start over at the next instruction of a different type (or the end).
IncIt = SameTypeIt;
}
}
VisitedInstrs.clear();
SmallVector<WeakVH, 8> PostProcessInstructions;
SmallDenseSet<Instruction *, 4> KeyNodes;
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; it++) {
// We may go through BB multiple times so skip the one we have checked.
if (!VisitedInstrs.insert(&*it).second) {
if (it->use_empty() && KeyNodes.count(&*it) > 0 &&
vectorizeSimpleInstructions(PostProcessInstructions, BB, R)) {
// We would like to start over since some instructions are deleted
// and the iterator may become invalid value.
Changed = true;
it = BB->begin();
e = BB->end();
}
continue;
}
if (isa<DbgInfoIntrinsic>(it))
continue;
// Try to vectorize reductions that use PHINodes.
if (PHINode *P = dyn_cast<PHINode>(it)) {
// Check that the PHI is a reduction PHI.
if (P->getNumIncomingValues() != 2)
return Changed;
// Try to match and vectorize a horizontal reduction.
if (vectorizeRootInstruction(P, getReductionValue(DT, P, BB, LI), BB, R,
TTI)) {
Changed = true;
it = BB->begin();
e = BB->end();
continue;
}
continue;
}
// Ran into an instruction without users, like terminator, or function call
// with ignored return value, store. Ignore unused instructions (basing on
// instruction type, except for CallInst and InvokeInst).
if (it->use_empty() && (it->getType()->isVoidTy() || isa<CallInst>(it) ||
isa<InvokeInst>(it))) {
KeyNodes.insert(&*it);
bool OpsChanged = false;
if (ShouldStartVectorizeHorAtStore || !isa<StoreInst>(it)) {
for (auto *V : it->operand_values()) {
// Try to match and vectorize a horizontal reduction.
OpsChanged |= vectorizeRootInstruction(nullptr, V, BB, R, TTI);
}
}
// Start vectorization of post-process list of instructions from the
// top-tree instructions to try to vectorize as many instructions as
// possible.
OpsChanged |= vectorizeSimpleInstructions(PostProcessInstructions, BB, R);
if (OpsChanged) {
// We would like to start over since some instructions are deleted
// and the iterator may become invalid value.
Changed = true;
it = BB->begin();
e = BB->end();
continue;
}
}
if (isa<InsertElementInst>(it) || isa<CmpInst>(it) ||
isa<InsertValueInst>(it))
PostProcessInstructions.push_back(&*it);
}
return Changed;
}
bool SLPVectorizerPass::vectorizeGEPIndices(BasicBlock *BB, BoUpSLP &R) {
auto Changed = false;
for (auto &Entry : GEPs) {
// If the getelementptr list has fewer than two elements, there's nothing
// to do.
if (Entry.second.size() < 2)
continue;
LLVM_DEBUG(dbgs() << "SLP: Analyzing a getelementptr list of length "
<< Entry.second.size() << ".\n");
// We process the getelementptr list in chunks of 16 (like we do for
// stores) to minimize compile-time.
for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += 16) {
auto Len = std::min<unsigned>(BE - BI, 16);
auto GEPList = makeArrayRef(&Entry.second[BI], Len);
// Initialize a set a candidate getelementptrs. Note that we use a
// SetVector here to preserve program order. If the index computations
// are vectorizable and begin with loads, we want to minimize the chance
// of having to reorder them later.
SetVector<Value *> Candidates(GEPList.begin(), GEPList.end());
// Some of the candidates may have already been vectorized after we
// initially collected them. If so, the WeakTrackingVHs will have
// nullified the
// values, so remove them from the set of candidates.
Candidates.remove(nullptr);
// Remove from the set of candidates all pairs of getelementptrs with
// constant differences. Such getelementptrs are likely not good
// candidates for vectorization in a bottom-up phase since one can be
// computed from the other. We also ensure all candidate getelementptr
// indices are unique.
for (int I = 0, E = GEPList.size(); I < E && Candidates.size() > 1; ++I) {
auto *GEPI = cast<GetElementPtrInst>(GEPList[I]);
if (!Candidates.count(GEPI))
continue;
auto *SCEVI = SE->getSCEV(GEPList[I]);
for (int J = I + 1; J < E && Candidates.size() > 1; ++J) {
auto *GEPJ = cast<GetElementPtrInst>(GEPList[J]);
auto *SCEVJ = SE->getSCEV(GEPList[J]);
if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) {
Candidates.remove(GEPList[I]);
Candidates.remove(GEPList[J]);
} else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) {
Candidates.remove(GEPList[J]);
}
}
}
// We break out of the above computation as soon as we know there are
// fewer than two candidates remaining.
if (Candidates.size() < 2)
continue;
// Add the single, non-constant index of each candidate to the bundle. We
// ensured the indices met these constraints when we originally collected
// the getelementptrs.
SmallVector<Value *, 16> Bundle(Candidates.size());
auto BundleIndex = 0u;
for (auto *V : Candidates) {
auto *GEP = cast<GetElementPtrInst>(V);
auto *GEPIdx = GEP->idx_begin()->get();
assert(GEP->getNumIndices() == 1 || !isa<Constant>(GEPIdx));
Bundle[BundleIndex++] = GEPIdx;
}
// Try and vectorize the indices. We are currently only interested in
// gather-like cases of the form:
//
// ... = g[a[0] - b[0]] + g[a[1] - b[1]] + ...
//
// where the loads of "a", the loads of "b", and the subtractions can be
// performed in parallel. It's likely that detecting this pattern in a
// bottom-up phase will be simpler and less costly than building a
// full-blown top-down phase beginning at the consecutive loads.
Changed |= tryToVectorizeList(Bundle, R);
}
}
return Changed;
}
bool SLPVectorizerPass::vectorizeStoreChains(BoUpSLP &R) {
bool Changed = false;
// Attempt to sort and vectorize each of the store-groups.
for (StoreListMap::iterator it = Stores.begin(), e = Stores.end(); it != e;
++it) {
if (it->second.size() < 2)
continue;
LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length "
<< it->second.size() << ".\n");
// Process the stores in chunks of 16.
// TODO: The limit of 16 inhibits greater vectorization factors.
// For example, AVX2 supports v32i8. Increasing this limit, however,
// may cause a significant compile-time increase.
for (unsigned CI = 0, CE = it->second.size(); CI < CE; CI += 16) {
unsigned Len = std::min<unsigned>(CE - CI, 16);
Changed |= vectorizeStores(makeArrayRef(&it->second[CI], Len), R);
}
}
return Changed;
}
char SLPVectorizer::ID = 0;
static const char lv_name[] = "SLP Vectorizer";
INITIALIZE_PASS_BEGIN(SLPVectorizer, SV_NAME, lv_name, false, false)
INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass)
INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass)
INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
INITIALIZE_PASS_DEPENDENCY(DemandedBitsWrapperPass)
INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass)
INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false)
Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); }