| //===- SLPVectorizer.cpp - A bottom up SLP Vectorizer ---------------------===// |
| // |
| // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| // See https://llvm.org/LICENSE.txt for license information. |
| // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| // |
| //===----------------------------------------------------------------------===// |
| // |
| // This pass implements the Bottom Up SLP vectorizer. It detects consecutive |
| // stores that can be put together into vector-stores. Next, it attempts to |
| // construct vectorizable tree using the use-def chains. If a profitable tree |
| // was found, the SLP vectorizer performs vectorization on the tree. |
| // |
| // The pass is inspired by the work described in the paper: |
| // "Loop-Aware SLP in GCC" by Ira Rosen, Dorit Nuzman, Ayal Zaks. |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #include "llvm/Transforms/Vectorize/SLPVectorizer.h" |
| #include "llvm/ADT/DenseMap.h" |
| #include "llvm/ADT/DenseSet.h" |
| #include "llvm/ADT/Optional.h" |
| #include "llvm/ADT/PostOrderIterator.h" |
| #include "llvm/ADT/PriorityQueue.h" |
| #include "llvm/ADT/STLExtras.h" |
| #include "llvm/ADT/SetOperations.h" |
| #include "llvm/ADT/SetVector.h" |
| #include "llvm/ADT/SmallBitVector.h" |
| #include "llvm/ADT/SmallPtrSet.h" |
| #include "llvm/ADT/SmallSet.h" |
| #include "llvm/ADT/SmallString.h" |
| #include "llvm/ADT/Statistic.h" |
| #include "llvm/ADT/iterator.h" |
| #include "llvm/ADT/iterator_range.h" |
| #include "llvm/Analysis/AliasAnalysis.h" |
| #include "llvm/Analysis/AssumptionCache.h" |
| #include "llvm/Analysis/CodeMetrics.h" |
| #include "llvm/Analysis/DemandedBits.h" |
| #include "llvm/Analysis/GlobalsModRef.h" |
| #include "llvm/Analysis/IVDescriptors.h" |
| #include "llvm/Analysis/LoopAccessAnalysis.h" |
| #include "llvm/Analysis/LoopInfo.h" |
| #include "llvm/Analysis/MemoryLocation.h" |
| #include "llvm/Analysis/OptimizationRemarkEmitter.h" |
| #include "llvm/Analysis/ScalarEvolution.h" |
| #include "llvm/Analysis/ScalarEvolutionExpressions.h" |
| #include "llvm/Analysis/TargetLibraryInfo.h" |
| #include "llvm/Analysis/TargetTransformInfo.h" |
| #include "llvm/Analysis/ValueTracking.h" |
| #include "llvm/Analysis/VectorUtils.h" |
| #include "llvm/IR/Attributes.h" |
| #include "llvm/IR/BasicBlock.h" |
| #include "llvm/IR/Constant.h" |
| #include "llvm/IR/Constants.h" |
| #include "llvm/IR/DataLayout.h" |
| #include "llvm/IR/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/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/InitializePasses.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/InstructionCost.h" |
| #include "llvm/Support/KnownBits.h" |
| #include "llvm/Support/MathExtras.h" |
| #include "llvm/Support/raw_ostream.h" |
| #include "llvm/Transforms/Utils/InjectTLIMappings.h" |
| #include "llvm/Transforms/Utils/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"); |
| |
| cl::opt<bool> RunSLPVectorization("vectorize-slp", cl::init(true), cl::Hidden, |
| cl::desc("Run the SLP vectorization passes")); |
| |
| static cl::opt<int> |
| SLPCostThreshold("slp-threshold", cl::init(0), cl::Hidden, |
| cl::desc("Only vectorize if you gain more than this " |
| "number ")); |
| |
| static cl::opt<bool> |
| ShouldVectorizeHor("slp-vectorize-hor", cl::init(true), cl::Hidden, |
| cl::desc("Attempt to vectorize horizontal reductions")); |
| |
| static cl::opt<bool> ShouldStartVectorizeHorAtStore( |
| "slp-vectorize-hor-store", cl::init(false), cl::Hidden, |
| cl::desc( |
| "Attempt to vectorize horizontal reductions feeding into a store")); |
| |
| static cl::opt<int> |
| MaxVectorRegSizeOption("slp-max-reg-size", cl::init(128), cl::Hidden, |
| cl::desc("Attempt to vectorize for this register size in bits")); |
| |
| static cl::opt<unsigned> |
| MaxVFOption("slp-max-vf", cl::init(0), cl::Hidden, |
| cl::desc("Maximum SLP vectorization factor (0=unlimited)")); |
| |
| static cl::opt<int> |
| MaxStoreLookup("slp-max-store-lookup", cl::init(32), cl::Hidden, |
| cl::desc("Maximum depth of the lookup for consecutive stores.")); |
| |
| /// Limits the size of scheduling regions in a block. |
| /// It avoid long compile times for _very_ large blocks where vector |
| /// instructions are spread over a wide range. |
| /// This limit is way higher than needed by real-world functions. |
| static cl::opt<int> |
| ScheduleRegionSizeBudget("slp-schedule-budget", cl::init(100000), cl::Hidden, |
| cl::desc("Limit the size of the SLP scheduling region per block")); |
| |
| static cl::opt<int> MinVectorRegSizeOption( |
| "slp-min-reg-size", cl::init(128), cl::Hidden, |
| cl::desc("Attempt to vectorize for this register size in bits")); |
| |
| static cl::opt<unsigned> RecursionMaxDepth( |
| "slp-recursion-max-depth", cl::init(12), cl::Hidden, |
| cl::desc("Limit the recursion depth when building a vectorizable tree")); |
| |
| static cl::opt<unsigned> MinTreeSize( |
| "slp-min-tree-size", cl::init(3), cl::Hidden, |
| cl::desc("Only vectorize small trees if they are fully vectorizable")); |
| |
| // The maximum depth that the look-ahead score heuristic will explore. |
| // The higher this value, the higher the compilation time overhead. |
| static cl::opt<int> LookAheadMaxDepth( |
| "slp-max-look-ahead-depth", cl::init(2), cl::Hidden, |
| cl::desc("The maximum look-ahead depth for operand reordering scores")); |
| |
| // The Look-ahead heuristic goes through the users of the bundle to calculate |
| // the users cost in getExternalUsesCost(). To avoid compilation time increase |
| // we limit the number of users visited to this value. |
| static cl::opt<unsigned> LookAheadUsersBudget( |
| "slp-look-ahead-users-budget", cl::init(2), cl::Hidden, |
| cl::desc("The maximum number of users to visit while visiting the " |
| "predecessors. This prevents compilation time increase.")); |
| |
| static cl::opt<bool> |
| ViewSLPTree("view-slp-tree", cl::Hidden, |
| cl::desc("Display the SLP trees with Graphviz")); |
| |
| // Limit the number of alias checks. The limit is chosen so that |
| // it has no negative effect on the llvm benchmarks. |
| static const unsigned AliasedCheckLimit = 10; |
| |
| // Another limit for the alias checks: The maximum distance between load/store |
| // instructions where alias checks are done. |
| // This limit is useful for very large basic blocks. |
| static const unsigned MaxMemDepDistance = 160; |
| |
| /// If the ScheduleRegionSizeBudget is exhausted, we allow small scheduling |
| /// regions to be handled. |
| static const int MinScheduleRegionSize = 16; |
| |
| /// Predicate for the element types that the SLP vectorizer supports. |
| /// |
| /// The most important thing to filter here are types which are invalid in LLVM |
| /// vectors. We also filter target specific types which have absolutely no |
| /// meaningful vectorization path such as x86_fp80 and ppc_f128. This just |
| /// avoids spending time checking the cost model and realizing that they will |
| /// be inevitably scalarized. |
| static bool isValidElementType(Type *Ty) { |
| return VectorType::isValidElementType(Ty) && !Ty->isX86_FP80Ty() && |
| !Ty->isPPC_FP128Ty(); |
| } |
| |
| /// \returns True if the value is a constant (but not globals/constant |
| /// expressions). |
| static bool isConstant(Value *V) { |
| return isa<Constant>(V) && !isa<ConstantExpr>(V) && !isa<GlobalValue>(V); |
| } |
| |
| /// Checks if \p V is one of vector-like instructions, i.e. undef, |
| /// insertelement/extractelement with constant indices for fixed vector type or |
| /// extractvalue instruction. |
| static bool isVectorLikeInstWithConstOps(Value *V) { |
| if (!isa<InsertElementInst, ExtractElementInst>(V) && |
| !isa<ExtractValueInst, UndefValue>(V)) |
| return false; |
| auto *I = dyn_cast<Instruction>(V); |
| if (!I || isa<ExtractValueInst>(I)) |
| return true; |
| if (!isa<FixedVectorType>(I->getOperand(0)->getType())) |
| return false; |
| if (isa<ExtractElementInst>(I)) |
| return isConstant(I->getOperand(1)); |
| assert(isa<InsertElementInst>(V) && "Expected only insertelement."); |
| return isConstant(I->getOperand(2)); |
| } |
| |
| /// \returns true if all of the instructions in \p VL are in the same block or |
| /// false otherwise. |
| static bool allSameBlock(ArrayRef<Value *> VL) { |
| Instruction *I0 = dyn_cast<Instruction>(VL[0]); |
| if (!I0) |
| return false; |
| if (all_of(VL, isVectorLikeInstWithConstOps)) |
| return true; |
| |
| BasicBlock *BB = I0->getParent(); |
| for (int I = 1, E = VL.size(); I < E; I++) { |
| auto *II = dyn_cast<Instruction>(VL[I]); |
| if (!II) |
| return false; |
| |
| if (BB != II->getParent()) |
| return false; |
| } |
| return true; |
| } |
| |
| /// \returns True if all of the values in \p VL are constants (but not |
| /// globals/constant expressions). |
| static bool allConstant(ArrayRef<Value *> VL) { |
| // Constant expressions and globals can't be vectorized like normal integer/FP |
| // constants. |
| return all_of(VL, isConstant); |
| } |
| |
| /// \returns True if all of the values in \p VL are identical or some of them |
| /// are UndefValue. |
| static bool isSplat(ArrayRef<Value *> VL) { |
| Value *FirstNonUndef = nullptr; |
| for (Value *V : VL) { |
| if (isa<UndefValue>(V)) |
| continue; |
| if (!FirstNonUndef) { |
| FirstNonUndef = V; |
| continue; |
| } |
| if (V != FirstNonUndef) |
| return false; |
| } |
| return FirstNonUndef != nullptr; |
| } |
| |
| /// \returns True if \p I is commutative, handles CmpInst and BinaryOperator. |
| static bool isCommutative(Instruction *I) { |
| if (auto *Cmp = dyn_cast<CmpInst>(I)) |
| return Cmp->isCommutative(); |
| if (auto *BO = dyn_cast<BinaryOperator>(I)) |
| return BO->isCommutative(); |
| // TODO: This should check for generic Instruction::isCommutative(), but |
| // we need to confirm that the caller code correctly handles Intrinsics |
| // for example (does not have 2 operands). |
| return false; |
| } |
| |
| /// Checks if the vector of instructions can be represented as a shuffle, like: |
| /// %x0 = extractelement <4 x i8> %x, i32 0 |
| /// %x3 = extractelement <4 x i8> %x, i32 3 |
| /// %y1 = extractelement <4 x i8> %y, i32 1 |
| /// %y2 = extractelement <4 x i8> %y, i32 2 |
| /// %x0x0 = mul i8 %x0, %x0 |
| /// %x3x3 = mul i8 %x3, %x3 |
| /// %y1y1 = mul i8 %y1, %y1 |
| /// %y2y2 = mul i8 %y2, %y2 |
| /// %ins1 = insertelement <4 x i8> poison, i8 %x0x0, i32 0 |
| /// %ins2 = insertelement <4 x i8> %ins1, i8 %x3x3, i32 1 |
| /// %ins3 = insertelement <4 x i8> %ins2, i8 %y1y1, i32 2 |
| /// %ins4 = insertelement <4 x i8> %ins3, i8 %y2y2, i32 3 |
| /// ret <4 x i8> %ins4 |
| /// can be transformed into: |
| /// %1 = shufflevector <4 x i8> %x, <4 x i8> %y, <4 x i32> <i32 0, i32 3, i32 5, |
| /// i32 6> |
| /// %2 = mul <4 x i8> %1, %1 |
| /// ret <4 x i8> %2 |
| /// We convert this initially to something like: |
| /// %x0 = extractelement <4 x i8> %x, i32 0 |
| /// %x3 = extractelement <4 x i8> %x, i32 3 |
| /// %y1 = extractelement <4 x i8> %y, i32 1 |
| /// %y2 = extractelement <4 x i8> %y, i32 2 |
| /// %1 = insertelement <4 x i8> poison, i8 %x0, i32 0 |
| /// %2 = insertelement <4 x i8> %1, i8 %x3, i32 1 |
| /// %3 = insertelement <4 x i8> %2, i8 %y1, i32 2 |
| /// %4 = insertelement <4 x i8> %3, i8 %y2, i32 3 |
| /// %5 = mul <4 x i8> %4, %4 |
| /// %6 = extractelement <4 x i8> %5, i32 0 |
| /// %ins1 = insertelement <4 x i8> poison, i8 %6, i32 0 |
| /// %7 = extractelement <4 x i8> %5, i32 1 |
| /// %ins2 = insertelement <4 x i8> %ins1, i8 %7, i32 1 |
| /// %8 = extractelement <4 x i8> %5, i32 2 |
| /// %ins3 = insertelement <4 x i8> %ins2, i8 %8, i32 2 |
| /// %9 = extractelement <4 x i8> %5, i32 3 |
| /// %ins4 = insertelement <4 x i8> %ins3, i8 %9, i32 3 |
| /// ret <4 x i8> %ins4 |
| /// InstCombiner transforms this into a shuffle and vector mul |
| /// Mask will return the Shuffle Mask equivalent to the extracted elements. |
| /// TODO: Can we split off and reuse the shuffle mask detection from |
| /// TargetTransformInfo::getInstructionThroughput? |
| static Optional<TargetTransformInfo::ShuffleKind> |
| isFixedVectorShuffle(ArrayRef<Value *> VL, SmallVectorImpl<int> &Mask) { |
| auto *EI0 = cast<ExtractElementInst>(VL[0]); |
| if (isa<ScalableVectorType>(EI0->getVectorOperandType())) |
| return None; |
| unsigned Size = |
| cast<FixedVectorType>(EI0->getVectorOperandType())->getNumElements(); |
| 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 (cast<FixedVectorType>(Vec->getType())->getNumElements() != 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)) { |
| Mask.push_back(UndefMaskElem); |
| continue; |
| } |
| unsigned IntIdx = Idx->getValue().getZExtValue(); |
| Mask.push_back(IntIdx); |
| // We can extractelement from undef or poison 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 true if \p Opcode is allowed as part of of the main/alternate |
| /// instruction for SLP vectorization. |
| /// |
| /// Example of unsupported opcode is SDIV that can potentially cause UB if the |
| /// "shuffled out" lane would result in division by zero. |
| static bool isValidForAlternation(unsigned Opcode) { |
| if (Instruction::isIntDivRem(Opcode)) |
| return false; |
| |
| return true; |
| } |
| |
| /// \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 && isValidForAlternation(InstOpcode) && |
| isValidForAlternation(Opcode)) { |
| 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) { |
| assert(isValidForAlternation(Opcode) && |
| isValidForAlternation(InstOpcode) && |
| "Cast isn't safe for alternation, logic needs to be updated!"); |
| 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->arg_size(); 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, AAResults *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; |
| } |
| |
| /// Shuffles \p Mask in accordance with the given \p SubMask. |
| static void addMask(SmallVectorImpl<int> &Mask, ArrayRef<int> SubMask) { |
| if (SubMask.empty()) |
| return; |
| if (Mask.empty()) { |
| Mask.append(SubMask.begin(), SubMask.end()); |
| return; |
| } |
| SmallVector<int> NewMask(SubMask.size(), UndefMaskElem); |
| int TermValue = std::min(Mask.size(), SubMask.size()); |
| for (int I = 0, E = SubMask.size(); I < E; ++I) { |
| if (SubMask[I] >= TermValue || SubMask[I] == UndefMaskElem || |
| Mask[SubMask[I]] >= TermValue) |
| continue; |
| NewMask[I] = Mask[SubMask[I]]; |
| } |
| Mask.swap(NewMask); |
| } |
| |
| /// Order may have elements assigned special value (size) which is out of |
| /// bounds. Such indices only appear on places which correspond to undef values |
| /// (see canReuseExtract for details) and used in order to avoid undef values |
| /// have effect on operands ordering. |
| /// The first loop below simply finds all unused indices and then the next loop |
| /// nest assigns these indices for undef values positions. |
| /// As an example below Order has two undef positions and they have assigned |
| /// values 3 and 7 respectively: |
| /// before: 6 9 5 4 9 2 1 0 |
| /// after: 6 3 5 4 7 2 1 0 |
| static void fixupOrderingIndices(SmallVectorImpl<unsigned> &Order) { |
| const unsigned Sz = Order.size(); |
| SmallBitVector UsedIndices(Sz); |
| SmallVector<int> MaskedIndices; |
| for (unsigned I = 0; I < Sz; ++I) { |
| if (Order[I] < Sz) |
| UsedIndices.set(Order[I]); |
| else |
| MaskedIndices.push_back(I); |
| } |
| if (MaskedIndices.empty()) |
| return; |
| SmallVector<int> AvailableIndices(MaskedIndices.size()); |
| unsigned Cnt = 0; |
| int Idx = UsedIndices.find_first(); |
| do { |
| AvailableIndices[Cnt] = Idx; |
| Idx = UsedIndices.find_next(Idx); |
| ++Cnt; |
| } while (Idx > 0); |
| assert(Cnt == MaskedIndices.size() && "Non-synced masked/available indices."); |
| for (int I = 0, E = MaskedIndices.size(); I < E; ++I) |
| Order[MaskedIndices[I]] = AvailableIndices[I]; |
| } |
| |
| namespace llvm { |
| |
| static void inversePermutation(ArrayRef<unsigned> Indices, |
| SmallVectorImpl<int> &Mask) { |
| Mask.clear(); |
| const unsigned E = Indices.size(); |
| Mask.resize(E, UndefMaskElem); |
| for (unsigned I = 0; I < E; ++I) |
| Mask[Indices[I]] = I; |
| } |
| |
| /// \returns inserting index of InsertElement or InsertValue instruction, |
| /// using Offset as base offset for index. |
| static Optional<int> getInsertIndex(Value *InsertInst, unsigned Offset) { |
| int Index = Offset; |
| if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) { |
| if (auto *CI = dyn_cast<ConstantInt>(IE->getOperand(2))) { |
| auto *VT = cast<FixedVectorType>(IE->getType()); |
| if (CI->getValue().uge(VT->getNumElements())) |
| return UndefMaskElem; |
| Index *= VT->getNumElements(); |
| Index += CI->getZExtValue(); |
| return Index; |
| } |
| if (isa<UndefValue>(IE->getOperand(2))) |
| return UndefMaskElem; |
| return None; |
| } |
| |
| auto *IV = cast<InsertValueInst>(InsertInst); |
| Type *CurrentType = IV->getType(); |
| for (unsigned I : IV->indices()) { |
| if (auto *ST = dyn_cast<StructType>(CurrentType)) { |
| Index *= ST->getNumElements(); |
| CurrentType = ST->getElementType(I); |
| } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { |
| Index *= AT->getNumElements(); |
| CurrentType = AT->getElementType(); |
| } else { |
| return None; |
| } |
| Index += I; |
| } |
| return Index; |
| } |
| |
| /// Reorders the list of scalars in accordance with the given \p Order and then |
| /// the \p Mask. \p Order - is the original order of the scalars, need to |
| /// reorder scalars into an unordered state at first according to the given |
| /// order. Then the ordered scalars are shuffled once again in accordance with |
| /// the provided mask. |
| static void reorderScalars(SmallVectorImpl<Value *> &Scalars, |
| ArrayRef<int> Mask) { |
| assert(!Mask.empty() && "Expected non-empty mask."); |
| SmallVector<Value *> Prev(Scalars.size(), |
| UndefValue::get(Scalars.front()->getType())); |
| Prev.swap(Scalars); |
| for (unsigned I = 0, E = Prev.size(); I < E; ++I) |
| if (Mask[I] != UndefMaskElem) |
| Scalars[Mask[I]] = Prev[I]; |
| } |
| |
| namespace slpvectorizer { |
| |
| /// Bottom Up SLP Vectorizer. |
| class BoUpSLP { |
| struct TreeEntry; |
| struct ScheduleData; |
| |
| public: |
| using ValueList = SmallVector<Value *, 8>; |
| using InstrList = SmallVector<Instruction *, 16>; |
| using ValueSet = SmallPtrSet<Value *, 16>; |
| using StoreList = SmallVector<StoreInst *, 8>; |
| using ExtraValueToDebugLocsMap = |
| MapVector<Value *, SmallVector<Instruction *, 2>>; |
| using OrdersType = SmallVector<unsigned, 4>; |
| |
| BoUpSLP(Function *Func, ScalarEvolution *Se, TargetTransformInfo *Tti, |
| TargetLibraryInfo *TLi, AAResults *Aa, LoopInfo *Li, |
| DominatorTree *Dt, AssumptionCache *AC, DemandedBits *DB, |
| const DataLayout *DL, OptimizationRemarkEmitter *ORE) |
| : 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(TargetTransformInfo::RGK_FixedWidthVector) |
| .getFixedSize(); |
| |
| 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. |
| InstructionCost getSpillCost() const; |
| |
| /// \returns the vectorization cost of the subtree that starts at \p VL. |
| /// A negative number means that this is profitable. |
| InstructionCost getTreeCost(ArrayRef<Value *> VectorizedVals = None); |
| |
| /// 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); |
| |
| /// Builds external uses of the vectorized scalars, i.e. the list of |
| /// vectorized scalars to be extracted, their lanes and their scalar users. \p |
| /// ExternallyUsedValues contains additional list of external uses to handle |
| /// vectorization of reductions. |
| void |
| buildExternalUses(const ExtraValueToDebugLocsMap &ExternallyUsedValues = {}); |
| |
| /// Clear the internal data structures that are created by 'buildTree'. |
| void deleteTree() { |
| VectorizableTree.clear(); |
| ScalarToTreeEntry.clear(); |
| MustGather.clear(); |
| ExternalUses.clear(); |
| for (auto &Iter : BlocksSchedules) { |
| BlockScheduling *BS = Iter.second.get(); |
| BS->clear(); |
| } |
| MinBWs.clear(); |
| InstrElementSize.clear(); |
| } |
| |
| unsigned getTreeSize() const { return VectorizableTree.size(); } |
| |
| /// Perform LICM and CSE on the newly generated gather sequences. |
| void optimizeGatherSequence(); |
| |
| /// Checks if the specified gather tree entry \p TE can be represented as a |
| /// shuffled vector entry + (possibly) permutation with other gathers. It |
| /// implements the checks only for possibly ordered scalars (Loads, |
| /// ExtractElement, ExtractValue), which can be part of the graph. |
| Optional<OrdersType> findReusedOrderedScalars(const TreeEntry &TE); |
| |
| /// Reorders the current graph to the most profitable order starting from the |
| /// root node to the leaf nodes. The best order is chosen only from the nodes |
| /// of the same size (vectorization factor). Smaller nodes are considered |
| /// parts of subgraph with smaller VF and they are reordered independently. We |
| /// can make it because we still need to extend smaller nodes to the wider VF |
| /// and we can merge reordering shuffles with the widening shuffles. |
| void reorderTopToBottom(); |
| |
| /// Reorders the current graph to the most profitable order starting from |
| /// leaves to the root. It allows to rotate small subgraphs and reduce the |
| /// number of reshuffles if the leaf nodes use the same order. In this case we |
| /// can merge the orders and just shuffle user node instead of shuffling its |
| /// operands. Plus, even the leaf nodes have different orders, it allows to |
| /// sink reordering in the graph closer to the root node and merge it later |
| /// during analysis. |
| void reorderBottomToTop(bool IgnoreReorder = false); |
| |
| /// \return The vector element size in bits to use when vectorizing the |
| /// expression tree ending at \p V. If V is a store, the size is the width of |
| /// the stored value. Otherwise, the size is the width of the largest loaded |
| /// value reaching V. This method is used by the vectorizer to calculate |
| /// vectorization factors. |
| unsigned getVectorElementSize(Value *V); |
| |
| /// Compute the minimum type sizes required to represent the entries in a |
| /// vectorizable tree. |
| void computeMinimumValueSizes(); |
| |
| // \returns maximum vector register size as set by TTI or overridden by cl::opt. |
| unsigned getMaxVecRegSize() const { |
| return MaxVecRegSize; |
| } |
| |
| // \returns minimum vector register size as set by cl::opt. |
| unsigned getMinVecRegSize() const { |
| return MinVecRegSize; |
| } |
| |
| unsigned getMinVF(unsigned Sz) const { |
| return std::max(2U, getMinVecRegSize() / Sz); |
| } |
| |
| unsigned getMaximumVF(unsigned ElemWidth, unsigned Opcode) const { |
| unsigned MaxVF = MaxVFOption.getNumOccurrences() ? |
| MaxVFOption : TTI->getMaximumVF(ElemWidth, Opcode); |
| return MaxVF ? MaxVF : UINT_MAX; |
| } |
| |
| /// Check if homogeneous aggregate is isomorphic to some VectorType. |
| /// Accepts homogeneous multidimensional aggregate of scalars/vectors like |
| /// {[4 x i16], [4 x i16]}, { <2 x float>, <2 x float> }, |
| /// {{{i16, i16}, {i16, i16}}, {{i16, i16}, {i16, i16}}} and so on. |
| /// |
| /// \returns number of elements in vector if isomorphism exists, 0 otherwise. |
| unsigned canMapToVector(Type *T, const DataLayout &DL) const; |
| |
| /// \returns True if the VectorizableTree is both tiny and not fully |
| /// vectorizable. We do not vectorize such trees. |
| bool isTreeTinyAndNotFullyVectorizable(bool ForReduction = false) const; |
| |
| /// Assume that a legal-sized 'or'-reduction of shifted/zexted loaded values |
| /// can be load combined in the backend. Load combining may not be allowed in |
| /// the IR optimizer, so we do not want to alter the pattern. For example, |
| /// partially transforming a scalar bswap() pattern into vector code is |
| /// effectively impossible for the backend to undo. |
| /// TODO: If load combining is allowed in the IR optimizer, this analysis |
| /// may not be necessary. |
| bool isLoadCombineReductionCandidate(RecurKind RdxKind) const; |
| |
| /// Assume that a vector of stores of bitwise-or/shifted/zexted loaded values |
| /// can be load combined in the backend. Load combining may not be allowed in |
| /// the IR optimizer, so we do not want to alter the pattern. For example, |
| /// partially transforming a scalar bswap() pattern into vector code is |
| /// effectively impossible for the backend to undo. |
| /// TODO: If load combining is allowed in the IR optimizer, this analysis |
| /// may not be necessary. |
| bool isLoadCombineCandidate() const; |
| |
| OptimizationRemarkEmitter *getORE() { return ORE; } |
| |
| /// This structure holds any data we need about the edges being traversed |
| /// during buildTree_rec(). We keep track of: |
| /// (i) the user TreeEntry index, and |
| /// (ii) the index of the edge. |
| struct EdgeInfo { |
| EdgeInfo() = default; |
| EdgeInfo(TreeEntry *UserTE, unsigned EdgeIdx) |
| : UserTE(UserTE), EdgeIdx(EdgeIdx) {} |
| /// The user TreeEntry. |
| TreeEntry *UserTE = nullptr; |
| /// The operand index of the use. |
| unsigned EdgeIdx = UINT_MAX; |
| #ifndef NDEBUG |
| friend inline raw_ostream &operator<<(raw_ostream &OS, |
| const BoUpSLP::EdgeInfo &EI) { |
| EI.dump(OS); |
| return OS; |
| } |
| /// Debug print. |
| void dump(raw_ostream &OS) const { |
| OS << "{User:" << (UserTE ? std::to_string(UserTE->Idx) : "null") |
| << " EdgeIdx:" << EdgeIdx << "}"; |
| } |
| LLVM_DUMP_METHOD void dump() const { dump(dbgs()); } |
| #endif |
| }; |
| |
| /// A helper data structure to hold the operands of a vector of instructions. |
| /// This supports a fixed vector length for all operand vectors. |
| class VLOperands { |
| /// For each operand we need (i) the value, and (ii) the opcode that it |
| /// would be attached to if the expression was in a left-linearized form. |
| /// This is required to avoid illegal operand reordering. |
| /// For example: |
| /// \verbatim |
| /// 0 Op1 |
| /// |/ |
| /// Op1 Op2 Linearized + Op2 |
| /// \ / ----------> |/ |
| /// - - |
| /// |
| /// Op1 - Op2 (0 + Op1) - Op2 |
| /// \endverbatim |
| /// |
| /// Value Op1 is attached to a '+' operation, and Op2 to a '-'. |
| /// |
| /// Another way to think of this is to track all the operations across the |
| /// path from the operand all the way to the root of the tree and to |
| /// calculate the operation that corresponds to this path. For example, the |
| /// path from Op2 to the root crosses the RHS of the '-', therefore the |
| /// corresponding operation is a '-' (which matches the one in the |
| /// linearized tree, as shown above). |
| /// |
| /// For lack of a better term, we refer to this operation as Accumulated |
| /// Path Operation (APO). |
| struct OperandData { |
| OperandData() = default; |
| OperandData(Value *V, bool APO, bool IsUsed) |
| : V(V), APO(APO), IsUsed(IsUsed) {} |
| /// The operand value. |
| Value *V = nullptr; |
| /// TreeEntries only allow a single opcode, or an alternate sequence of |
| /// them (e.g, +, -). Therefore, we can safely use a boolean value for the |
| /// APO. It is set to 'true' if 'V' is attached to an inverse operation |
| /// in the left-linearized form (e.g., Sub/Div), and 'false' otherwise |
| /// (e.g., Add/Mul) |
| bool APO = false; |
| /// Helper data for the reordering function. |
| bool IsUsed = false; |
| }; |
| |
| /// During operand reordering, we are trying to select the operand at lane |
| /// that matches best with the operand at the neighboring lane. Our |
| /// selection is based on the type of value we are looking for. For example, |
| /// if the neighboring lane has a load, we need to look for a load that is |
| /// accessing a consecutive address. These strategies are summarized in the |
| /// 'ReorderingMode' enumerator. |
| enum class ReorderingMode { |
| Load, ///< Matching loads to consecutive memory addresses |
| Opcode, ///< Matching instructions based on opcode (same or alternate) |
| Constant, ///< Matching constants |
| Splat, ///< Matching the same instruction multiple times (broadcast) |
| Failed, ///< We failed to create a vectorizable group |
| }; |
| |
| using OperandDataVec = SmallVector<OperandData, 2>; |
| |
| /// A vector of operand vectors. |
| SmallVector<OperandDataVec, 4> OpsVec; |
| |
| const DataLayout &DL; |
| ScalarEvolution &SE; |
| const BoUpSLP &R; |
| |
| /// \returns the operand data at \p OpIdx and \p Lane. |
| OperandData &getData(unsigned OpIdx, unsigned Lane) { |
| return OpsVec[OpIdx][Lane]; |
| } |
| |
| /// \returns the operand data at \p OpIdx and \p Lane. Const version. |
| const OperandData &getData(unsigned OpIdx, unsigned Lane) const { |
| return OpsVec[OpIdx][Lane]; |
| } |
| |
| /// Clears the used flag for all entries. |
| void clearUsed() { |
| for (unsigned OpIdx = 0, NumOperands = getNumOperands(); |
| OpIdx != NumOperands; ++OpIdx) |
| for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; |
| ++Lane) |
| OpsVec[OpIdx][Lane].IsUsed = false; |
| } |
| |
| /// Swap the operand at \p OpIdx1 with that one at \p OpIdx2. |
| void swap(unsigned OpIdx1, unsigned OpIdx2, unsigned Lane) { |
| std::swap(OpsVec[OpIdx1][Lane], OpsVec[OpIdx2][Lane]); |
| } |
| |
| // The hard-coded scores listed here are not very important. When computing |
| // the scores of matching one sub-tree with another, we are basically |
| // counting the number of values that are matching. So even if all scores |
| // are set to 1, we would still get a decent matching result. |
| // However, sometimes we have to break ties. For example we may have to |
| // choose between matching loads vs matching opcodes. This is what these |
| // scores are helping us with: they provide the order of preference. |
| |
| /// Loads from consecutive memory addresses, e.g. load(A[i]), load(A[i+1]). |
| static const int ScoreConsecutiveLoads = 3; |
| /// ExtractElementInst from same vector and consecutive indexes. |
| static const int ScoreConsecutiveExtracts = 3; |
| /// Constants. |
| static const int ScoreConstants = 2; |
| /// Instructions with the same opcode. |
| static const int ScoreSameOpcode = 2; |
| /// Instructions with alt opcodes (e.g, add + sub). |
| static const int ScoreAltOpcodes = 1; |
| /// Identical instructions (a.k.a. splat or broadcast). |
| static const int ScoreSplat = 1; |
| /// Matching with an undef is preferable to failing. |
| static const int ScoreUndef = 1; |
| /// Score for failing to find a decent match. |
| static const int ScoreFail = 0; |
| /// User exteranl to the vectorized code. |
| static const int ExternalUseCost = 1; |
| /// The user is internal but in a different lane. |
| static const int UserInDiffLaneCost = ExternalUseCost; |
| |
| /// \returns the score of placing \p V1 and \p V2 in consecutive lanes. |
| static int getShallowScore(Value *V1, Value *V2, const DataLayout &DL, |
| ScalarEvolution &SE) { |
| auto *LI1 = dyn_cast<LoadInst>(V1); |
| auto *LI2 = dyn_cast<LoadInst>(V2); |
| if (LI1 && LI2) { |
| if (LI1->getParent() != LI2->getParent()) |
| return VLOperands::ScoreFail; |
| |
| Optional<int> Dist = getPointersDiff( |
| LI1->getType(), LI1->getPointerOperand(), LI2->getType(), |
| LI2->getPointerOperand(), DL, SE, /*StrictCheck=*/true); |
| return (Dist && *Dist == 1) ? VLOperands::ScoreConsecutiveLoads |
| : VLOperands::ScoreFail; |
| } |
| |
| auto *C1 = dyn_cast<Constant>(V1); |
| auto *C2 = dyn_cast<Constant>(V2); |
| if (C1 && C2) |
| return VLOperands::ScoreConstants; |
| |
| // Extracts from consecutive indexes of the same vector better score as |
| // the extracts could be optimized away. |
| Value *EV; |
| ConstantInt *Ex1Idx, *Ex2Idx; |
| if (match(V1, m_ExtractElt(m_Value(EV), m_ConstantInt(Ex1Idx))) && |
| match(V2, m_ExtractElt(m_Deferred(EV), m_ConstantInt(Ex2Idx))) && |
| Ex1Idx->getZExtValue() + 1 == Ex2Idx->getZExtValue()) |
| return VLOperands::ScoreConsecutiveExtracts; |
| |
| auto *I1 = dyn_cast<Instruction>(V1); |
| auto *I2 = dyn_cast<Instruction>(V2); |
| if (I1 && I2) { |
| if (I1 == I2) |
| return VLOperands::ScoreSplat; |
| InstructionsState S = getSameOpcode({I1, I2}); |
| // Note: Only consider instructions with <= 2 operands to avoid |
| // complexity explosion. |
| if (S.getOpcode() && S.MainOp->getNumOperands() <= 2) |
| return S.isAltShuffle() ? VLOperands::ScoreAltOpcodes |
| : VLOperands::ScoreSameOpcode; |
| } |
| |
| if (isa<UndefValue>(V2)) |
| return VLOperands::ScoreUndef; |
| |
| return VLOperands::ScoreFail; |
| } |
| |
| /// Holds the values and their lane that are taking part in the look-ahead |
| /// score calculation. This is used in the external uses cost calculation. |
| SmallDenseMap<Value *, int> InLookAheadValues; |
| |
| /// \Returns the additinal cost due to uses of \p LHS and \p RHS that are |
| /// either external to the vectorized code, or require shuffling. |
| int getExternalUsesCost(const std::pair<Value *, int> &LHS, |
| const std::pair<Value *, int> &RHS) { |
| int Cost = 0; |
| std::array<std::pair<Value *, int>, 2> Values = {{LHS, RHS}}; |
| for (int Idx = 0, IdxE = Values.size(); Idx != IdxE; ++Idx) { |
| Value *V = Values[Idx].first; |
| if (isa<Constant>(V)) { |
| // Since this is a function pass, it doesn't make semantic sense to |
| // walk the users of a subclass of Constant. The users could be in |
| // another function, or even another module that happens to be in |
| // the same LLVMContext. |
| continue; |
| } |
| |
| // Calculate the absolute lane, using the minimum relative lane of LHS |
| // and RHS as base and Idx as the offset. |
| int Ln = std::min(LHS.second, RHS.second) + Idx; |
| assert(Ln >= 0 && "Bad lane calculation"); |
| unsigned UsersBudget = LookAheadUsersBudget; |
| for (User *U : V->users()) { |
| if (const TreeEntry *UserTE = R.getTreeEntry(U)) { |
| // The user is in the VectorizableTree. Check if we need to insert. |
| auto It = llvm::find(UserTE->Scalars, U); |
| assert(It != UserTE->Scalars.end() && "U is in UserTE"); |
| int UserLn = std::distance(UserTE->Scalars.begin(), It); |
| assert(UserLn >= 0 && "Bad lane"); |
| if (UserLn != Ln) |
| Cost += UserInDiffLaneCost; |
| } else { |
| // Check if the user is in the look-ahead code. |
| auto It2 = InLookAheadValues.find(U); |
| if (It2 != InLookAheadValues.end()) { |
| // The user is in the look-ahead code. Check the lane. |
| if (It2->second != Ln) |
| Cost += UserInDiffLaneCost; |
| } else { |
| // The user is neither in SLP tree nor in the look-ahead code. |
| Cost += ExternalUseCost; |
| } |
| } |
| // Limit the number of visited uses to cap compilation time. |
| if (--UsersBudget == 0) |
| break; |
| } |
| } |
| return Cost; |
| } |
| |
| /// Go through the operands of \p LHS and \p RHS recursively until \p |
| /// MaxLevel, and return the cummulative score. For example: |
| /// \verbatim |
| /// A[0] B[0] A[1] B[1] C[0] D[0] B[1] A[1] |
| /// \ / \ / \ / \ / |
| /// + + + + |
| /// G1 G2 G3 G4 |
| /// \endverbatim |
| /// The getScoreAtLevelRec(G1, G2) function will try to match the nodes at |
| /// each level recursively, accumulating the score. It starts from matching |
| /// the additions at level 0, then moves on to the loads (level 1). The |
| /// score of G1 and G2 is higher than G1 and G3, because {A[0],A[1]} and |
| /// {B[0],B[1]} match with VLOperands::ScoreConsecutiveLoads, while |
| /// {A[0],C[0]} has a score of VLOperands::ScoreFail. |
| /// Please note that the order of the operands does not matter, as we |
| /// evaluate the score of all profitable combinations of operands. In |
| /// other words the score of G1 and G4 is the same as G1 and G2. This |
| /// heuristic is based on ideas described in: |
| /// Look-ahead SLP: Auto-vectorization in the presence of commutative |
| /// operations, CGO 2018 by Vasileios Porpodas, Rodrigo C. O. Rocha, |
| /// LuÃs F. W. Góes |
| int getScoreAtLevelRec(const std::pair<Value *, int> &LHS, |
| const std::pair<Value *, int> &RHS, int CurrLevel, |
| int MaxLevel) { |
| |
| Value *V1 = LHS.first; |
| Value *V2 = RHS.first; |
| // Get the shallow score of V1 and V2. |
| int ShallowScoreAtThisLevel = |
| std::max((int)ScoreFail, getShallowScore(V1, V2, DL, SE) - |
| getExternalUsesCost(LHS, RHS)); |
| int Lane1 = LHS.second; |
| int Lane2 = RHS.second; |
| |
| // If reached MaxLevel, |
| // or if V1 and V2 are not instructions, |
| // or if they are SPLAT, |
| // or if they are not consecutive, early return the current cost. |
| auto *I1 = dyn_cast<Instruction>(V1); |
| auto *I2 = dyn_cast<Instruction>(V2); |
| if (CurrLevel == MaxLevel || !(I1 && I2) || I1 == I2 || |
| ShallowScoreAtThisLevel == VLOperands::ScoreFail || |
| (isa<LoadInst>(I1) && isa<LoadInst>(I2) && ShallowScoreAtThisLevel)) |
| return ShallowScoreAtThisLevel; |
| assert(I1 && I2 && "Should have early exited."); |
| |
| // Keep track of in-tree values for determining the external-use cost. |
| InLookAheadValues[V1] = Lane1; |
| InLookAheadValues[V2] = Lane2; |
| |
| // Contains the I2 operand indexes that got matched with I1 operands. |
| SmallSet<unsigned, 4> Op2Used; |
| |
| // Recursion towards the operands of I1 and I2. We are trying all possbile |
| // operand pairs, and keeping track of the best score. |
| for (unsigned OpIdx1 = 0, NumOperands1 = I1->getNumOperands(); |
| OpIdx1 != NumOperands1; ++OpIdx1) { |
| // Try to pair op1I with the best operand of I2. |
| int MaxTmpScore = 0; |
| unsigned MaxOpIdx2 = 0; |
| bool FoundBest = false; |
| // If I2 is commutative try all combinations. |
| unsigned FromIdx = isCommutative(I2) ? 0 : OpIdx1; |
| unsigned ToIdx = isCommutative(I2) |
| ? I2->getNumOperands() |
| : std::min(I2->getNumOperands(), OpIdx1 + 1); |
| assert(FromIdx <= ToIdx && "Bad index"); |
| for (unsigned OpIdx2 = FromIdx; OpIdx2 != ToIdx; ++OpIdx2) { |
| // Skip operands already paired with OpIdx1. |
| if (Op2Used.count(OpIdx2)) |
| continue; |
| // Recursively calculate the cost at each level |
| int TmpScore = getScoreAtLevelRec({I1->getOperand(OpIdx1), Lane1}, |
| {I2->getOperand(OpIdx2), Lane2}, |
| CurrLevel + 1, MaxLevel); |
| // Look for the best score. |
| if (TmpScore > VLOperands::ScoreFail && TmpScore > MaxTmpScore) { |
| MaxTmpScore = TmpScore; |
| MaxOpIdx2 = OpIdx2; |
| FoundBest = true; |
| } |
| } |
| if (FoundBest) { |
| // Pair {OpIdx1, MaxOpIdx2} was found to be best. Never revisit it. |
| Op2Used.insert(MaxOpIdx2); |
| ShallowScoreAtThisLevel += MaxTmpScore; |
| } |
| } |
| return ShallowScoreAtThisLevel; |
| } |
| |
| /// \Returns the look-ahead score, which tells us how much the sub-trees |
| /// rooted at \p LHS and \p RHS match, the more they match the higher the |
| /// score. This helps break ties in an informed way when we cannot decide on |
| /// the order of the operands by just considering the immediate |
| /// predecessors. |
| int getLookAheadScore(const std::pair<Value *, int> &LHS, |
| const std::pair<Value *, int> &RHS) { |
| InLookAheadValues.clear(); |
| return getScoreAtLevelRec(LHS, RHS, 1, LookAheadMaxDepth); |
| } |
| |
| // Search all operands in Ops[*][Lane] for the one that matches best |
| // Ops[OpIdx][LastLane] and return its opreand index. |
| // If no good match can be found, return None. |
| Optional<unsigned> |
| getBestOperand(unsigned OpIdx, int Lane, int LastLane, |
| ArrayRef<ReorderingMode> ReorderingModes) { |
| unsigned NumOperands = getNumOperands(); |
| |
| // The operand of the previous lane at OpIdx. |
| Value *OpLastLane = getData(OpIdx, LastLane).V; |
| |
| // Our strategy mode for OpIdx. |
| ReorderingMode RMode = ReorderingModes[OpIdx]; |
| |
| // The linearized opcode of the operand at OpIdx, Lane. |
| bool OpIdxAPO = getData(OpIdx, Lane).APO; |
| |
| // The best operand index and its score. |
| // Sometimes we have more than one option (e.g., Opcode and Undefs), so we |
| // are using the score to differentiate between the two. |
| struct BestOpData { |
| Optional<unsigned> Idx = None; |
| unsigned Score = 0; |
| } BestOp; |
| |
| // Iterate through all unused operands and look for the best. |
| for (unsigned Idx = 0; Idx != NumOperands; ++Idx) { |
| // Get the operand at Idx and Lane. |
| OperandData &OpData = getData(Idx, Lane); |
| Value *Op = OpData.V; |
| bool OpAPO = OpData.APO; |
| |
| // Skip already selected operands. |
| if (OpData.IsUsed) |
| continue; |
| |
| // Skip if we are trying to move the operand to a position with a |
| // different opcode in the linearized tree form. This would break the |
| // semantics. |
| if (OpAPO != OpIdxAPO) |
| continue; |
| |
| // Look for an operand that matches the current mode. |
| switch (RMode) { |
| case ReorderingMode::Load: |
| case ReorderingMode::Constant: |
| case ReorderingMode::Opcode: { |
| bool LeftToRight = Lane > LastLane; |
| Value *OpLeft = (LeftToRight) ? OpLastLane : Op; |
| Value *OpRight = (LeftToRight) ? Op : OpLastLane; |
| unsigned Score = |
| getLookAheadScore({OpLeft, LastLane}, {OpRight, Lane}); |
| if (Score > BestOp.Score) { |
| BestOp.Idx = Idx; |
| BestOp.Score = Score; |
| } |
| break; |
| } |
| case ReorderingMode::Splat: |
| if (Op == OpLastLane) |
| BestOp.Idx = Idx; |
| break; |
| case ReorderingMode::Failed: |
| return None; |
| } |
| } |
| |
| if (BestOp.Idx) { |
| getData(BestOp.Idx.getValue(), Lane).IsUsed = true; |
| return BestOp.Idx; |
| } |
| // If we could not find a good match return None. |
| return None; |
| } |
| |
| /// Helper for reorderOperandVecs. \Returns the lane that we should start |
| /// reordering from. This is the one which has the least number of operands |
| /// that can freely move about. |
| unsigned getBestLaneToStartReordering() const { |
| unsigned BestLane = 0; |
| unsigned Min = UINT_MAX; |
| for (unsigned Lane = 0, NumLanes = getNumLanes(); Lane != NumLanes; |
| ++Lane) { |
| unsigned NumFreeOps = getMaxNumOperandsThatCanBeReordered(Lane); |
| if (NumFreeOps < Min) { |
| Min = NumFreeOps; |
| BestLane = Lane; |
| } |
| } |
| return BestLane; |
| } |
| |
| /// \Returns the maximum number of operands that are allowed to be reordered |
| /// for \p Lane. This is used as a heuristic for selecting the first lane to |
| /// start operand reordering. |
| unsigned getMaxNumOperandsThatCanBeReordered(unsigned Lane) const { |
| unsigned CntTrue = 0; |
| unsigned NumOperands = getNumOperands(); |
| // Operands with the same APO can be reordered. We therefore need to count |
| // how many of them we have for each APO, like this: Cnt[APO] = x. |
| // Since we only have two APOs, namely true and false, we can avoid using |
| // a map. Instead we can simply count the number of operands that |
| // correspond to one of them (in this case the 'true' APO), and calculate |
| // the other by subtracting it from the total number of operands. |
| for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) |
| if (getData(OpIdx, Lane).APO) |
| ++CntTrue; |
| unsigned CntFalse = NumOperands - CntTrue; |
| return std::max(CntTrue, CntFalse); |
| } |
| |
| /// Go through the instructions in VL and append their operands. |
| void appendOperandsOfVL(ArrayRef<Value *> VL) { |
| assert(!VL.empty() && "Bad VL"); |
| assert((empty() || VL.size() == getNumLanes()) && |
| "Expected same number of lanes"); |
| assert(isa<Instruction>(VL[0]) && "Expected instruction"); |
| unsigned NumOperands = cast<Instruction>(VL[0])->getNumOperands(); |
| OpsVec.resize(NumOperands); |
| unsigned NumLanes = VL.size(); |
| for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { |
| OpsVec[OpIdx].resize(NumLanes); |
| for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { |
| assert(isa<Instruction>(VL[Lane]) && "Expected instruction"); |
| // Our tree has just 3 nodes: the root and two operands. |
| // It is therefore trivial to get the APO. We only need to check the |
| // opcode of VL[Lane] and whether the operand at OpIdx is the LHS or |
| // RHS operand. The LHS operand of both add and sub is never attached |
| // to an inversese operation in the linearized form, therefore its APO |
| // is false. The RHS is true only if VL[Lane] is an inverse operation. |
| |
| // Since operand reordering is performed on groups of commutative |
| // operations or alternating sequences (e.g., +, -), we can safely |
| // tell the inverse operations by checking commutativity. |
| bool IsInverseOperation = !isCommutative(cast<Instruction>(VL[Lane])); |
| bool APO = (OpIdx == 0) ? false : IsInverseOperation; |
| OpsVec[OpIdx][Lane] = {cast<Instruction>(VL[Lane])->getOperand(OpIdx), |
| APO, false}; |
| } |
| } |
| } |
| |
| /// \returns the number of operands. |
| unsigned getNumOperands() const { return OpsVec.size(); } |
| |
| /// \returns the number of lanes. |
| unsigned getNumLanes() const { return OpsVec[0].size(); } |
| |
| /// \returns the operand value at \p OpIdx and \p Lane. |
| Value *getValue(unsigned OpIdx, unsigned Lane) const { |
| return getData(OpIdx, Lane).V; |
| } |
| |
| /// \returns true if the data structure is empty. |
| bool empty() const { return OpsVec.empty(); } |
| |
| /// Clears the data. |
| void clear() { OpsVec.clear(); } |
| |
| /// \Returns true if there are enough operands identical to \p Op to fill |
| /// the whole vector. |
| /// Note: This modifies the 'IsUsed' flag, so a cleanUsed() must follow. |
| bool shouldBroadcast(Value *Op, unsigned OpIdx, unsigned Lane) { |
| bool OpAPO = getData(OpIdx, Lane).APO; |
| for (unsigned Ln = 0, Lns = getNumLanes(); Ln != Lns; ++Ln) { |
| if (Ln == Lane) |
| continue; |
| // This is set to true if we found a candidate for broadcast at Lane. |
| bool FoundCandidate = false; |
| for (unsigned OpI = 0, OpE = getNumOperands(); OpI != OpE; ++OpI) { |
| OperandData &Data = getData(OpI, Ln); |
| if (Data.APO != OpAPO || Data.IsUsed) |
| continue; |
| if (Data.V == Op) { |
| FoundCandidate = true; |
| Data.IsUsed = true; |
| break; |
| } |
| } |
| if (!FoundCandidate) |
| return false; |
| } |
| return true; |
| } |
| |
| public: |
| /// Initialize with all the operands of the instruction vector \p RootVL. |
| VLOperands(ArrayRef<Value *> RootVL, const DataLayout &DL, |
| ScalarEvolution &SE, const BoUpSLP &R) |
| : DL(DL), SE(SE), R(R) { |
| // Append all the operands of RootVL. |
| appendOperandsOfVL(RootVL); |
| } |
| |
| /// \Returns a value vector with the operands across all lanes for the |
| /// opearnd at \p OpIdx. |
| ValueList getVL(unsigned OpIdx) const { |
| ValueList OpVL(OpsVec[OpIdx].size()); |
| assert(OpsVec[OpIdx].size() == getNumLanes() && |
| "Expected same num of lanes across all operands"); |
| for (unsigned Lane = 0, Lanes = getNumLanes(); Lane != Lanes; ++Lane) |
| OpVL[Lane] = OpsVec[OpIdx][Lane].V; |
| return OpVL; |
| } |
| |
| // Performs operand reordering for 2 or more operands. |
| // The original operands are in OrigOps[OpIdx][Lane]. |
| // The reordered operands are returned in 'SortedOps[OpIdx][Lane]'. |
| void reorder() { |
| unsigned NumOperands = getNumOperands(); |
| unsigned NumLanes = getNumLanes(); |
| // Each operand has its own mode. We are using this mode to help us select |
| // the instructions for each lane, so that they match best with the ones |
| // we have selected so far. |
| SmallVector<ReorderingMode, 2> ReorderingModes(NumOperands); |
| |
| // This is a greedy single-pass algorithm. We are going over each lane |
| // once and deciding on the best order right away with no back-tracking. |
| // However, in order to increase its effectiveness, we start with the lane |
| // that has operands that can move the least. For example, given the |
| // following lanes: |
| // Lane 0 : A[0] = B[0] + C[0] // Visited 3rd |
| // Lane 1 : A[1] = C[1] - B[1] // Visited 1st |
| // Lane 2 : A[2] = B[2] + C[2] // Visited 2nd |
| // Lane 3 : A[3] = C[3] - B[3] // Visited 4th |
| // we will start at Lane 1, since the operands of the subtraction cannot |
| // be reordered. Then we will visit the rest of the lanes in a circular |
| // fashion. That is, Lanes 2, then Lane 0, and finally Lane 3. |
| |
| // Find the first lane that we will start our search from. |
| unsigned FirstLane = getBestLaneToStartReordering(); |
| |
| // Initialize the modes. |
| for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { |
| Value *OpLane0 = getValue(OpIdx, FirstLane); |
| // Keep track if we have instructions with all the same opcode on one |
| // side. |
| if (isa<LoadInst>(OpLane0)) |
| ReorderingModes[OpIdx] = ReorderingMode::Load; |
| else if (isa<Instruction>(OpLane0)) { |
| // Check if OpLane0 should be broadcast. |
| if (shouldBroadcast(OpLane0, OpIdx, FirstLane)) |
| ReorderingModes[OpIdx] = ReorderingMode::Splat; |
| else |
| ReorderingModes[OpIdx] = ReorderingMode::Opcode; |
| } |
| else if (isa<Constant>(OpLane0)) |
| ReorderingModes[OpIdx] = ReorderingMode::Constant; |
| else if (isa<Argument>(OpLane0)) |
| // Our best hope is a Splat. It may save some cost in some cases. |
| ReorderingModes[OpIdx] = ReorderingMode::Splat; |
| else |
| // NOTE: This should be unreachable. |
| ReorderingModes[OpIdx] = ReorderingMode::Failed; |
| } |
| |
| // If the initial strategy fails for any of the operand indexes, then we |
| // perform reordering again in a second pass. This helps avoid assigning |
| // high priority to the failed strategy, and should improve reordering for |
| // the non-failed operand indexes. |
| for (int Pass = 0; Pass != 2; ++Pass) { |
| // Skip the second pass if the first pass did not fail. |
| bool StrategyFailed = false; |
| // Mark all operand data as free to use. |
| clearUsed(); |
| // We keep the original operand order for the FirstLane, so reorder the |
| // rest of the lanes. We are visiting the nodes in a circular fashion, |
| // using FirstLane as the center point and increasing the radius |
| // distance. |
| for (unsigned Distance = 1; Distance != NumLanes; ++Distance) { |
| // Visit the lane on the right and then the lane on the left. |
| for (int Direction : {+1, -1}) { |
| int Lane = FirstLane + Direction * Distance; |
| if (Lane < 0 || Lane >= (int)NumLanes) |
| continue; |
| int LastLane = Lane - Direction; |
| assert(LastLane >= 0 && LastLane < (int)NumLanes && |
| "Out of bounds"); |
| // Look for a good match for each operand. |
| for (unsigned OpIdx = 0; OpIdx != NumOperands; ++OpIdx) { |
| // Search for the operand that matches SortedOps[OpIdx][Lane-1]. |
| Optional<unsigned> BestIdx = |
| getBestOperand(OpIdx, Lane, LastLane, ReorderingModes); |
| // By not selecting a value, we allow the operands that follow to |
| // select a better matching value. We will get a non-null value in |
| // the next run of getBestOperand(). |
| if (BestIdx) { |
| // Swap the current operand with the one returned by |
| // getBestOperand(). |
| swap(OpIdx, BestIdx.getValue(), Lane); |
| } else { |
| // We failed to find a best operand, set mode to 'Failed'. |
| ReorderingModes[OpIdx] = ReorderingMode::Failed; |
| // Enable the second pass. |
| StrategyFailed = true; |
| } |
| } |
| } |
| } |
| // Skip second pass if the strategy did not fail. |
| if (!StrategyFailed) |
| break; |
| } |
| } |
| |
| #if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP) |
| LLVM_DUMP_METHOD static StringRef getModeStr(ReorderingMode RMode) { |
| switch (RMode) { |
| case ReorderingMode::Load: |
| return "Load"; |
| case ReorderingMode::Opcode: |
| return "Opcode"; |
| case ReorderingMode::Constant: |
| return "Constant"; |
| case ReorderingMode::Splat: |
| return "Splat"; |
| case ReorderingMode::Failed: |
| return "Failed"; |
| } |
| llvm_unreachable("Unimplemented Reordering Type"); |
| } |
| |
| LLVM_DUMP_METHOD static raw_ostream &printMode(ReorderingMode RMode, |
| raw_ostream &OS) { |
| return OS << getModeStr(RMode); |
| } |
| |
| /// Debug print. |
| LLVM_DUMP_METHOD static void dumpMode(ReorderingMode RMode) { |
| printMode(RMode, dbgs()); |
| } |
| |
| friend raw_ostream &operator<<(raw_ostream &OS, ReorderingMode RMode) { |
| return printMode(RMode, OS); |
| } |
| |
| LLVM_DUMP_METHOD raw_ostream &print(raw_ostream &OS) const { |
| const unsigned Indent = 2; |
| unsigned Cnt = 0; |
| for (const OperandDataVec &OpDataVec : OpsVec) { |
| OS << "Operand " << Cnt++ << "\n"; |
| for (const OperandData &OpData : OpDataVec) { |
| OS.indent(Indent) << "{"; |
| if (Value *V = OpData.V) |
| OS << *V; |
| else |
| OS << "null"; |
| OS << ", APO:" << OpData.APO << "}\n"; |
| } |
| OS << "\n"; |
| } |
| return OS; |
| } |
| |
| /// Debug print. |
| LLVM_DUMP_METHOD void dump() const { print(dbgs()); } |
| #endif |
| }; |
| |
| /// Checks if the instruction is marked for deletion. |
| bool isDeleted(Instruction *I) const { return DeletedInstructions.count(I); } |
| |
| /// Marks values operands for later deletion by replacing them with Undefs. |
| void eraseInstructions(ArrayRef<Value *> AV); |
| |
| ~BoUpSLP(); |
| |
| private: |
| /// Checks if all users of \p I are the part of the vectorization tree. |
| bool areAllUsersVectorized(Instruction *I, |
| ArrayRef<Value *> VectorizedVals) const; |
| |
| /// \returns the cost of the vectorizable entry. |
| InstructionCost getEntryCost(const TreeEntry *E, |
| ArrayRef<Value *> VectorizedVals); |
| |
| /// This is the recursive part of buildTree. |
| void buildTree_rec(ArrayRef<Value *> Roots, unsigned Depth, |
| const EdgeInfo &EI); |
| |
| /// \returns true if the ExtractElement/ExtractValue instructions in \p VL can |
| /// be vectorized to use the original vector (or aggregate "bitcast" to a |
| /// vector) and sets \p CurrentOrder to the identity permutation; otherwise |
| /// returns false, setting \p CurrentOrder to either an empty vector or a |
| /// non-identity permutation that allows to reuse extract instructions. |
| bool canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, |
| SmallVectorImpl<unsigned> &CurrentOrder) const; |
| |
| /// Vectorize a single entry in the tree. |
| Value *vectorizeTree(TreeEntry *E); |
| |
| /// Vectorize a single entry in the tree, 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. If \p |
| /// NeedToShuffle is true, need to add a cost of reshuffling some of the |
| /// vector elements. |
| InstructionCost getGatherCost(FixedVectorType *Ty, |
| const DenseSet<unsigned> &ShuffledIndices, |
| bool NeedToShuffle) const; |
| |
| /// Checks if the gathered \p VL can be represented as shuffle(s) of previous |
| /// tree entries. |
| /// \returns ShuffleKind, if gathered values can be represented as shuffles of |
| /// previous tree entries. \p Mask is filled with the shuffle mask. |
| Optional<TargetTransformInfo::ShuffleKind> |
| isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, |
| SmallVectorImpl<const TreeEntry *> &Entries); |
| |
| /// \returns the scalarization cost for this list of values. Assuming that |
| /// this subtree gets vectorized, we may need to extract the values from the |
| /// roots. This method calculates the cost of extracting the values. |
| InstructionCost getGatherCost(ArrayRef<Value *> VL) const; |
| |
| /// Set the Builder insert point to one after the last instruction in |
| /// the bundle |
| void setInsertPointAfterBundle(const TreeEntry *E); |
| |
| /// \returns a vector from a collection of scalars in \p VL. |
| Value *gather(ArrayRef<Value *> VL); |
| |
| /// \returns whether the VectorizableTree is fully vectorizable and will |
| /// be beneficial even the tree height is tiny. |
| bool isFullyVectorizableTinyTree(bool ForReduction) const; |
| |
| /// Reorder commutative or alt operands to get better probability of |
| /// generating vectorized code. |
| static void reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, |
| SmallVectorImpl<Value *> &Left, |
| SmallVectorImpl<Value *> &Right, |
| const DataLayout &DL, |
| ScalarEvolution &SE, |
| const BoUpSLP &R); |
| struct TreeEntry { |
| using VecTreeTy = SmallVector<std::unique_ptr<TreeEntry>, 8>; |
| TreeEntry(VecTreeTy &Container) : Container(Container) {} |
| |
| /// \returns true if the scalars in VL are equal to this entry. |
| bool isSame(ArrayRef<Value *> VL) const { |
| auto &&IsSame = [VL](ArrayRef<Value *> Scalars, ArrayRef<int> Mask) { |
| if (Mask.size() != VL.size() && VL.size() == Scalars.size()) |
| return std::equal(VL.begin(), VL.end(), Scalars.begin()); |
| return VL.size() == Mask.size() && |
| std::equal(VL.begin(), VL.end(), Mask.begin(), |
| [Scalars](Value *V, int Idx) { |
| return (isa<UndefValue>(V) && |
| Idx == UndefMaskElem) || |
| (Idx != UndefMaskElem && V == Scalars[Idx]); |
| }); |
| }; |
| if (!ReorderIndices.empty()) { |
| // TODO: implement matching if the nodes are just reordered, still can |
| // treat the vector as the same if the list of scalars matches VL |
| // directly, without reordering. |
| SmallVector<int> Mask; |
| inversePermutation(ReorderIndices, Mask); |
| if (VL.size() == Scalars.size()) |
| return IsSame(Scalars, Mask); |
| if (VL.size() == ReuseShuffleIndices.size()) { |
| ::addMask(Mask, ReuseShuffleIndices); |
| return IsSame(Scalars, Mask); |
| } |
| return false; |
| } |
| return IsSame(Scalars, ReuseShuffleIndices); |
| } |
| |
| /// \returns true if current entry has same operands as \p TE. |
| bool hasEqualOperands(const TreeEntry &TE) const { |
| if (TE.getNumOperands() != getNumOperands()) |
| return false; |
| SmallBitVector Used(getNumOperands()); |
| for (unsigned I = 0, E = getNumOperands(); I < E; ++I) { |
| unsigned PrevCount = Used.count(); |
| for (unsigned K = 0; K < E; ++K) { |
| if (Used.test(K)) |
| continue; |
| if (getOperand(K) == TE.getOperand(I)) { |
| Used.set(K); |
| break; |
| } |
| } |
| // Check if we actually found the matching operand. |
| if (PrevCount == Used.count()) |
| return false; |
| } |
| return true; |
| } |
| |
| /// \return Final vectorization factor for the node. Defined by the total |
| /// number of vectorized scalars, including those, used several times in the |
| /// entry and counted in the \a ReuseShuffleIndices, if any. |
| unsigned getVectorFactor() const { |
| if (!ReuseShuffleIndices.empty()) |
| return ReuseShuffleIndices.size(); |
| return Scalars.size(); |
| }; |
| |
| /// A vector of scalars. |
| ValueList Scalars; |
| |
| /// The Scalars are vectorized into this value. It is initialized to Null. |
| Value *VectorizedValue = nullptr; |
| |
| /// Do we need to gather this sequence or vectorize it |
| /// (either with vector instruction or with scatter/gather |
| /// intrinsics for store/load)? |
| enum EntryState { Vectorize, ScatterVectorize, NeedToGather }; |
| EntryState State; |
| |
| /// Does this sequence require some shuffling? |
| SmallVector<int, 4> ReuseShuffleIndices; |
| |
| /// Does this entry require reordering? |
| SmallVector<unsigned, 4> ReorderIndices; |
| |
| /// Points back to the VectorizableTree. |
| /// |
| /// Only used for Graphviz right now. Unfortunately GraphTrait::NodeRef has |
| /// to be a pointer and needs to be able to initialize the child iterator. |
| /// Thus we need a reference back to the container to translate the indices |
| /// to entries. |
| VecTreeTy &Container; |
| |
| /// The TreeEntry index containing the user of this entry. We can actually |
| /// have multiple users so the data structure is not truly a tree. |
| SmallVector<EdgeInfo, 1> UserTreeIndices; |
| |
| /// The index of this treeEntry in VectorizableTree. |
| int Idx = -1; |
| |
| private: |
| /// The operands of each instruction in each lane Operands[op_index][lane]. |
| /// Note: This helps avoid the replication of the code that performs the |
| /// reordering of operands during buildTree_rec() and vectorizeTree(). |
| SmallVector<ValueList, 2> Operands; |
| |
| /// The main/alternate instruction. |
| Instruction *MainOp = nullptr; |
| Instruction *AltOp = nullptr; |
| |
| public: |
| /// Set this bundle's \p OpIdx'th operand to \p OpVL. |
| void setOperand(unsigned OpIdx, ArrayRef<Value *> OpVL) { |
| if (Operands.size() < OpIdx + 1) |
| Operands.resize(OpIdx + 1); |
| assert(Operands[OpIdx].empty() && "Already resized?"); |
| Operands[OpIdx].resize(Scalars.size()); |
| for (unsigned Lane = 0, E = Scalars.size(); Lane != E; ++Lane) |
| Operands[OpIdx][Lane] = OpVL[Lane]; |
| } |
| |
| /// Set the operands of this bundle in their original order. |
| void setOperandsInOrder() { |
| assert(Operands.empty() && "Already initialized?"); |
| auto *I0 = cast<Instruction>(Scalars[0]); |
| Operands.resize(I0->getNumOperands()); |
| unsigned NumLanes = Scalars.size(); |
| for (unsigned OpIdx = 0, NumOperands = I0->getNumOperands(); |
| OpIdx != NumOperands; ++OpIdx) { |
| Operands[OpIdx].resize(NumLanes); |
| for (unsigned Lane = 0; Lane != NumLanes; ++Lane) { |
| auto *I = cast<Instruction>(Scalars[Lane]); |
| assert(I->getNumOperands() == NumOperands && |
| "Expected same number of operands"); |
| Operands[OpIdx][Lane] = I->getOperand(OpIdx); |
| } |
| } |
| } |
| |
| /// Reorders operands of the node to the given mask \p Mask. |
| void reorderOperands(ArrayRef<int> Mask) { |
| for (ValueList &Operand : Operands) |
| reorderScalars(Operand, Mask); |
| } |
| |
| /// \returns the \p OpIdx operand of this TreeEntry. |
| ValueList &getOperand(unsigned OpIdx) { |
| assert(OpIdx < Operands.size() && "Off bounds"); |
| return Operands[OpIdx]; |
| } |
| |
| /// \returns the \p OpIdx operand of this TreeEntry. |
| ArrayRef<Value *> getOperand(unsigned OpIdx) const { |
| assert(OpIdx < Operands.size() && "Off bounds"); |
| return Operands[OpIdx]; |
| } |
| |
| /// \returns the number of operands. |
| unsigned getNumOperands() const { return Operands.size(); } |
| |
| /// \return the single \p OpIdx operand. |
| Value *getSingleOperand(unsigned OpIdx) const { |
| assert(OpIdx < Operands.size() && "Off bounds"); |
| assert(!Operands[OpIdx].empty() && "No operand available"); |
| return Operands[OpIdx][0]; |
| } |
| |
| /// Some of the instructions in the list have alternate opcodes. |
| bool isAltShuffle() const { |
| return getOpcode() != getAltOpcode(); |
| } |
| |
| bool isOpcodeOrAlt(Instruction *I) const { |
| unsigned CheckedOpcode = I->getOpcode(); |
| return (getOpcode() == CheckedOpcode || |
| getAltOpcode() == CheckedOpcode); |
| } |
| |
| /// Chooses the correct key for scheduling data. If \p Op has the same (or |
| /// alternate) opcode as \p OpValue, the key is \p Op. Otherwise the key is |
| /// \p OpValue. |
| Value *isOneOf(Value *Op) const { |
| auto *I = dyn_cast<Instruction>(Op); |
| if (I && isOpcodeOrAlt(I)) |
| return Op; |
| return MainOp; |
| } |
| |
| void setOperations(const InstructionsState &S) { |
| MainOp = S.MainOp; |
| AltOp = S.AltOp; |
| } |
| |
| Instruction *getMainOp() const { |
| return MainOp; |
| } |
| |
| Instruction *getAltOp() const { |
| return AltOp; |
| } |
| |
| /// The main/alternate opcodes for the list of instructions. |
| unsigned getOpcode() const { |
| return MainOp ? MainOp->getOpcode() : 0; |
| } |
| |
| unsigned getAltOpcode() const { |
| return AltOp ? AltOp->getOpcode() : 0; |
| } |
| |
| /// When ReuseReorderShuffleIndices is empty it just returns position of \p |
| /// V within vector of Scalars. Otherwise, try to remap on its reuse index. |
| int findLaneForValue(Value *V) const { |
| unsigned FoundLane = std::distance(Scalars.begin(), find(Scalars, V)); |
| assert(FoundLane < Scalars.size() && "Couldn't find extract lane"); |
| if (!ReorderIndices.empty()) |
| FoundLane = ReorderIndices[FoundLane]; |
| assert(FoundLane < Scalars.size() && "Couldn't find extract lane"); |
| if (!ReuseShuffleIndices.empty()) { |
| FoundLane = std::distance(ReuseShuffleIndices.begin(), |
| find(ReuseShuffleIndices, FoundLane)); |
| } |
| return FoundLane; |
| } |
| |
| #ifndef NDEBUG |
| /// Debug printer. |
| LLVM_DUMP_METHOD void dump() const { |
| dbgs() << Idx << ".\n"; |
| for (unsigned OpI = 0, OpE = Operands.size(); OpI != OpE; ++OpI) { |
| dbgs() << "Operand " << OpI << ":\n"; |
| for (const Value *V : Operands[OpI]) |
| dbgs().indent(2) << *V << "\n"; |
| } |
| dbgs() << "Scalars: \n"; |
| for (Value *V : Scalars) |
| dbgs().indent(2) << *V << "\n"; |
| dbgs() << "State: "; |
| switch (State) { |
| case Vectorize: |
| dbgs() << "Vectorize\n"; |
| break; |
| case ScatterVectorize: |
| dbgs() << "ScatterVectorize\n"; |
| break; |
| case NeedToGather: |
| dbgs() << "NeedToGather\n"; |
| break; |
| } |
| dbgs() << "MainOp: "; |
| if (MainOp) |
| dbgs() << *MainOp << "\n"; |
| else |
| dbgs() << "NULL\n"; |
| dbgs() << "AltOp: "; |
| if (AltOp) |
| dbgs() << *AltOp << "\n"; |
| else |
| dbgs() << "NULL\n"; |
| dbgs() << "VectorizedValue: "; |
| if (VectorizedValue) |
| dbgs() << *VectorizedValue << "\n"; |
| else |
| dbgs() << "NULL\n"; |
| dbgs() << "ReuseShuffleIndices: "; |
| if (ReuseShuffleIndices.empty()) |
| dbgs() << "Empty"; |
| else |
| for (unsigned ReuseIdx : ReuseShuffleIndices) |
| dbgs() << ReuseIdx << ", "; |
| dbgs() << "\n"; |
| dbgs() << "ReorderIndices: "; |
| for (unsigned ReorderIdx : ReorderIndices) |
| dbgs() << ReorderIdx << ", "; |
| dbgs() << "\n"; |
| dbgs() << "UserTreeIndices: "; |
| for (const auto &EInfo : UserTreeIndices) |
| dbgs() << EInfo << ", "; |
| dbgs() << "\n"; |
| } |
| #endif |
| }; |
| |
| #ifndef NDEBUG |
| void dumpTreeCosts(const TreeEntry *E, InstructionCost ReuseShuffleCost, |
| InstructionCost VecCost, |
| InstructionCost ScalarCost) const { |
| dbgs() << "SLP: Calculated costs for Tree:\n"; E->dump(); |
| dbgs() << "SLP: Costs:\n"; |
| dbgs() << "SLP: ReuseShuffleCost = " << ReuseShuffleCost << "\n"; |
| dbgs() << "SLP: VectorCost = " << VecCost << "\n"; |
| dbgs() << "SLP: ScalarCost = " << ScalarCost << "\n"; |
| dbgs() << "SLP: ReuseShuffleCost + VecCost - ScalarCost = " << |
| ReuseShuffleCost + VecCost - ScalarCost << "\n"; |
| } |
| #endif |
| |
| /// Create a new VectorizableTree entry. |
| TreeEntry *newTreeEntry(ArrayRef<Value *> VL, Optional<ScheduleData *> Bundle, |
| const InstructionsState &S, |
| const EdgeInfo &UserTreeIdx, |
| ArrayRef<int> ReuseShuffleIndices = None, |
| ArrayRef<unsigned> ReorderIndices = None) { |
| TreeEntry::EntryState EntryState = |
| Bundle ? TreeEntry::Vectorize : TreeEntry::NeedToGather; |
| return newTreeEntry(VL, EntryState, Bundle, S, UserTreeIdx, |
| ReuseShuffleIndices, ReorderIndices); |
| } |
| |
| TreeEntry *newTreeEntry(ArrayRef<Value *> VL, |
| TreeEntry::EntryState EntryState, |
| Optional<ScheduleData *> Bundle, |
| const InstructionsState &S, |
| const EdgeInfo &UserTreeIdx, |
| ArrayRef<int> ReuseShuffleIndices = None, |
| ArrayRef<unsigned> ReorderIndices = None) { |
| assert(((!Bundle && EntryState == TreeEntry::NeedToGather) || |
| (Bundle && EntryState != TreeEntry::NeedToGather)) && |
| "Need to vectorize gather entry?"); |
| VectorizableTree.push_back(std::make_unique<TreeEntry>(VectorizableTree)); |
| TreeEntry *Last = VectorizableTree.back().get(); |
| Last->Idx = VectorizableTree.size() - 1; |
| Last->State = EntryState; |
| Last->ReuseShuffleIndices.append(ReuseShuffleIndices.begin(), |
| ReuseShuffleIndices.end()); |
| if (ReorderIndices.empty()) { |
| Last->Scalars.assign(VL.begin(), VL.end()); |
| Last->setOperations(S); |
| } else { |
| // Reorder scalars and build final mask. |
| Last->Scalars.assign(VL.size(), nullptr); |
| transform(ReorderIndices, Last->Scalars.begin(), |
| [VL](unsigned Idx) -> Value * { |
| if (Idx >= VL.size()) |
| return UndefValue::get(VL.front()->getType()); |
| return VL[Idx]; |
| }); |
| InstructionsState S = getSameOpcode(Last->Scalars); |
| Last->setOperations(S); |
| Last->ReorderIndices.append(ReorderIndices.begin(), ReorderIndices.end()); |
| } |
| if (Last->State != TreeEntry::NeedToGather) { |
| for (Value *V : VL) { |
| assert(!getTreeEntry(V) && "Scalar already in tree!"); |
| ScalarToTreeEntry[V] = Last; |
| } |
| // Update the scheduler bundle to point to this TreeEntry. |
| unsigned Lane = 0; |
| for (ScheduleData *BundleMember = Bundle.getValue(); BundleMember; |
| BundleMember = BundleMember->NextInBundle) { |
| BundleMember->TE = Last; |
| BundleMember->Lane = Lane; |
| ++Lane; |
| } |
| assert((!Bundle.getValue() || Lane == VL.size()) && |
| "Bundle and VL out of sync"); |
| } else { |
| MustGather.insert(VL.begin(), VL.end()); |
| } |
| |
| if (UserTreeIdx.UserTE) |
| Last->UserTreeIndices.push_back(UserTreeIdx); |
| |
| return Last; |
| } |
| |
| /// -- Vectorization State -- |
| /// Holds all of the tree entries. |
| TreeEntry::VecTreeTy VectorizableTree; |
| |
| #ifndef NDEBUG |
| /// Debug printer. |
| LLVM_DUMP_METHOD void dumpVectorizableTree() const { |
| for (unsigned Id = 0, IdE = VectorizableTree.size(); Id != IdE; ++Id) { |
| VectorizableTree[Id]->dump(); |
| dbgs() << "\n"; |
| } |
| } |
| #endif |
| |
| TreeEntry *getTreeEntry(Value *V) { return ScalarToTreeEntry.lookup(V); } |
| |
| const TreeEntry *getTreeEntry(Value *V) const { |
| return ScalarToTreeEntry.lookup(V); |
| } |
| |
| /// Maps a specific scalar to its tree entry. |
| SmallDenseMap<Value*, TreeEntry *> ScalarToTreeEntry; |
| |
| /// Maps a value to the proposed vectorizable size. |
| SmallDenseMap<Value *, unsigned> InstrElementSize; |
| |
| /// A list of scalars that we found that we need to keep as scalars. |
| ValueSet MustGather; |
| |
| /// 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(); |
| } |
| bool aliased = true; |
| if (Loc1.Ptr && isSimple(Inst1)) |
| aliased = isModOrRefSet(AA->getModRefInfo(Inst2, Loc1)); |
| // Store the result in the cache. |
| result = aliased; |
| return aliased; |
| } |
| |
| using AliasCacheKey = std::pair<Instruction *, Instruction *>; |
| |
| /// Cache for alias results. |
| /// TODO: consider moving this to the AliasAnalysis itself. |
| DenseMap<AliasCacheKey, 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, bool ReplaceOpsWithUndef = false) { |
| auto It = DeletedInstructions.try_emplace(I, ReplaceOpsWithUndef).first; |
| It->getSecond() = It->getSecond() && ReplaceOpsWithUndef; |
| } |
| |
| /// Temporary store for deleted instructions. Instructions will be deleted |
| /// eventually when the BoUpSLP is destructed. |
| DenseMap<Instruction *, bool> 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 *> GatherShuffleSeq; |
| |
| /// 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; |
| TE = nullptr; |
| Lane = -1; |
| } |
| |
| /// 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; |
| |
| /// The TreeEntry that this instruction corresponds to. |
| TreeEntry *TE = nullptr; |
| |
| /// The lane of this node in the TreeEntry. |
| int Lane = -1; |
| }; |
| |
| #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) const { |
| return SD->SchedulingRegionID == SchedulingRegionID; |
| } |
| |
| /// Marks an instruction as scheduled and puts all dependent ready |
| /// instructions into the ready-list. |
| template <typename ReadyListType> |
| void schedule(ScheduleData *SD, ReadyListType &ReadyList) { |
| SD->IsScheduled = true; |
| LLVM_DEBUG(dbgs() << "SLP: schedule " << *SD << "\n"); |
| |
| ScheduleData *BundleMember = SD; |
| while (BundleMember) { |
| if (BundleMember->Inst != BundleMember->OpValue) { |
| BundleMember = BundleMember->NextInBundle; |
| continue; |
| } |
| // Handle the def-use chain dependencies. |
| |
| // Decrement the unscheduled counter and insert to ready list if ready. |
| auto &&DecrUnsched = [this, &ReadyList](Instruction *I) { |
| doForAllOpcodes(I, [&ReadyList](ScheduleData *OpDef) { |
| if (OpDef && OpDef->hasValidDependencies() && |
| OpDef->incrementUnscheduledDeps(-1) == 0) { |
| // There are no more unscheduled dependencies after |
| // decrementing, so we can put the dependent instruction |
| // into the ready list. |
| ScheduleData *DepBundle = OpDef->FirstInBundle; |
| assert(!DepBundle->IsScheduled && |
| "already scheduled bundle gets ready"); |
| ReadyList.insert(DepBundle); |
| LLVM_DEBUG(dbgs() |
| << "SLP: gets ready (def): " << *DepBundle << "\n"); |
| } |
| }); |
| }; |
| |
| // If BundleMember is a vector bundle, its operands may have been |
| // reordered duiring buildTree(). We therefore need to get its operands |
| // through the TreeEntry. |
| if (TreeEntry *TE = BundleMember->TE) { |
| int Lane = BundleMember->Lane; |
| assert(Lane >= 0 && "Lane not set"); |
| |
| // Since vectorization tree is being built recursively this assertion |
| // ensures that the tree entry has all operands set before reaching |
| // this code. Couple of exceptions known at the moment are extracts |
| // where their second (immediate) operand is not added. Since |
| // immediates do not affect scheduler behavior this is considered |
| // okay. |
| auto *In = TE->getMainOp(); |
| assert(In && |
| (isa<ExtractValueInst>(In) || isa<ExtractElementInst>(In) || |
| In->getNumOperands() == TE->getNumOperands()) && |
| "Missed TreeEntry operands?"); |
| (void)In; // fake use to avoid build failure when assertions disabled |
| |
| for (unsigned OpIdx = 0, NumOperands = TE->getNumOperands(); |
| OpIdx != NumOperands; ++OpIdx) |
| if (auto *I = dyn_cast<Instruction>(TE->getOperand(OpIdx)[Lane])) |
| DecrUnsched(I); |
| } else { |
| // If BundleMember is a stand-alone instruction, no operand reordering |
| // has taken place, so we directly access its operands. |
| for (Use &U : BundleMember->Inst->operands()) |
| if (auto *I = dyn_cast<Instruction>(U.get())) |
| DecrUnsched(I); |
| } |
| // Handle the memory dependencies. |
| for (ScheduleData *MemoryDepSD : BundleMember->MemoryDependencies) { |
| if (MemoryDepSD->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. |
| /// \returns the scheduling bundle. The returned Optional value is non-None |
| /// if \p VL is allowed to be scheduled. |
| Optional<ScheduleData *> |
| tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, |
| const InstructionsState &S); |
| |
| /// Un-bundles a group of instructions. |
| void cancelScheduling(ArrayRef<Value *> VL, Value *OpValue); |
| |
| /// Allocates schedule data chunk. |
| ScheduleData *allocateScheduleDataChunks(); |
| |
| /// Extends the scheduling region so that V is inside the region. |
| /// \returns true if the region size is within the limit. |
| bool extendSchedulingRegion(Value *V, const InstructionsState &S); |
| |
| /// Initialize the ScheduleData structures for new instructions in the |
| /// scheduling region. |
| void initScheduleData(Instruction *FromI, Instruction *ToI, |
| ScheduleData *PrevLoadStore, |
| ScheduleData *NextLoadStore); |
| |
| /// Updates the dependency information of a bundle and of all instructions/ |
| /// bundles which depend on the original bundle. |
| void calculateDependencies(ScheduleData *SD, bool InsertInReadyList, |
| BoUpSLP *SLP); |
| |
| /// Sets all instruction in the scheduling region to un-scheduled. |
| void resetSchedule(); |
| |
| BasicBlock *BB; |
| |
| /// Simple memory allocation for ScheduleData. |
| std::vector<std::unique_ptr<ScheduleData[]>> ScheduleDataChunks; |
| |
| /// The size of a ScheduleData array in ScheduleDataChunks. |
| int ChunkSize; |
| |
| /// The allocator position in the current chunk, which is the last entry |
| /// of ScheduleDataChunks. |
| int ChunkPos; |
| |
| /// Attaches ScheduleData to Instruction. |
| /// Note that the mapping survives during all vectorization iterations, i.e. |
| /// ScheduleData structures are recycled. |
| DenseMap<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; |
| |
| /// A DenseMapInfo implementation for holding DenseMaps and DenseSets of |
| /// sorted SmallVectors of unsigned. |
| struct OrdersTypeDenseMapInfo { |
| static OrdersType getEmptyKey() { |
| OrdersType V; |
| V.push_back(~1U); |
| return V; |
| } |
| |
| static OrdersType getTombstoneKey() { |
| OrdersType V; |
| V.push_back(~2U); |
| return V; |
| } |
| |
| static unsigned getHashValue(const OrdersType &V) { |
| return static_cast<unsigned>(hash_combine_range(V.begin(), V.end())); |
| } |
| |
| static bool isEqual(const OrdersType &LHS, const OrdersType &RHS) { |
| return LHS == RHS; |
| } |
| }; |
| |
| // Analysis and block reference. |
| Function *F; |
| ScalarEvolution *SE; |
| TargetTransformInfo *TTI; |
| TargetLibraryInfo *TLI; |
| AAResults *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 *; |
| |
| using ContainerTy = BoUpSLP::TreeEntry::VecTreeTy; |
| |
| /// Add the VectorizableTree to the index iterator to be able to return |
| /// TreeEntry pointers. |
| struct ChildIteratorType |
| : public iterator_adaptor_base< |
| ChildIteratorType, SmallVector<BoUpSLP::EdgeInfo, 1>::iterator> { |
| ContainerTy &VectorizableTree; |
| |
| ChildIteratorType(SmallVector<BoUpSLP::EdgeInfo, 1>::iterator W, |
| ContainerTy &VT) |
| : ChildIteratorType::iterator_adaptor_base(W), VectorizableTree(VT) {} |
| |
| NodeRef operator*() { return I->UserTE; } |
| }; |
| |
| static NodeRef getEntryNode(BoUpSLP &R) { |
| return R.VectorizableTree[0].get(); |
| } |
| |
| static ChildIteratorType child_begin(NodeRef N) { |
| return {N->UserTreeIndices.begin(), N->Container}; |
| } |
| |
| static ChildIteratorType child_end(NodeRef N) { |
| return {N->UserTreeIndices.end(), N->Container}; |
| } |
| |
| /// For the node iterator we just need to turn the TreeEntry iterator into a |
| /// TreeEntry* iterator so that it dereferences to NodeRef. |
| class nodes_iterator { |
| using ItTy = ContainerTy::iterator; |
| ItTy It; |
| |
| public: |
| nodes_iterator(const ItTy &It2) : It(It2) {} |
| NodeRef operator*() { return It->get(); } |
| nodes_iterator operator++() { |
| ++It; |
| return *this; |
| } |
| bool operator!=(const nodes_iterator &N2) const { return N2.It != It; } |
| }; |
| |
| static nodes_iterator nodes_begin(BoUpSLP *R) { |
| return nodes_iterator(R->VectorizableTree.begin()); |
| } |
| |
| static nodes_iterator nodes_end(BoUpSLP *R) { |
| return nodes_iterator(R->VectorizableTree.end()); |
| } |
| |
| static unsigned size(BoUpSLP *R) { return R->VectorizableTree.size(); } |
| }; |
| |
| template <> struct DOTGraphTraits<BoUpSLP *> : public DefaultDOTGraphTraits { |
| using TreeEntry = BoUpSLP::TreeEntry; |
| |
| DOTGraphTraits(bool isSimple = false) : DefaultDOTGraphTraits(isSimple) {} |
| |
| std::string getNodeLabel(const TreeEntry *Entry, const BoUpSLP *R) { |
| std::string Str; |
| raw_string_ostream OS(Str); |
| if (isSplat(Entry->Scalars)) |
| OS << "<splat> "; |
| for (auto V : Entry->Scalars) { |
| OS << *V; |
| if (llvm::any_of(R->ExternalUses, [&](const BoUpSLP::ExternalUser &EU) { |
| return EU.Scalar == V; |
| })) |
| OS << " <extract>"; |
| OS << "\n"; |
| } |
| return Str; |
| } |
| |
| static std::string getNodeAttributes(const TreeEntry *Entry, |
| const BoUpSLP *) { |
| if (Entry->State == TreeEntry::NeedToGather) |
| return "color=red"; |
| return ""; |
| } |
| }; |
| |
| } // end namespace llvm |
| |
| BoUpSLP::~BoUpSLP() { |
| for (const auto &Pair : DeletedInstructions) { |
| // Replace operands of ignored instructions with Undefs in case if they were |
| // marked for deletion. |
| if (Pair.getSecond()) { |
| Value *Undef = UndefValue::get(Pair.getFirst()->getType()); |
| Pair.getFirst()->replaceAllUsesWith(Undef); |
| } |
| Pair.getFirst()->dropAllReferences(); |
| } |
| for (const auto &Pair : DeletedInstructions) { |
| assert(Pair.getFirst()->use_empty() && |
| "trying to erase instruction with users."); |
| Pair.getFirst()->eraseFromParent(); |
| } |
| #ifdef EXPENSIVE_CHECKS |
| // If we could guarantee that this call is not extremely slow, we could |
| // remove the ifdef limitation (see PR47712). |
| assert(!verifyFunction(*F, &dbgs())); |
| #endif |
| } |
| |
| void BoUpSLP::eraseInstructions(ArrayRef<Value *> AV) { |
| for (auto *V : AV) { |
| if (auto *I = dyn_cast<Instruction>(V)) |
| eraseInstruction(I, /*ReplaceOpsWithUndef=*/true); |
| }; |
| } |
| |
| /// Reorders the given \p Reuses mask according to the given \p Mask. \p Reuses |
| /// contains original mask for the scalars reused in the node. Procedure |
| /// transform this mask in accordance with the given \p Mask. |
| static void reorderReuses(SmallVectorImpl<int> &Reuses, ArrayRef<int> Mask) { |
| assert(!Mask.empty() && Reuses.size() == Mask.size() && |
| "Expected non-empty mask."); |
| SmallVector<int> Prev(Reuses.begin(), Reuses.end()); |
| Prev.swap(Reuses); |
| for (unsigned I = 0, E = Prev.size(); I < E; ++I) |
| if (Mask[I] != UndefMaskElem) |
| Reuses[Mask[I]] = Prev[I]; |
| } |
| |
| /// Reorders the given \p Order according to the given \p Mask. \p Order - is |
| /// the original order of the scalars. Procedure transforms the provided order |
| /// in accordance with the given \p Mask. If the resulting \p Order is just an |
| /// identity order, \p Order is cleared. |
| static void reorderOrder(SmallVectorImpl<unsigned> &Order, ArrayRef<int> Mask) { |
| assert(!Mask.empty() && "Expected non-empty mask."); |
| SmallVector<int> MaskOrder; |
| if (Order.empty()) { |
| MaskOrder.resize(Mask.size()); |
| std::iota(MaskOrder.begin(), MaskOrder.end(), 0); |
| } else { |
| inversePermutation(Order, MaskOrder); |
| } |
| reorderReuses(MaskOrder, Mask); |
| if (ShuffleVectorInst::isIdentityMask(MaskOrder)) { |
| Order.clear(); |
| return; |
| } |
| Order.assign(Mask.size(), Mask.size()); |
| for (unsigned I = 0, E = Mask.size(); I < E; ++I) |
| if (MaskOrder[I] != UndefMaskElem) |
| Order[MaskOrder[I]] = I; |
| fixupOrderingIndices(Order); |
| } |
| |
| Optional<BoUpSLP::OrdersType> |
| BoUpSLP::findReusedOrderedScalars(const BoUpSLP::TreeEntry &TE) { |
| assert(TE.State == TreeEntry::NeedToGather && "Expected gather node only."); |
| unsigned NumScalars = TE.Scalars.size(); |
| OrdersType CurrentOrder(NumScalars, NumScalars); |
| SmallVector<int> Positions; |
| SmallBitVector UsedPositions(NumScalars); |
| const TreeEntry *STE = nullptr; |
| // Try to find all gathered scalars that are gets vectorized in other |
| // vectorize node. Here we can have only one single tree vector node to |
| // correctly identify order of the gathered scalars. |
| for (unsigned I = 0; I < NumScalars; ++I) { |
| Value *V = TE.Scalars[I]; |
| if (!isa<LoadInst, ExtractElementInst, ExtractValueInst>(V)) |
| continue; |
| if (const auto *LocalSTE = getTreeEntry(V)) { |
| if (!STE) |
| STE = LocalSTE; |
| else if (STE != LocalSTE) |
| // Take the order only from the single vector node. |
| return None; |
| unsigned Lane = |
| std::distance(STE->Scalars.begin(), find(STE->Scalars, V)); |
| if (Lane >= NumScalars) |
| return None; |
| if (CurrentOrder[Lane] != NumScalars) { |
| if (Lane != I) |
| continue; |
| UsedPositions.reset(CurrentOrder[Lane]); |
| } |
| // The partial identity (where only some elements of the gather node are |
| // in the identity order) is good. |
| CurrentOrder[Lane] = I; |
| UsedPositions.set(I); |
| } |
| } |
| // Need to keep the order if we have a vector entry and at least 2 scalars or |
| // the vectorized entry has just 2 scalars. |
| if (STE && (UsedPositions.count() > 1 || STE->Scalars.size() == 2)) { |
| auto &&IsIdentityOrder = [NumScalars](ArrayRef<unsigned> CurrentOrder) { |
| for (unsigned I = 0; I < NumScalars; ++I) |
| if (CurrentOrder[I] != I && CurrentOrder[I] != NumScalars) |
| return false; |
| return true; |
| }; |
| if (IsIdentityOrder(CurrentOrder)) { |
| CurrentOrder.clear(); |
| return CurrentOrder; |
| } |
| auto *It = CurrentOrder.begin(); |
| for (unsigned I = 0; I < NumScalars;) { |
| if (UsedPositions.test(I)) { |
| ++I; |
| continue; |
| } |
| if (*It == NumScalars) { |
| *It = I; |
| ++I; |
| } |
| ++It; |
| } |
| return CurrentOrder; |
| } |
| return None; |
| } |
| |
| void BoUpSLP::reorderTopToBottom() { |
| // Maps VF to the graph nodes. |
| DenseMap<unsigned, SmallPtrSet<TreeEntry *, 4>> VFToOrderedEntries; |
| // ExtractElement gather nodes which can be vectorized and need to handle |
| // their ordering. |
| DenseMap<const TreeEntry *, OrdersType> GathersToOrders; |
| // Find all reorderable nodes with the given VF. |
| // Currently the are vectorized loads,extracts + some gathering of extracts. |
| for_each(VectorizableTree, [this, &VFToOrderedEntries, &GathersToOrders]( |
| const std::unique_ptr<TreeEntry> &TE) { |
| // No need to reorder if need to shuffle reuses, still need to shuffle the |
| // node. |
| if (!TE->ReuseShuffleIndices.empty()) |
| return; |
| if (TE->State == TreeEntry::Vectorize && |
| isa<LoadInst, ExtractElementInst, ExtractValueInst, StoreInst, |
| InsertElementInst>(TE->getMainOp()) && |
| !TE->isAltShuffle()) { |
| VFToOrderedEntries[TE->Scalars.size()].insert(TE.get()); |
| return; |
| } |
| if (TE->State == TreeEntry::NeedToGather) { |
| if (TE->getOpcode() == Instruction::ExtractElement && |
| !TE->isAltShuffle() && |
| isa<FixedVectorType>(cast<ExtractElementInst>(TE->getMainOp()) |
| ->getVectorOperandType()) && |
| allSameType(TE->Scalars) && allSameBlock(TE->Scalars)) { |
| // Check that gather of extractelements can be represented as |
| // just a shuffle of a single vector. |
| OrdersType CurrentOrder; |
| bool Reuse = |
| canReuseExtract(TE->Scalars, TE->getMainOp(), CurrentOrder); |
| if (Reuse || !CurrentOrder.empty()) { |
| VFToOrderedEntries[TE->Scalars.size()].insert(TE.get()); |
| GathersToOrders.try_emplace(TE.get(), CurrentOrder); |
| return; |
| } |
| } |
| if (Optional<OrdersType> CurrentOrder = |
| findReusedOrderedScalars(*TE.get())) { |
| VFToOrderedEntries[TE->Scalars.size()].insert(TE.get()); |
| GathersToOrders.try_emplace(TE.get(), *CurrentOrder); |
| } |
| } |
| }); |
| |
| // Reorder the graph nodes according to their vectorization factor. |
| for (unsigned VF = VectorizableTree.front()->Scalars.size(); VF > 1; |
| VF /= 2) { |
| auto It = VFToOrderedEntries.find(VF); |
| if (It == VFToOrderedEntries.end()) |
| continue; |
| // Try to find the most profitable order. We just are looking for the most |
| // used order and reorder scalar elements in the nodes according to this |
| // mostly used order. |
| const SmallPtrSetImpl<TreeEntry *> &OrderedEntries = It->getSecond(); |
| // All operands are reordered and used only in this node - propagate the |
| // most used order to the user node. |
| MapVector<OrdersType, unsigned, |
| DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo>> |
| OrdersUses; |
| SmallPtrSet<const TreeEntry *, 4> VisitedOps; |
| for (const TreeEntry *OpTE : OrderedEntries) { |
| // No need to reorder this nodes, still need to extend and to use shuffle, |
| // just need to merge reordering shuffle and the reuse shuffle. |
| if (!OpTE->ReuseShuffleIndices.empty()) |
| continue; |
| // Count number of orders uses. |
| const auto &Order = [OpTE, &GathersToOrders]() -> const OrdersType & { |
| if (OpTE->State == TreeEntry::NeedToGather) |
| return GathersToOrders.find(OpTE)->second; |
| return OpTE->ReorderIndices; |
| }(); |
| // Stores actually store the mask, not the order, need to invert. |
| if (OpTE->State == TreeEntry::Vectorize && !OpTE->isAltShuffle() && |
| OpTE->getOpcode() == Instruction::Store && !Order.empty()) { |
| SmallVector<int> Mask; |
| inversePermutation(Order, Mask); |
| unsigned E = Order.size(); |
| OrdersType CurrentOrder(E, E); |
| transform(Mask, CurrentOrder.begin(), [E](int Idx) { |
| return Idx == UndefMaskElem ? E : static_cast<unsigned>(Idx); |
| }); |
| fixupOrderingIndices(CurrentOrder); |
| ++OrdersUses.insert(std::make_pair(CurrentOrder, 0)).first->second; |
| } else { |
| ++OrdersUses.insert(std::make_pair(Order, 0)).first->second; |
| } |
| } |
| // Set order of the user node. |
| if (OrdersUses.empty()) |
| continue; |
| // Choose the most used order. |
| ArrayRef<unsigned> BestOrder = OrdersUses.front().first; |
| unsigned Cnt = OrdersUses.front().second; |
| for (const auto &Pair : drop_begin(OrdersUses)) { |
| if (Cnt < Pair.second || (Cnt == Pair.second && Pair.first.empty())) { |
| BestOrder = Pair.first; |
| Cnt = Pair.second; |
| } |
| } |
| // Set order of the user node. |
| if (BestOrder.empty()) |
| continue; |
| SmallVector<int> Mask; |
| inversePermutation(BestOrder, Mask); |
| SmallVector<int> MaskOrder(BestOrder.size(), UndefMaskElem); |
| unsigned E = BestOrder.size(); |
| transform(BestOrder, MaskOrder.begin(), [E](unsigned I) { |
| return I < E ? static_cast<int>(I) : UndefMaskElem; |
| }); |
| // Do an actual reordering, if profitable. |
| for (std::unique_ptr<TreeEntry> &TE : VectorizableTree) { |
| // Just do the reordering for the nodes with the given VF. |
| if (TE->Scalars.size() != VF) { |
| if (TE->ReuseShuffleIndices.size() == VF) { |
| // Need to reorder the reuses masks of the operands with smaller VF to |
| // be able to find the match between the graph nodes and scalar |
| // operands of the given node during vectorization/cost estimation. |
| assert(all_of(TE->UserTreeIndices, |
| [VF, &TE](const EdgeInfo &EI) { |
| return EI.UserTE->Scalars.size() == VF || |
| EI.UserTE->Scalars.size() == |
| TE->Scalars.size(); |
| }) && |
| "All users must be of VF size."); |
| // Update ordering of the operands with the smaller VF than the given |
| // one. |
| reorderReuses(TE->ReuseShuffleIndices, Mask); |
| } |
| continue; |
| } |
| if (TE->State == TreeEntry::Vectorize && |
| isa<ExtractElementInst, ExtractValueInst, LoadInst, StoreInst, |
| InsertElementInst>(TE->getMainOp()) && |
| !TE->isAltShuffle()) { |
| // Build correct orders for extract{element,value}, loads and |
| // stores. |
| reorderOrder(TE->ReorderIndices, Mask); |
| if (isa<InsertElementInst, StoreInst>(TE->getMainOp())) |
| TE->reorderOperands(Mask); |
| } else { |
| // Reorder the node and its operands. |
| TE->reorderOperands(Mask); |
| assert(TE->ReorderIndices.empty() && |
| "Expected empty reorder sequence."); |
| reorderScalars(TE->Scalars, Mask); |
| } |
| if (!TE->ReuseShuffleIndices.empty()) { |
| // Apply reversed order to keep the original ordering of the reused |
| // elements to avoid extra reorder indices shuffling. |
| OrdersType CurrentOrder; |
| reorderOrder(CurrentOrder, MaskOrder); |
| SmallVector<int> NewReuses; |
| inversePermutation(CurrentOrder, NewReuses); |
| addMask(NewReuses, TE->ReuseShuffleIndices); |
| TE->ReuseShuffleIndices.swap(NewReuses); |
| } |
| } |
| } |
| } |
| |
| void BoUpSLP::reorderBottomToTop(bool IgnoreReorder) { |
| SetVector<TreeEntry *> OrderedEntries; |
| DenseMap<const TreeEntry *, OrdersType> GathersToOrders; |
| // Find all reorderable leaf nodes with the given VF. |
| // Currently the are vectorized loads,extracts without alternate operands + |
| // some gathering of extracts. |
| SmallVector<TreeEntry *> NonVectorized; |
| for_each(VectorizableTree, [this, &OrderedEntries, &GathersToOrders, |
| &NonVectorized]( |
| const std::unique_ptr<TreeEntry> &TE) { |
| if (TE->State != TreeEntry::Vectorize) |
| NonVectorized.push_back(TE.get()); |
| // No need to reorder if need to shuffle reuses, still need to shuffle the |
| // node. |
| if (!TE->ReuseShuffleIndices.empty()) |
| return; |
| if (TE->State == TreeEntry::Vectorize && |
| isa<LoadInst, ExtractElementInst, ExtractValueInst>(TE->getMainOp()) && |
| !TE->isAltShuffle()) { |
| OrderedEntries.insert(TE.get()); |
| return; |
| } |
| if (TE->State == TreeEntry::NeedToGather) { |
| if (TE->getOpcode() == Instruction::ExtractElement && |
| !TE->isAltShuffle() && |
| isa<FixedVectorType>(cast<ExtractElementInst>(TE->getMainOp()) |
| ->getVectorOperandType()) && |
| allSameType(TE->Scalars) && allSameBlock(TE->Scalars)) { |
| // Check that gather of extractelements can be represented as |
| // just a shuffle of a single vector with a single user only. |
| OrdersType CurrentOrder; |
| bool Reuse = |
| canReuseExtract(TE->Scalars, TE->getMainOp(), CurrentOrder); |
| if ((Reuse || !CurrentOrder.empty()) && |
| !any_of(VectorizableTree, |
| [&TE](const std::unique_ptr<TreeEntry> &Entry) { |
| return Entry->State == TreeEntry::NeedToGather && |
| Entry.get() != TE.get() && |
| Entry->isSame(TE->Scalars); |
| })) { |
| OrderedEntries.insert(TE.get()); |
| GathersToOrders.try_emplace(TE.get(), CurrentOrder); |
| return; |
| } |
| } |
| if (Optional<OrdersType> CurrentOrder = |
| findReusedOrderedScalars(*TE.get())) { |
| OrderedEntries.insert(TE.get()); |
| GathersToOrders.try_emplace(TE.get(), *CurrentOrder); |
| } |
| } |
| }); |
| |
| // Checks if the operands of the users are reordarable and have only single |
| // use. |
| auto &&CheckOperands = |
| [this, &NonVectorized](const auto &Data, |
| SmallVectorImpl<TreeEntry *> &GatherOps) { |
| for (unsigned I = 0, E = Data.first->getNumOperands(); I < E; ++I) { |
| if (any_of(Data.second, |
| [I](const std::pair<unsigned, TreeEntry *> &OpData) { |
| return OpData.first == I && |
| OpData.second->State == TreeEntry::Vectorize; |
| })) |
| continue; |
| ArrayRef<Value *> VL = Data.first->getOperand(I); |
| const TreeEntry *TE = nullptr; |
| const auto *It = find_if(VL, [this, &TE](Value *V) { |
| TE = getTreeEntry(V); |
| return TE; |
| }); |
| if (It != VL.end() && TE->isSame(VL)) |
| return false; |
| TreeEntry *Gather = nullptr; |
| if (count_if(NonVectorized, [VL, &Gather](TreeEntry *TE) { |
| assert(TE->State != TreeEntry::Vectorize && |
| "Only non-vectorized nodes are expected."); |
| if (TE->isSame(VL)) { |
| Gather = TE; |
| return true; |
| } |
| return false; |
| }) > 1) |
| return false; |
| if (Gather) |
| GatherOps.push_back(Gather); |
| } |
| return true; |
| }; |
| // 1. Propagate order to the graph nodes, which use only reordered nodes. |
| // I.e., if the node has operands, that are reordered, try to make at least |
| // one operand order in the natural order and reorder others + reorder the |
| // user node itself. |
| SmallPtrSet<const TreeEntry *, 4> Visited; |
| while (!OrderedEntries.empty()) { |
| // 1. Filter out only reordered nodes. |
| // 2. If the entry has multiple uses - skip it and jump to the next node. |
| MapVector<TreeEntry *, SmallVector<std::pair<unsigned, TreeEntry *>>> Users; |
| SmallVector<TreeEntry *> Filtered; |
| for (TreeEntry *TE : OrderedEntries) { |
| if (!(TE->State == TreeEntry::Vectorize || |
| (TE->State == TreeEntry::NeedToGather && |
| GathersToOrders.count(TE))) || |
| TE->UserTreeIndices.empty() || !TE->ReuseShuffleIndices.empty() || |
| !all_of(drop_begin(TE->UserTreeIndices), |
| [TE](const EdgeInfo &EI) { |
| return EI.UserTE == TE->UserTreeIndices.front().UserTE; |
| }) || |
| !Visited.insert(TE).second) { |
| Filtered.push_back(TE); |
| continue; |
| } |
| // Build a map between user nodes and their operands order to speedup |
| // search. The graph currently does not provide this dependency directly. |
| for (EdgeInfo &EI : TE->UserTreeIndices) { |
| TreeEntry *UserTE = EI.UserTE; |
| auto It = Users.find(UserTE); |
| if (It == Users.end()) |
| It = Users.insert({UserTE, {}}).first; |
| It->second.emplace_back(EI.EdgeIdx, TE); |
| } |
| } |
| // Erase filtered entries. |
| for_each(Filtered, |
| [&OrderedEntries](TreeEntry *TE) { OrderedEntries.remove(TE); }); |
| for (const auto &Data : Users) { |
| // Check that operands are used only in the User node. |
| SmallVector<TreeEntry *> GatherOps; |
| if (!CheckOperands(Data, GatherOps)) { |
| for_each(Data.second, |
| [&OrderedEntries](const std::pair<unsigned, TreeEntry *> &Op) { |
| OrderedEntries.remove(Op.second); |
| }); |
| continue; |
| } |
| // All operands are reordered and used only in this node - propagate the |
| // most used order to the user node. |
| MapVector<OrdersType, unsigned, |
| DenseMap<OrdersType, unsigned, OrdersTypeDenseMapInfo>> |
| OrdersUses; |
| SmallPtrSet<const TreeEntry *, 4> VisitedOps; |
| for (const auto &Op : Data.second) { |
| TreeEntry *OpTE = Op.second; |
| if (!OpTE->ReuseShuffleIndices.empty() || |
| (IgnoreReorder && OpTE == VectorizableTree.front().get())) |
| continue; |
| const auto &Order = [OpTE, &GathersToOrders]() -> const OrdersType & { |
| if (OpTE->State == TreeEntry::NeedToGather) |
| return GathersToOrders.find(OpTE)->second; |
| return OpTE->ReorderIndices; |
| }(); |
| // Stores actually store the mask, not the order, need to invert. |
| if (OpTE->State == TreeEntry::Vectorize && !OpTE->isAltShuffle() && |
| OpTE->getOpcode() == Instruction::Store && !Order.empty()) { |
| SmallVector<int> Mask; |
| inversePermutation(Order, Mask); |
| unsigned E = Order.size(); |
| OrdersType CurrentOrder(E, E); |
| transform(Mask, CurrentOrder.begin(), [E](int Idx) { |
| return Idx == UndefMaskElem ? E : static_cast<unsigned>(Idx); |
| }); |
| fixupOrderingIndices(CurrentOrder); |
| ++OrdersUses.insert(std::make_pair(CurrentOrder, 0)).first->second; |
| } else { |
| ++OrdersUses.insert(std::make_pair(Order, 0)).first->second; |
| } |
| if (VisitedOps.insert(OpTE).second) |
| OrdersUses.insert(std::make_pair(OrdersType(), 0)).first->second += |
| OpTE->UserTreeIndices.size(); |
| assert(OrdersUses[{}] > 0 && "Counter cannot be less than 0."); |
| --OrdersUses[{}]; |
| } |
| // If no orders - skip current nodes and jump to the next one, if any. |
| if (OrdersUses.empty()) { |
| for_each(Data.second, |
| [&OrderedEntries](const std::pair<unsigned, TreeEntry *> &Op) { |
| OrderedEntries.remove(Op.second); |
| }); |
| continue; |
| } |
| // Choose the best order. |
| ArrayRef<unsigned> BestOrder = OrdersUses.front().first; |
| unsigned Cnt = OrdersUses.front().second; |
| for (const auto &Pair : drop_begin(OrdersUses)) { |
| if (Cnt < Pair.second || (Cnt == Pair.second && Pair.first.empty())) { |
| BestOrder = Pair.first; |
| Cnt = Pair.second; |
| } |
| } |
| // Set order of the user node (reordering of operands and user nodes). |
| if (BestOrder.empty()) { |
| for_each(Data.second, |
| [&OrderedEntries](const std::pair<unsigned, TreeEntry *> &Op) { |
| OrderedEntries.remove(Op.second); |
| }); |
| continue; |
| } |
| // Erase operands from OrderedEntries list and adjust their orders. |
| VisitedOps.clear(); |
| SmallVector<int> Mask; |
| inversePermutation(BestOrder, Mask); |
| SmallVector<int> MaskOrder(BestOrder.size(), UndefMaskElem); |
| unsigned E = BestOrder.size(); |
| transform(BestOrder, MaskOrder.begin(), [E](unsigned I) { |
| return I < E ? static_cast<int>(I) : UndefMaskElem; |
| }); |
| for (const std::pair<unsigned, TreeEntry *> &Op : Data.second) { |
| TreeEntry *TE = Op.second; |
| OrderedEntries.remove(TE); |
| if (!VisitedOps.insert(TE).second) |
| continue; |
| if (!TE->ReuseShuffleIndices.empty() && TE->ReorderIndices.empty()) { |
| // Just reorder reuses indices. |
| reorderReuses(TE->ReuseShuffleIndices, Mask); |
| continue; |
| } |
| // Gathers are processed separately. |
| if (TE->State != TreeEntry::Vectorize) |
| continue; |
| assert((BestOrder.size() == TE->ReorderIndices.size() || |
| TE->ReorderIndices.empty()) && |
| "Non-matching sizes of user/operand entries."); |
| reorderOrder(TE->ReorderIndices, Mask); |
| } |
| // For gathers just need to reorder its scalars. |
| for (TreeEntry *Gather : GatherOps) { |
| assert(Gather->ReorderIndices.empty() && |
| "Unexpected reordering of gathers."); |
| if (!Gather->ReuseShuffleIndices.empty()) { |
| // Just reorder reuses indices. |
| reorderReuses(Gather->ReuseShuffleIndices, Mask); |
| continue; |
| } |
| reorderScalars(Gather->Scalars, Mask); |
| OrderedEntries.remove(Gather); |
| } |
| // Reorder operands of the user node and set the ordering for the user |
| // node itself. |
| if (Data.first->State != TreeEntry::Vectorize || |
| !isa<ExtractElementInst, ExtractValueInst, LoadInst>( |
| Data.first->getMainOp()) || |
| Data.first->isAltShuffle()) |
| Data.first->reorderOperands(Mask); |
| if (!isa<InsertElementInst, StoreInst>(Data.first->getMainOp()) || |
| Data.first->isAltShuffle()) { |
| reorderScalars(Data.first->Scalars, Mask); |
| reorderOrder(Data.first->ReorderIndices, MaskOrder); |
| if (Data.first->ReuseShuffleIndices.empty() && |
| !Data.first->ReorderIndices.empty() && |
| !Data.first->isAltShuffle()) { |
| // Insert user node to the list to try to sink reordering deeper in |
| // the graph. |
| OrderedEntries.insert(Data.first); |
| } |
| } else { |
| reorderOrder(Data.first->ReorderIndices, Mask); |
| } |
| } |
| } |
| // If the reordering is unnecessary, just remove the reorder. |
| if (IgnoreReorder && !VectorizableTree.front()->ReorderIndices.empty() && |
| VectorizableTree.front()->ReuseShuffleIndices.empty()) |
| VectorizableTree.front()->ReorderIndices.clear(); |
| } |
| |
| void BoUpSLP::buildExternalUses( |
| const ExtraValueToDebugLocsMap &ExternallyUsedValues) { |
| // Collect the values that we need to extract from the tree. |
| for (auto &TEPtr : VectorizableTree) { |
| TreeEntry *Entry = TEPtr.get(); |
| |
| // No need to handle users of gathered values. |
| if (Entry->State == TreeEntry::NeedToGather) |
| continue; |
| |
| // For each lane: |
| for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { |
| Value *Scalar = Entry->Scalars[Lane]; |
| int FoundLane = Entry->findLaneForValue(Scalar); |
| |
| // Check if the scalar is externally used as an extra arg. |
| auto ExtI = ExternallyUsedValues.find(Scalar); |
| if (ExtI != ExternallyUsedValues.end()) { |
| LLVM_DEBUG(dbgs() << "SLP: Need to extract: Extra arg from lane " |
| << Lane << " from " << *Scalar << ".\n"); |
| ExternalUses.emplace_back(Scalar, nullptr, FoundLane); |
| } |
| for (User *U : Scalar->users()) { |
| LLVM_DEBUG(dbgs() << "SLP: Checking user:" << *U << ".\n"); |
| |
| Instruction *UserInst = dyn_cast<Instruction>(U); |
| if (!UserInst) |
| continue; |
| |
| if (isDeleted(UserInst)) |
| continue; |
| |
| // Skip in-tree scalars that become vectors |
| if (TreeEntry *UseEntry = getTreeEntry(U)) { |
| Value *UseScalar = UseEntry->Scalars[0]; |
| // Some in-tree scalars will remain as scalar in vectorized |
| // instructions. If that is the case, the one in Lane 0 will |
| // be used. |
| if (UseScalar != U || |
| UseEntry->State == TreeEntry::ScatterVectorize || |
| !InTreeUserNeedToExtract(Scalar, UserInst, TLI)) { |
| LLVM_DEBUG(dbgs() << "SLP: \tInternal user will be removed:" << *U |
| << ".\n"); |
| assert(UseEntry->State != TreeEntry::NeedToGather && "Bad state"); |
| continue; |
| } |
| } |
| |
| // Ignore users in the user ignore list. |
| if (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(ArrayRef<Value *> Roots, |
| ArrayRef<Value *> UserIgnoreLst) { |
| deleteTree(); |
| UserIgnoreList = UserIgnoreLst; |
| if (!allSameType(Roots)) |
| return; |
| buildTree_rec(Roots, 0, EdgeInfo()); |
| } |
| |
| namespace { |
| /// Tracks the state we can represent the loads in the given sequence. |
| enum class LoadsState { Gather, Vectorize, ScatterVectorize }; |
| } // anonymous namespace |
| |
| /// Checks if the given array of loads can be represented as a vectorized, |
| /// scatter or just simple gather. |
| static LoadsState canVectorizeLoads(ArrayRef<Value *> VL, const Value *VL0, |
| const TargetTransformInfo &TTI, |
| const DataLayout &DL, ScalarEvolution &SE, |
| SmallVectorImpl<unsigned> &Order, |
| SmallVectorImpl<Value *> &PointerOps) { |
| // Check that a vectorized load would load the same memory as a scalar |
| // load. For example, we don't want to vectorize loads that are smaller |
| // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM |
| // treats loading/storing it as an i8 struct. If we vectorize loads/stores |
| // from such a struct, we read/write packed bits disagreeing with the |
| // unvectorized version. |
| Type *ScalarTy = VL0->getType(); |
| |
| if (DL.getTypeSizeInBits(ScalarTy) != DL.getTypeAllocSizeInBits(ScalarTy)) |
| return LoadsState::Gather; |
| |
| // Make sure all loads in the bundle are simple - we can't vectorize |
| // atomic or volatile loads. |
| PointerOps.clear(); |
| PointerOps.resize(VL.size()); |
| auto *POIter = PointerOps.begin(); |
| for (Value *V : VL) { |
| auto *L = cast<LoadInst>(V); |
| if (!L->isSimple()) |
| return LoadsState::Gather; |
| *POIter = L->getPointerOperand(); |
| ++POIter; |
| } |
| |
| Order.clear(); |
| // Check the order of pointer operands. |
| if (llvm::sortPtrAccesses(PointerOps, ScalarTy, DL, SE, Order)) { |
| Value *Ptr0; |
| Value *PtrN; |
| if (Order.empty()) { |
| Ptr0 = PointerOps.front(); |
| PtrN = PointerOps.back(); |
| } else { |
| Ptr0 = PointerOps[Order.front()]; |
| PtrN = PointerOps[Order.back()]; |
| } |
| Optional<int> Diff = |
| getPointersDiff(ScalarTy, Ptr0, ScalarTy, PtrN, DL, SE); |
| // Check that the sorted loads are consecutive. |
| if (static_cast<unsigned>(*Diff) == VL.size() - 1) |
| return LoadsState::Vectorize; |
| Align CommonAlignment = cast<LoadInst>(VL0)->getAlign(); |
| for (Value *V : VL) |
| CommonAlignment = |
| commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); |
| if (TTI.isLegalMaskedGather(FixedVectorType::get(ScalarTy, VL.size()), |
| CommonAlignment)) |
| return LoadsState::ScatterVectorize; |
| } |
| |
| return LoadsState::Gather; |
| } |
| |
| void BoUpSLP::buildTree_rec(ArrayRef<Value *> VL, unsigned Depth, |
| const EdgeInfo &UserTreeIdx) { |
| assert((allConstant(VL) || allSameType(VL)) && "Invalid types!"); |
| |
| SmallVector<int> ReuseShuffleIndicies; |
| SmallVector<Value *> UniqueValues; |
| auto &&TryToFindDuplicates = [&VL, &ReuseShuffleIndicies, &UniqueValues, |
| &UserTreeIdx, |
| this](const InstructionsState &S) { |
| // Check that every instruction appears once in this bundle. |
| DenseMap<Value *, unsigned> UniquePositions; |
| for (Value *V : VL) { |
| auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); |
| ReuseShuffleIndicies.emplace_back(isa<UndefValue>(V) ? -1 |
| : Res.first->second); |
| if (Res.second) |
| UniqueValues.emplace_back(V); |
| } |
| size_t NumUniqueScalarValues = UniqueValues.size(); |
| if (NumUniqueScalarValues == VL.size()) { |
| ReuseShuffleIndicies.clear(); |
| } else { |
| LLVM_DEBUG(dbgs() << "SLP: Shuffle for reused scalars.\n"); |
| if (NumUniqueScalarValues <= 1 || |
| !llvm::isPowerOf2_32(NumUniqueScalarValues)) { |
| LLVM_DEBUG(dbgs() << "SLP: Scalar used twice in bundle.\n"); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); |
| return false; |
| } |
| VL = UniqueValues; |
| } |
| return true; |
| }; |
| |
| InstructionsState S = getSameOpcode(VL); |
| if (Depth == RecursionMaxDepth) { |
| LLVM_DEBUG(dbgs() << "SLP: Gathering due to max recursion depth.\n"); |
| if (TryToFindDuplicates(S)) |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| return; |
| } |
| |
| // Don't handle scalable vectors |
| if (S.getOpcode() == Instruction::ExtractElement && |
| isa<ScalableVectorType>( |
| cast<ExtractElementInst>(S.OpValue)->getVectorOperandType())) { |
| LLVM_DEBUG(dbgs() << "SLP: Gathering due to scalable vector type.\n"); |
| if (TryToFindDuplicates(S)) |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| return; |
| } |
| |
| // Don't handle vectors. |
| if (S.OpValue->getType()->isVectorTy() && |
| !isa<InsertElementInst>(S.OpValue)) { |
| LLVM_DEBUG(dbgs() << "SLP: Gathering due to vector type.\n"); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); |
| return; |
| } |
| |
| if (StoreInst *SI = dyn_cast<StoreInst>(S.OpValue)) |
| if (SI->getValueOperand()->getType()->isVectorTy()) { |
| LLVM_DEBUG(dbgs() << "SLP: Gathering due to store vector type.\n"); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); |
| return; |
| } |
| |
| // If all of the operands are identical or constant we have a simple solution. |
| // If we deal with insert/extract instructions, they all must have constant |
| // indices, otherwise we should gather them, not try to vectorize. |
| if (allConstant(VL) || isSplat(VL) || !allSameBlock(VL) || !S.getOpcode() || |
| (isa<InsertElementInst, ExtractValueInst, ExtractElementInst>(S.MainOp) && |
| !all_of(VL, isVectorLikeInstWithConstOps))) { |
| LLVM_DEBUG(dbgs() << "SLP: Gathering due to C,S,B,O. \n"); |
| if (TryToFindDuplicates(S)) |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| return; |
| } |
| |
| // We now know that this is a vector of instructions of the same type from |
| // the same block. |
| |
| // Don't vectorize ephemeral values. |
| for (Value *V : VL) { |
| if (EphValues.count(V)) { |
| LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V |
| << ") is ephemeral.\n"); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); |
| return; |
| } |
| } |
| |
| // Check if this is a duplicate of another entry. |
| if (TreeEntry *E = getTreeEntry(S.OpValue)) { |
| LLVM_DEBUG(dbgs() << "SLP: \tChecking bundle: " << *S.OpValue << ".\n"); |
| if (!E->isSame(VL)) { |
| LLVM_DEBUG(dbgs() << "SLP: Gathering due to partial overlap.\n"); |
| if (TryToFindDuplicates(S)) |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| return; |
| } |
| // Record the reuse of the tree node. FIXME, currently this is only used to |
| // properly draw the graph rather than for the actual vectorization. |
| E->UserTreeIndices.push_back(UserTreeIdx); |
| LLVM_DEBUG(dbgs() << "SLP: Perfect diamond merge at " << *S.OpValue |
| << ".\n"); |
| return; |
| } |
| |
| // Check that none of the instructions in the bundle are already in the tree. |
| for (Value *V : VL) { |
| auto *I = dyn_cast<Instruction>(V); |
| if (!I) |
| continue; |
| if (getTreeEntry(I)) { |
| LLVM_DEBUG(dbgs() << "SLP: The instruction (" << *V |
| << ") is already in tree.\n"); |
| if (TryToFindDuplicates(S)) |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| 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 (Value *V : VL) { |
| if (MustGather.count(V) || is_contained(UserIgnoreList, V)) { |
| LLVM_DEBUG(dbgs() << "SLP: Gathering due to gathered scalar.\n"); |
| if (TryToFindDuplicates(S)) |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| 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, None /*not vectorized*/, S, UserTreeIdx); |
| return; |
| } |
| |
| // Check that every instruction appears once in this bundle. |
| if (!TryToFindDuplicates(S)) |
| return; |
| |
| auto &BSRef = BlocksSchedules[BB]; |
| if (!BSRef) |
| BSRef = std::make_unique<BlockScheduling>(BB); |
| |
| BlockScheduling &BS = *BSRef.get(); |
| |
| Optional<ScheduleData *> Bundle = BS.tryScheduleBundle(VL, this, S); |
| if (!Bundle) { |
| LLVM_DEBUG(dbgs() << "SLP: We are not able to schedule this bundle!\n"); |
| assert((!BS.getScheduleData(VL0) || |
| !BS.getScheduleData(VL0)->isPartOfBundle()) && |
| "tryScheduleBundle should cancelScheduling on failure"); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| return; |
| } |
| LLVM_DEBUG(dbgs() << "SLP: We are able to schedule this bundle.\n"); |
| |
| unsigned ShuffleOrOp = S.isAltShuffle() ? |
| (unsigned) Instruction::ShuffleVector : S.getOpcode(); |
| switch (ShuffleOrOp) { |
| case Instruction::PHI: { |
| auto *PH = cast<PHINode>(VL0); |
| |
| // Check for terminator values (e.g. invoke). |
| for (Value *V : VL) |
| for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { |
| Instruction *Term = dyn_cast<Instruction>( |
| cast<PHINode>(V)->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, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| return; |
| } |
| } |
| |
| TreeEntry *TE = |
| newTreeEntry(VL, Bundle, S, UserTreeIdx, ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of PHINodes.\n"); |
| |
| // Keeps the reordered operands to avoid code duplication. |
| SmallVector<ValueList, 2> OperandsVec; |
| for (unsigned I = 0, E = PH->getNumIncomingValues(); I < E; ++I) { |
| if (!DT->isReachableFromEntry(PH->getIncomingBlock(I))) { |
| ValueList Operands(VL.size(), PoisonValue::get(PH->getType())); |
| TE->setOperand(I, Operands); |
| OperandsVec.push_back(Operands); |
| continue; |
| } |
| ValueList Operands; |
| // Prepare the operand vector. |
| for (Value *V : VL) |
| Operands.push_back(cast<PHINode>(V)->getIncomingValueForBlock( |
| PH->getIncomingBlock(I))); |
| TE->setOperand(I, Operands); |
| OperandsVec.push_back(Operands); |
| } |
| for (unsigned OpIdx = 0, OpE = OperandsVec.size(); OpIdx != OpE; ++OpIdx) |
| buildTree_rec(OperandsVec[OpIdx], Depth + 1, {TE, OpIdx}); |
| return; |
| } |
| case Instruction::ExtractValue: |
| case Instruction::ExtractElement: { |
| OrdersType CurrentOrder; |
| bool Reuse = canReuseExtract(VL, VL0, CurrentOrder); |
| if (Reuse) { |
| LLVM_DEBUG(dbgs() << "SLP: Reusing or shuffling extract sequence.\n"); |
| newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| // This is a special case, as it does not gather, but at the same time |
| // we are not extending buildTree_rec() towards the operands. |
| ValueList Op0; |
| Op0.assign(VL.size(), VL0->getOperand(0)); |
| VectorizableTree.back()->setOperand(0, Op0); |
| return; |
| } |
| if (!CurrentOrder.empty()) { |
| LLVM_DEBUG({ |
| dbgs() << "SLP: Reusing or shuffling of reordered extract sequence " |
| "with order"; |
| for (unsigned Idx : CurrentOrder) |
| dbgs() << " " << Idx; |
| dbgs() << "\n"; |
| }); |
| fixupOrderingIndices(CurrentOrder); |
| // Insert new order with initial value 0, if it does not exist, |
| // otherwise return the iterator to the existing one. |
| newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies, CurrentOrder); |
| // This is a special case, as it does not gather, but at the same time |
| // we are not extending buildTree_rec() towards the operands. |
| ValueList Op0; |
| Op0.assign(VL.size(), VL0->getOperand(0)); |
| VectorizableTree.back()->setOperand(0, Op0); |
| return; |
| } |
| LLVM_DEBUG(dbgs() << "SLP: Gather extract sequence.\n"); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| BS.cancelScheduling(VL, VL0); |
| return; |
| } |
| case Instruction::InsertElement: { |
| assert(ReuseShuffleIndicies.empty() && "All inserts should be unique"); |
| |
| // Check that we have a buildvector and not a shuffle of 2 or more |
| // different vectors. |
| ValueSet SourceVectors; |
| int MinIdx = std::numeric_limits<int>::max(); |
| for (Value *V : VL) { |
| SourceVectors.insert(cast<Instruction>(V)->getOperand(0)); |
| Optional<int> Idx = *getInsertIndex(V, 0); |
| if (!Idx || *Idx == UndefMaskElem) |
| continue; |
| MinIdx = std::min(MinIdx, *Idx); |
| } |
| |
| if (count_if(VL, [&SourceVectors](Value *V) { |
| return !SourceVectors.contains(V); |
| }) >= 2) { |
| // Found 2nd source vector - cancel. |
| LLVM_DEBUG(dbgs() << "SLP: Gather of insertelement vectors with " |
| "different source vectors.\n"); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx); |
| BS.cancelScheduling(VL, VL0); |
| return; |
| } |
| |
| auto OrdCompare = [](const std::pair<int, int> &P1, |
| const std::pair<int, int> &P2) { |
| return P1.first > P2.first; |
| }; |
| PriorityQueue<std::pair<int, int>, SmallVector<std::pair<int, int>>, |
| decltype(OrdCompare)> |
| Indices(OrdCompare); |
| for (int I = 0, E = VL.size(); I < E; ++I) { |
| Optional<int> Idx = *getInsertIndex(VL[I], 0); |
| if (!Idx || *Idx == UndefMaskElem) |
| continue; |
| Indices.emplace(*Idx, I); |
| } |
| OrdersType CurrentOrder(VL.size(), VL.size()); |
| bool IsIdentity = true; |
| for (int I = 0, E = VL.size(); I < E; ++I) { |
| CurrentOrder[Indices.top().second] = I; |
| IsIdentity &= Indices.top().second == I; |
| Indices.pop(); |
| } |
| if (IsIdentity) |
| CurrentOrder.clear(); |
| TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| None, CurrentOrder); |
| LLVM_DEBUG(dbgs() << "SLP: added inserts bundle.\n"); |
| |
| constexpr int NumOps = 2; |
| ValueList VectorOperands[NumOps]; |
| for (int I = 0; I < NumOps; ++I) { |
| for (Value *V : VL) |
| VectorOperands[I].push_back(cast<Instruction>(V)->getOperand(I)); |
| |
| TE->setOperand(I, VectorOperands[I]); |
| } |
| buildTree_rec(VectorOperands[NumOps - 1], Depth + 1, {TE, NumOps - 1}); |
| return; |
| } |
| case Instruction::Load: { |
| // Check that a vectorized load would load the same memory as a scalar |
| // load. For example, we don't want to vectorize loads that are smaller |
| // than 8-bit. Even though we have a packed struct {<i2, i2, i2, i2>} LLVM |
| // treats loading/storing it as an i8 struct. If we vectorize loads/stores |
| // from such a struct, we read/write packed bits disagreeing with the |
| // unvectorized version. |
| SmallVector<Value *> PointerOps; |
| OrdersType CurrentOrder; |
| TreeEntry *TE = nullptr; |
| switch (canVectorizeLoads(VL, VL0, *TTI, *DL, *SE, CurrentOrder, |
| PointerOps)) { |
| case LoadsState::Vectorize: |
| if (CurrentOrder.empty()) { |
| // Original loads are consecutive and does not require reordering. |
| TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of loads.\n"); |
| } else { |
| fixupOrderingIndices(CurrentOrder); |
| // Need to reorder. |
| TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies, CurrentOrder); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled loads.\n"); |
| } |
| TE->setOperandsInOrder(); |
| break; |
| case LoadsState::ScatterVectorize: |
| // Vectorizing non-consecutive loads with `llvm.masked.gather`. |
| TE = newTreeEntry(VL, TreeEntry::ScatterVectorize, Bundle, S, |
| UserTreeIdx, ReuseShuffleIndicies); |
| TE->setOperandsInOrder(); |
| buildTree_rec(PointerOps, Depth + 1, {TE, 0}); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of non-consecutive loads.\n"); |
| break; |
| case LoadsState::Gather: |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| #ifndef NDEBUG |
| Type *ScalarTy = VL0->getType(); |
| if (DL->getTypeSizeInBits(ScalarTy) != |
| DL->getTypeAllocSizeInBits(ScalarTy)) |
| LLVM_DEBUG(dbgs() << "SLP: Gathering loads of non-packed type.\n"); |
| else if (any_of(VL, [](Value *V) { |
| return !cast<LoadInst>(V)->isSimple(); |
| })) |
| LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple loads.\n"); |
| else |
| LLVM_DEBUG(dbgs() << "SLP: Gathering non-consecutive loads.\n"); |
| #endif // NDEBUG |
| break; |
| } |
| return; |
| } |
| case Instruction::ZExt: |
| case Instruction::SExt: |
| case Instruction::FPToUI: |
| case Instruction::FPToSI: |
| case Instruction::FPExt: |
| case Instruction::PtrToInt: |
| case Instruction::IntToPtr: |
| case Instruction::SIToFP: |
| case Instruction::UIToFP: |
| case Instruction::Trunc: |
| case Instruction::FPTrunc: |
| case Instruction::BitCast: { |
| Type *SrcTy = VL0->getOperand(0)->getType(); |
| for (Value *V : VL) { |
| Type *Ty = cast<Instruction>(V)->getOperand(0)->getType(); |
| if (Ty != SrcTy || !isValidElementType(Ty)) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() |
| << "SLP: Gathering casts with different src types.\n"); |
| return; |
| } |
| } |
| TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of casts.\n"); |
| |
| TE->setOperandsInOrder(); |
| for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { |
| ValueList Operands; |
| // Prepare the operand vector. |
| for (Value *V : VL) |
| Operands.push_back(cast<Instruction>(V)->getOperand(i)); |
| |
| buildTree_rec(Operands, Depth + 1, {TE, i}); |
| } |
| return; |
| } |
| case Instruction::ICmp: |
| case Instruction::FCmp: { |
| // Check that all of the compares have the same predicate. |
| CmpInst::Predicate P0 = cast<CmpInst>(VL0)->getPredicate(); |
| CmpInst::Predicate SwapP0 = CmpInst::getSwappedPredicate(P0); |
| Type *ComparedTy = VL0->getOperand(0)->getType(); |
| for (Value *V : VL) { |
| CmpInst *Cmp = cast<CmpInst>(V); |
| if ((Cmp->getPredicate() != P0 && Cmp->getPredicate() != SwapP0) || |
| Cmp->getOperand(0)->getType() != ComparedTy) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() |
| << "SLP: Gathering cmp with different predicate.\n"); |
| return; |
| } |
| } |
| |
| TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of compares.\n"); |
| |
| ValueList Left, Right; |
| if (cast<CmpInst>(VL0)->isCommutative()) { |
| // Commutative predicate - collect + sort operands of the instructions |
| // so that each side is more likely to have the same opcode. |
| assert(P0 == SwapP0 && "Commutative Predicate mismatch"); |
| reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); |
| } else { |
| // Collect operands - commute if it uses the swapped predicate. |
| for (Value *V : VL) { |
| auto *Cmp = cast<CmpInst>(V); |
| Value *LHS = Cmp->getOperand(0); |
| Value *RHS = Cmp->getOperand(1); |
| if (Cmp->getPredicate() != P0) |
| std::swap(LHS, RHS); |
| Left.push_back(LHS); |
| Right.push_back(RHS); |
| } |
| } |
| TE->setOperand(0, Left); |
| TE->setOperand(1, Right); |
| buildTree_rec(Left, Depth + 1, {TE, 0}); |
| buildTree_rec(Right, Depth + 1, {TE, 1}); |
| return; |
| } |
| case Instruction::Select: |
| case Instruction::FNeg: |
| case Instruction::Add: |
| case Instruction::FAdd: |
| case Instruction::Sub: |
| case Instruction::FSub: |
| case Instruction::Mul: |
| case Instruction::FMul: |
| case Instruction::UDiv: |
| case Instruction::SDiv: |
| case Instruction::FDiv: |
| case Instruction::URem: |
| case Instruction::SRem: |
| case Instruction::FRem: |
| case Instruction::Shl: |
| case Instruction::LShr: |
| case Instruction::AShr: |
| case Instruction::And: |
| case Instruction::Or: |
| case Instruction::Xor: { |
| TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of un/bin op.\n"); |
| |
| // Sort operands of the instructions so that each side is more likely to |
| // have the same opcode. |
| if (isa<BinaryOperator>(VL0) && VL0->isCommutative()) { |
| ValueList Left, Right; |
| reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); |
| TE->setOperand(0, Left); |
| TE->setOperand(1, Right); |
| buildTree_rec(Left, Depth + 1, {TE, 0}); |
| buildTree_rec(Right, Depth + 1, {TE, 1}); |
| return; |
| } |
| |
| TE->setOperandsInOrder(); |
| for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { |
| ValueList Operands; |
| // Prepare the operand vector. |
| for (Value *V : VL) |
| Operands.push_back(cast<Instruction>(V)->getOperand(i)); |
| |
| buildTree_rec(Operands, Depth + 1, {TE, i}); |
| } |
| return; |
| } |
| case Instruction::GetElementPtr: { |
| // We don't combine GEPs with complicated (nested) indexing. |
| for (Value *V : VL) { |
| if (cast<Instruction>(V)->getNumOperands() != 2) { |
| LLVM_DEBUG(dbgs() << "SLP: not-vectorizable GEP (nested indexes).\n"); |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, 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 (Value *V : VL) { |
| Type *CurTy = cast<Instruction>(V)->getOperand(0)->getType(); |
| if (Ty0 != CurTy) { |
| LLVM_DEBUG(dbgs() |
| << "SLP: not-vectorizable GEP (different types).\n"); |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| return; |
| } |
| } |
| |
| // We don't combine GEPs with non-constant indexes. |
| Type *Ty1 = VL0->getOperand(1)->getType(); |
| for (Value *V : VL) { |
| auto Op = cast<Instruction>(V)->getOperand(1); |
| if (!isa<ConstantInt>(Op) || |
| (Op->getType() != Ty1 && |
| Op->getType()->getScalarSizeInBits() > |
| DL->getIndexSizeInBits( |
| V->getType()->getPointerAddressSpace()))) { |
| LLVM_DEBUG(dbgs() |
| << "SLP: not-vectorizable GEP (non-constant indexes).\n"); |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| return; |
| } |
| } |
| |
| TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of GEPs.\n"); |
| SmallVector<ValueList, 2> Operands(2); |
| // Prepare the operand vector for pointer operands. |
| for (Value *V : VL) |
| Operands.front().push_back( |
| cast<GetElementPtrInst>(V)->getPointerOperand()); |
| TE->setOperand(0, Operands.front()); |
| // Need to cast all indices to the same type before vectorization to |
| // avoid crash. |
| // Required to be able to find correct matches between different gather |
| // nodes and reuse the vectorized values rather than trying to gather them |
| // again. |
| int IndexIdx = 1; |
| Type *VL0Ty = VL0->getOperand(IndexIdx)->getType(); |
| Type *Ty = all_of(VL, |
| [VL0Ty, IndexIdx](Value *V) { |
| return VL0Ty == cast<GetElementPtrInst>(V) |
| ->getOperand(IndexIdx) |
| ->getType(); |
| }) |
| ? VL0Ty |
| : DL->getIndexType(cast<GetElementPtrInst>(VL0) |
| ->getPointerOperandType() |
| ->getScalarType()); |
| // Prepare the operand vector. |
| for (Value *V : VL) { |
| auto *Op = cast<Instruction>(V)->getOperand(IndexIdx); |
| auto *CI = cast<ConstantInt>(Op); |
| Operands.back().push_back(ConstantExpr::getIntegerCast( |
| CI, Ty, CI->getValue().isSignBitSet())); |
| } |
| TE->setOperand(IndexIdx, Operands.back()); |
| |
| for (unsigned I = 0, Ops = Operands.size(); I < Ops; ++I) |
| buildTree_rec(Operands[I], Depth + 1, {TE, I}); |
| return; |
| } |
| case Instruction::Store: { |
| // Check if the stores are consecutive or if we need to swizzle them. |
| llvm::Type *ScalarTy = cast<StoreInst>(VL0)->getValueOperand()->getType(); |
| // Avoid types that are padded when being allocated as scalars, while |
| // being packed together in a vector (such as i1). |
| if (DL->getTypeSizeInBits(ScalarTy) != |
| DL->getTypeAllocSizeInBits(ScalarTy)) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: Gathering stores of non-packed type.\n"); |
| return; |
| } |
| // Make sure all stores in the bundle are simple - we can't vectorize |
| // atomic or volatile stores. |
| SmallVector<Value *, 4> PointerOps(VL.size()); |
| ValueList Operands(VL.size()); |
| auto POIter = PointerOps.begin(); |
| auto OIter = Operands.begin(); |
| for (Value *V : VL) { |
| auto *SI = cast<StoreInst>(V); |
| if (!SI->isSimple()) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: Gathering non-simple stores.\n"); |
| return; |
| } |
| *POIter = SI->getPointerOperand(); |
| *OIter = SI->getValueOperand(); |
| ++POIter; |
| ++OIter; |
| } |
| |
| OrdersType CurrentOrder; |
| // Check the order of pointer operands. |
| if (llvm::sortPtrAccesses(PointerOps, ScalarTy, *DL, *SE, CurrentOrder)) { |
| Value *Ptr0; |
| Value *PtrN; |
| if (CurrentOrder.empty()) { |
| Ptr0 = PointerOps.front(); |
| PtrN = PointerOps.back(); |
| } else { |
| Ptr0 = PointerOps[CurrentOrder.front()]; |
| PtrN = PointerOps[CurrentOrder.back()]; |
| } |
| Optional<int> Dist = |
| getPointersDiff(ScalarTy, Ptr0, ScalarTy, PtrN, *DL, *SE); |
| // Check that the sorted pointer operands are consecutive. |
| if (static_cast<unsigned>(*Dist) == VL.size() - 1) { |
| if (CurrentOrder.empty()) { |
| // Original stores are consecutive and does not require reordering. |
| TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, |
| UserTreeIdx, ReuseShuffleIndicies); |
| TE->setOperandsInOrder(); |
| buildTree_rec(Operands, Depth + 1, {TE, 0}); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of stores.\n"); |
| } else { |
| fixupOrderingIndices(CurrentOrder); |
| TreeEntry *TE = |
| newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies, CurrentOrder); |
| TE->setOperandsInOrder(); |
| buildTree_rec(Operands, Depth + 1, {TE, 0}); |
| LLVM_DEBUG(dbgs() << "SLP: added a vector of jumbled stores.\n"); |
| } |
| return; |
| } |
| } |
| |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: Non-consecutive store.\n"); |
| return; |
| } |
| case Instruction::Call: { |
| // Check if the calls are all to the same vectorizable intrinsic or |
| // library function. |
| CallInst *CI = cast<CallInst>(VL0); |
| Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); |
| |
| VFShape Shape = VFShape::get( |
| *CI, ElementCount::getFixed(static_cast<unsigned int>(VL.size())), |
| false /*HasGlobalPred*/); |
| Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); |
| |
| if (!VecFunc && !isTriviallyVectorizable(ID)) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: Non-vectorizable call.\n"); |
| return; |
| } |
| Function *F = CI->getCalledFunction(); |
| unsigned NumArgs = CI->arg_size(); |
| SmallVector<Value*, 4> ScalarArgs(NumArgs, nullptr); |
| for (unsigned j = 0; j != NumArgs; ++j) |
| if (hasVectorInstrinsicScalarOpd(ID, j)) |
| ScalarArgs[j] = CI->getArgOperand(j); |
| for (Value *V : VL) { |
| CallInst *CI2 = dyn_cast<CallInst>(V); |
| if (!CI2 || CI2->getCalledFunction() != F || |
| getVectorIntrinsicIDForCall(CI2, TLI) != ID || |
| (VecFunc && |
| VecFunc != VFDatabase(*CI2).getVectorizedFunction(Shape)) || |
| !CI->hasIdenticalOperandBundleSchema(*CI2)) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: mismatched calls:" << *CI << "!=" << *V |
| << "\n"); |
| return; |
| } |
| // Some intrinsics have scalar arguments and should be same in order for |
| // them to be vectorized. |
| for (unsigned j = 0; j != NumArgs; ++j) { |
| if (hasVectorInstrinsicScalarOpd(ID, j)) { |
| Value *A1J = CI2->getArgOperand(j); |
| if (ScalarArgs[j] != A1J) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: mismatched arguments in call:" << *CI |
| << " argument " << ScalarArgs[j] << "!=" << A1J |
| << "\n"); |
| return; |
| } |
| } |
| } |
| // Verify that the bundle operands are identical between the two calls. |
| if (CI->hasOperandBundles() && |
| !std::equal(CI->op_begin() + CI->getBundleOperandsStartIndex(), |
| CI->op_begin() + CI->getBundleOperandsEndIndex(), |
| CI2->op_begin() + CI2->getBundleOperandsStartIndex())) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: mismatched bundle operands in calls:" |
| << *CI << "!=" << *V << '\n'); |
| return; |
| } |
| } |
| |
| TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| TE->setOperandsInOrder(); |
| for (unsigned i = 0, e = CI->arg_size(); i != e; ++i) { |
| // For scalar operands no need to to create an entry since no need to |
| // vectorize it. |
| if (hasVectorInstrinsicScalarOpd(ID, i)) |
| continue; |
| ValueList Operands; |
| // Prepare the operand vector. |
| for (Value *V : VL) { |
| auto *CI2 = cast<CallInst>(V); |
| Operands.push_back(CI2->getArgOperand(i)); |
| } |
| buildTree_rec(Operands, Depth + 1, {TE, i}); |
| } |
| return; |
| } |
| case Instruction::ShuffleVector: { |
| // If this is not an alternate sequence of opcode like add-sub |
| // then do not vectorize this instruction. |
| if (!S.isAltShuffle()) { |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: ShuffleVector are not vectorized.\n"); |
| return; |
| } |
| TreeEntry *TE = newTreeEntry(VL, Bundle /*vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: added a ShuffleVector op.\n"); |
| |
| // Reorder operands if reordering would enable vectorization. |
| if (isa<BinaryOperator>(VL0)) { |
| ValueList Left, Right; |
| reorderInputsAccordingToOpcode(VL, Left, Right, *DL, *SE, *this); |
| TE->setOperand(0, Left); |
| TE->setOperand(1, Right); |
| buildTree_rec(Left, Depth + 1, {TE, 0}); |
| buildTree_rec(Right, Depth + 1, {TE, 1}); |
| return; |
| } |
| |
| TE->setOperandsInOrder(); |
| for (unsigned i = 0, e = VL0->getNumOperands(); i < e; ++i) { |
| ValueList Operands; |
| // Prepare the operand vector. |
| for (Value *V : VL) |
| Operands.push_back(cast<Instruction>(V)->getOperand(i)); |
| |
| buildTree_rec(Operands, Depth + 1, {TE, i}); |
| } |
| return; |
| } |
| default: |
| BS.cancelScheduling(VL, VL0); |
| newTreeEntry(VL, None /*not vectorized*/, S, UserTreeIdx, |
| ReuseShuffleIndicies); |
| LLVM_DEBUG(dbgs() << "SLP: Gathering unknown instruction.\n"); |
| return; |
| } |
| } |
| |
| unsigned BoUpSLP::canMapToVector(Type *T, const DataLayout &DL) const { |
| unsigned N = 1; |
| Type *EltTy = T; |
| |
| while (isa<StructType>(EltTy) || isa<ArrayType>(EltTy) || |
| isa<VectorType>(EltTy)) { |
| if (auto *ST = dyn_cast<StructType>(EltTy)) { |
| // Check that struct is homogeneous. |
| for (const auto *Ty : ST->elements()) |
| if (Ty != *ST->element_begin()) |
| return 0; |
| N *= ST->getNumElements(); |
| EltTy = *ST->element_begin(); |
| } else if (auto *AT = dyn_cast<ArrayType>(EltTy)) { |
| N *= AT->getNumElements(); |
| EltTy = AT->getElementType(); |
| } else { |
| auto *VT = cast<FixedVectorType>(EltTy); |
| N *= VT->getNumElements(); |
| EltTy = VT->getElementType(); |
| } |
| } |
| |
| if (!isValidElementType(EltTy)) |
| return 0; |
| uint64_t VTSize = DL.getTypeStoreSizeInBits(FixedVectorType::get(EltTy, N)); |
| if (VTSize < MinVecRegSize || VTSize > MaxVecRegSize || VTSize != DL.getTypeStoreSizeInBits(T)) |
| return 0; |
| return N; |
| } |
| |
| bool BoUpSLP::canReuseExtract(ArrayRef<Value *> VL, Value *OpValue, |
| SmallVectorImpl<unsigned> &CurrentOrder) const { |
| 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 = cast<FixedVectorType>(Vec->getType())->getNumElements(); |
| } |
| |
| if (NElts != VL.size()) |
| return false; |
| |
| // Check that all of the indices extract from the correct offset. |
| bool ShouldKeepOrder = true; |
| unsigned E = VL.size(); |
| // Assign to all items the initial value E + 1 so we can check if the extract |
| // instruction index was used already. |
| // Also, later we can check that all the indices are used and we have a |
| // consecutive access in the extract instructions, by checking that no |
| // element of CurrentOrder still has value E + 1. |
| CurrentOrder.assign(E, E + 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, |
| ArrayRef<Value *> VectorizedVals) const { |
| return (I->hasOneUse() && is_contained(VectorizedVals, I)) || |
| llvm::all_of(I->users(), [this](User *U) { |
| return ScalarToTreeEntry.count(U) > 0; |
| }); |
| } |
| |
| static std::pair<InstructionCost, InstructionCost> |
| getVectorCallCosts(CallInst *CI, FixedVectorType *VecTy, |
| TargetTransformInfo *TTI, TargetLibraryInfo *TLI) { |
| Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); |
| |
| // Calculate the cost of the scalar and vector calls. |
| SmallVector<Type *, 4> VecTys; |
| for (Use &Arg : CI->args()) |
| VecTys.push_back( |
| FixedVectorType::get(Arg->getType(), VecTy->getNumElements())); |
| FastMathFlags FMF; |
| if (auto *FPCI = dyn_cast<FPMathOperator>(CI)) |
| FMF = FPCI->getFastMathFlags(); |
| SmallVector<const Value *> Arguments(CI->args()); |
| IntrinsicCostAttributes CostAttrs(ID, VecTy, Arguments, VecTys, FMF, |
| dyn_cast<IntrinsicInst>(CI)); |
| auto IntrinsicCost = |
| TTI->getIntrinsicInstrCost(CostAttrs, TTI::TCK_RecipThroughput); |
| |
| auto Shape = VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( |
| VecTy->getNumElements())), |
| false /*HasGlobalPred*/); |
| Function *VecFunc = VFDatabase(*CI).getVectorizedFunction(Shape); |
| auto LibCost = IntrinsicCost; |
| if (!CI->isNoBuiltin() && VecFunc) { |
| // Calculate the cost of the vector library call. |
| // If the corresponding vector call is cheaper, return its cost. |
| LibCost = TTI->getCallInstrCost(nullptr, VecTy, VecTys, |
| TTI::TCK_RecipThroughput); |
| } |
| return {IntrinsicCost, LibCost}; |
| } |
| |
| /// Compute the cost of creating a vector of type \p VecTy containing the |
| /// extracted values from \p VL. |
| static InstructionCost |
| computeExtractCost(ArrayRef<Value *> VL, FixedVectorType *VecTy, |
| TargetTransformInfo::ShuffleKind ShuffleKind, |
| ArrayRef<int> Mask, TargetTransformInfo &TTI) { |
| unsigned NumOfParts = TTI.getNumberOfParts(VecTy); |
| |
| if (ShuffleKind != TargetTransformInfo::SK_PermuteSingleSrc || !NumOfParts || |
| VecTy->getNumElements() < NumOfParts) |
| return TTI.getShuffleCost(ShuffleKind, VecTy, Mask); |
| |
| bool AllConsecutive = true; |
| unsigned EltsPerVector = VecTy->getNumElements() / NumOfParts; |
| unsigned Idx = -1; |
| InstructionCost Cost = 0; |
| |
| // Process extracts in blocks of EltsPerVector to check if the source vector |
| // operand can be re-used directly. If not, add the cost of creating a shuffle |
| // to extract the values into a vector register. |
| for (auto *V : VL) { |
| ++Idx; |
| |
| // Reached the start of a new vector registers. |
| if (Idx % EltsPerVector == 0) { |
| AllConsecutive = true; |
| continue; |
| } |
| |
| // Check all extracts for a vector register on the target directly |
| // extract values in order. |
| unsigned CurrentIdx = *getExtractIndex(cast<Instruction>(V)); |
| unsigned PrevIdx = *getExtractIndex(cast<Instruction>(VL[Idx - 1])); |
| AllConsecutive &= PrevIdx + 1 == CurrentIdx && |
| CurrentIdx % EltsPerVector == Idx % EltsPerVector; |
| |
| if (AllConsecutive) |
| continue; |
| |
| // Skip all indices, except for the last index per vector block. |
| if ((Idx + 1) % EltsPerVector != 0 && Idx + 1 != VL.size()) |
| continue; |
| |
| // If we have a series of extracts which are not consecutive and hence |
| // cannot re-use the source vector register directly, compute the shuffle |
| // cost to extract the a vector with EltsPerVector elements. |
| Cost += TTI.getShuffleCost( |
| TargetTransformInfo::SK_PermuteSingleSrc, |
| FixedVectorType::get(VecTy->getElementType(), EltsPerVector)); |
| } |
| return Cost; |
| } |
| |
| /// Build shuffle mask for shuffle graph entries and lists of main and alternate |
| /// operations operands. |
| static void |
| buildSuffleEntryMask(ArrayRef<Value *> VL, ArrayRef<unsigned> ReorderIndices, |
| ArrayRef<int> ReusesIndices, |
| const function_ref<bool(Instruction *)> IsAltOp, |
| SmallVectorImpl<int> &Mask, |
| SmallVectorImpl<Value *> *OpScalars = nullptr, |
| SmallVectorImpl<Value *> *AltScalars = nullptr) { |
| unsigned Sz = VL.size(); |
| Mask.assign(Sz, UndefMaskElem); |
| SmallVector<int> OrderMask; |
| if (!ReorderIndices.empty()) |
| inversePermutation(ReorderIndices, OrderMask); |
| for (unsigned I = 0; I < Sz; ++I) { |
| unsigned Idx = I; |
| if (!ReorderIndices.empty()) |
| Idx = OrderMask[I]; |
| auto *OpInst = cast<Instruction>(VL[Idx]); |
| if (IsAltOp(OpInst)) { |
| Mask[I] = Sz + Idx; |
| if (AltScalars) |
| AltScalars->push_back(OpInst); |
| } else { |
| Mask[I] = Idx; |
| if (OpScalars) |
| OpScalars->push_back(OpInst); |
| } |
| } |
| if (!ReusesIndices.empty()) { |
| SmallVector<int> NewMask(ReusesIndices.size(), UndefMaskElem); |
| transform(ReusesIndices, NewMask.begin(), [&Mask](int Idx) { |
| return Idx != UndefMaskElem ? Mask[Idx] : UndefMaskElem; |
| }); |
| Mask.swap(NewMask); |
| } |
| } |
| |
| InstructionCost BoUpSLP::getEntryCost(const TreeEntry *E, |
| ArrayRef<Value *> VectorizedVals) { |
| 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(); |
| else if (auto *IE = dyn_cast<InsertElementInst>(VL[0])) |
| ScalarTy = IE->getOperand(1)->getType(); |
| auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); |
| TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; |
| |
| // If we have computed a smaller type for the expression, update VecTy so |
| // that the costs will be accurate. |
| if (MinBWs.count(VL[0])) |
| VecTy = FixedVectorType::get( |
| IntegerType::get(F->getContext(), MinBWs[VL[0]].first), VL.size()); |
| unsigned EntryVF = E->getVectorFactor(); |
| auto *FinalVecTy = FixedVectorType::get(VecTy->getElementType(), EntryVF); |
| |
| bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); |
| // FIXME: it tries to fix a problem with MSVC buildbots. |
| TargetTransformInfo &TTIRef = *TTI; |
| auto &&AdjustExtractsCost = [this, &TTIRef, CostKind, VL, VecTy, |
| VectorizedVals](InstructionCost &Cost, |
| bool IsGather) { |
| DenseMap<Value *, int> ExtractVectorsTys; |
| 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), VectorizedVals) || |
| (IsGather && ScalarToTreeEntry.count(V))) |
| continue; |
| auto *EE = cast<ExtractElementInst>(V); |
| unsigned Idx = *getExtractIndex(EE); |
| if (TTIRef.getNumberOfParts(VecTy) != |
| TTIRef.getNumberOfParts(EE->getVectorOperandType())) { |
| auto It = |
| ExtractVectorsTys.try_emplace(EE->getVectorOperand(), Idx).first; |
| It->getSecond() = std::min<int>(It->second, Idx); |
| } |
| // Take credit for instruction that will become dead. |
| if (EE->hasOneUse()) { |
| Instruction *Ext = EE->user_back(); |
| if ((isa<SExtInst>(Ext) || isa<ZExtInst>(Ext)) && |
| all_of(Ext->users(), |
| [](User *U) { return isa<GetElementPtrInst>(U); })) { |
| // Use getExtractWithExtendCost() to calculate the cost of |
| // extractelement/ext pair. |
| Cost -= |
| TTIRef.getExtractWithExtendCost(Ext->getOpcode(), Ext->getType(), |
| EE->getVectorOperandType(), Idx); |
| // Add back the cost of s|zext which is subtracted separately. |
| Cost += TTIRef.getCastInstrCost( |
| Ext->getOpcode(), Ext->getType(), EE->getType(), |
| TTI::getCastContextHint(Ext), CostKind, Ext); |
| continue; |
| } |
| } |
| Cost -= TTIRef.getVectorInstrCost(Instruction::ExtractElement, |
| EE->getVectorOperandType(), Idx); |
| } |
| // Add a cost for subvector extracts/inserts if required. |
| for (const auto &Data : ExtractVectorsTys) { |
| auto *EEVTy = cast<FixedVectorType>(Data.first->getType()); |
| unsigned NumElts = VecTy->getNumElements(); |
| if (TTIRef.getNumberOfParts(EEVTy) > TTIRef.getNumberOfParts(VecTy)) { |
| unsigned Idx = (Data.second / NumElts) * NumElts; |
| unsigned EENumElts = EEVTy->getNumElements(); |
| if (Idx + NumElts <= EENumElts) { |
| Cost += |
| TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, |
| EEVTy, None, Idx, VecTy); |
| } else { |
| // Need to round up the subvector type vectorization factor to avoid a |
| // crash in cost model functions. Make SubVT so that Idx + VF of SubVT |
| // <= EENumElts. |
| auto *SubVT = |
| FixedVectorType::get(VecTy->getElementType(), EENumElts - Idx); |
| Cost += |
| TTIRef.getShuffleCost(TargetTransformInfo::SK_ExtractSubvector, |
| EEVTy, None, Idx, SubVT); |
| } |
| } else { |
| Cost += TTIRef.getShuffleCost(TargetTransformInfo::SK_InsertSubvector, |
| VecTy, None, 0, EEVTy); |
| } |
| } |
| }; |
| if (E->State == TreeEntry::NeedToGather) { |
| if (allConstant(VL)) |
| return 0; |
| if (isa<InsertElementInst>(VL[0])) |
| return InstructionCost::getInvalid(); |
| SmallVector<int> Mask; |
| SmallVector<const TreeEntry *> Entries; |
| Optional<TargetTransformInfo::ShuffleKind> Shuffle = |
| isGatherShuffledEntry(E, Mask, Entries); |
| if (Shuffle.hasValue()) { |
| InstructionCost GatherCost = 0; |
| if (ShuffleVectorInst::isIdentityMask(Mask)) { |
| // Perfect match in the graph, will reuse the previously vectorized |
| // node. Cost is 0. |
| LLVM_DEBUG( |
| dbgs() |
| << "SLP: perfect diamond match for gather bundle that starts with " |
| << *VL.front() << ".\n"); |
| if (NeedToShuffleReuses) |
| GatherCost = |
| TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, |
| FinalVecTy, E->ReuseShuffleIndices); |
| } else { |
| LLVM_DEBUG(dbgs() << "SLP: shuffled " << Entries.size() |
| << " entries for bundle that starts with " |
| << *VL.front() << ".\n"); |
| // Detected that instead of gather we can emit a shuffle of single/two |
| // previously vectorized nodes. Add the cost of the permutation rather |
| // than gather. |
| ::addMask(Mask, E->ReuseShuffleIndices); |
| GatherCost = TTI->getShuffleCost(*Shuffle, FinalVecTy, Mask); |
| } |
| return GatherCost; |
| } |
| if (isSplat(VL)) { |
| // Found the broadcasting of the single scalar, calculate the cost as the |
| // broadcast. |
| return TTI->getShuffleCost(TargetTransformInfo::SK_Broadcast, VecTy); |
| } |
| if (E->getOpcode() == Instruction::ExtractElement && allSameType(VL) && |
| allSameBlock(VL) && |
| !isa<ScalableVectorType>( |
| cast<ExtractElementInst>(E->getMainOp())->getVectorOperandType())) { |
| // Check that gather of extractelements can be represented as just a |
| // shuffle of a single/two vectors the scalars are extracted from. |
| SmallVector<int> Mask; |
| Optional<TargetTransformInfo::ShuffleKind> ShuffleKind = |
| isFixedVectorShuffle(VL, Mask); |
| if (ShuffleKind.hasValue()) { |
| // Found the bunch of extractelement instructions that must be gathered |
| // into a vector and can be represented as a permutation elements in a |
| // single input vector or of 2 input vectors. |
| InstructionCost Cost = |
| computeExtractCost(VL, VecTy, *ShuffleKind, Mask, *TTI); |
| AdjustExtractsCost(Cost, /*IsGather=*/true); |
| if (NeedToShuffleReuses) |
| Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, |
| FinalVecTy, E->ReuseShuffleIndices); |
| return Cost; |
| } |
| } |
| InstructionCost ReuseShuffleCost = 0; |
| if (NeedToShuffleReuses) |
| ReuseShuffleCost = TTI->getShuffleCost( |
| TTI::SK_PermuteSingleSrc, FinalVecTy, E->ReuseShuffleIndices); |
| // Improve gather cost for gather of loads, if we can group some of the |
| // loads into vector loads. |
| if (VL.size() > 2 && E->getOpcode() == Instruction::Load && |
| !E->isAltShuffle()) { |
| BoUpSLP::ValueSet VectorizedLoads; |
| unsigned StartIdx = 0; |
| unsigned VF = VL.size() / 2; |
| unsigned VectorizedCnt = 0; |
| unsigned ScatterVectorizeCnt = 0; |
| const unsigned Sz = DL->getTypeSizeInBits(E->getMainOp()->getType()); |
| for (unsigned MinVF = getMinVF(2 * Sz); VF >= MinVF; VF /= 2) { |
| for (unsigned Cnt = StartIdx, End = VL.size(); Cnt + VF <= End; |
| Cnt += VF) { |
| ArrayRef<Value *> Slice = VL.slice(Cnt, VF); |
| if (!VectorizedLoads.count(Slice.front()) && |
| !VectorizedLoads.count(Slice.back()) && allSameBlock(Slice)) { |
| SmallVector<Value *> PointerOps; |
| OrdersType CurrentOrder; |
| LoadsState LS = canVectorizeLoads(Slice, Slice.front(), *TTI, *DL, |
| *SE, CurrentOrder, PointerOps); |
| switch (LS) { |
| case LoadsState::Vectorize: |
| case LoadsState::ScatterVectorize: |
| // Mark the vectorized loads so that we don't vectorize them |
| // again. |
| if (LS == LoadsState::Vectorize) |
| ++VectorizedCnt; |
| else |
| ++ScatterVectorizeCnt; |
| VectorizedLoads.insert(Slice.begin(), Slice.end()); |
| // If we vectorized initial block, no need to try to vectorize it |
| // again. |
| if (Cnt == StartIdx) |
| StartIdx += VF; |
| break; |
| case LoadsState::Gather: |
| break; |
| } |
| } |
| } |
| // Check if the whole array was vectorized already - exit. |
| if (StartIdx >= VL.size()) |
| break; |
| // Found vectorizable parts - exit. |
| if (!VectorizedLoads.empty()) |
| break; |
| } |
| if (!VectorizedLoads.empty()) { |
| InstructionCost GatherCost = 0; |
| unsigned NumParts = TTI->getNumberOfParts(VecTy); |
| bool NeedInsertSubvectorAnalysis = |
| !NumParts || (VL.size() / VF) > NumParts; |
| // Get the cost for gathered loads. |
| for (unsigned I = 0, End = VL.size(); I < End; I += VF) { |
| if (VectorizedLoads.contains(VL[I])) |
| continue; |
| GatherCost += getGatherCost(VL.slice(I, VF)); |
| } |
| // The cost for vectorized loads. |
| InstructionCost ScalarsCost = 0; |
| for (Value *V : VectorizedLoads) { |
| auto *LI = cast<LoadInst>(V); |
| ScalarsCost += TTI->getMemoryOpCost( |
| Instruction::Load, LI->getType(), LI->getAlign(), |
| LI->getPointerAddressSpace(), CostKind, LI); |
| } |
| auto *LI = cast<LoadInst>(E->getMainOp()); |
| auto *LoadTy = FixedVectorType::get(LI->getType(), VF); |
| Align Alignment = LI->getAlign(); |
| GatherCost += |
| VectorizedCnt * |
| TTI->getMemoryOpCost(Instruction::Load, LoadTy, Alignment, |
| LI->getPointerAddressSpace(), CostKind, LI); |
| GatherCost += ScatterVectorizeCnt * |
| TTI->getGatherScatterOpCost( |
| Instruction::Load, LoadTy, LI->getPointerOperand(), |
| /*VariableMask=*/false, Alignment, CostKind, LI); |
| if (NeedInsertSubvectorAnalysis) { |
| // Add the cost for the subvectors insert. |
| for (int I = VF, E = VL.size(); I < E; I += VF) |
| GatherCost += TTI->getShuffleCost(TTI::SK_InsertSubvector, VecTy, |
| None, I, LoadTy); |
| } |
| return ReuseShuffleCost + GatherCost - ScalarsCost; |
| } |
| } |
| return ReuseShuffleCost + getGatherCost(VL); |
| } |
| InstructionCost CommonCost = 0; |
| SmallVector<int> Mask; |
| if (!E->ReorderIndices.empty()) { |
| SmallVector<int> NewMask; |
| if (E->getOpcode() == Instruction::Store) { |
| // For stores the order is actually a mask. |
| NewMask.resize(E->ReorderIndices.size()); |
| copy(E->ReorderIndices, NewMask.begin()); |
| } else { |
| inversePermutation(E->ReorderIndices, NewMask); |
| } |
| ::addMask(Mask, NewMask); |
| } |
| if (NeedToShuffleReuses) |
| ::addMask(Mask, E->ReuseShuffleIndices); |
| if (!Mask.empty() && !ShuffleVectorInst::isIdentityMask(Mask)) |
| CommonCost = |
| TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, FinalVecTy, Mask); |
| assert((E->State == TreeEntry::Vectorize || |
| E->State == TreeEntry::ScatterVectorize) && |
| "Unhandled state"); |
| assert(E->getOpcode() && allSameType(VL) && allSameBlock(VL) && "Invalid VL"); |
| Instruction *VL0 = E->getMainOp(); |
| unsigned ShuffleOrOp = |
| E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); |
| switch (ShuffleOrOp) { |
| case Instruction::PHI: |
| return 0; |
| |
| case Instruction::ExtractValue: |
| case Instruction::ExtractElement: { |
| // The common cost of removal ExtractElement/ExtractValue instructions + |
| // the cost of shuffles, if required to resuffle the original vector. |
| if (NeedToShuffleReuses) { |
| unsigned Idx = 0; |
| for (unsigned I : E->ReuseShuffleIndices) { |
| if (ShuffleOrOp == Instruction::ExtractElement) { |
| auto *EE = cast<ExtractElementInst>(VL[I]); |
| CommonCost -= TTI->getVectorInstrCost(Instruction::ExtractElement, |
| EE->getVectorOperandType(), |
| *getExtractIndex(EE)); |
| } else { |
| CommonCost -= TTI->getVectorInstrCost(Instruction::ExtractElement, |
| VecTy, Idx); |
| ++Idx; |
| } |
| } |
| Idx = EntryVF; |
| for (Value *V : VL) { |
| if (ShuffleOrOp == Instruction::ExtractElement) { |
| auto *EE = cast<ExtractElementInst>(V); |
| CommonCost += TTI->getVectorInstrCost(Instruction::ExtractElement, |
| EE->getVectorOperandType(), |
| *getExtractIndex(EE)); |
| } else { |
| --Idx; |
| CommonCost += TTI->getVectorInstrCost(Instruction::ExtractElement, |
| VecTy, Idx); |
| } |
| } |
| } |
| if (ShuffleOrOp == Instruction::ExtractValue) { |
| for (unsigned I = 0, E = VL.size(); I < E; ++I) { |
| auto *EI = cast<Instruction>(VL[I]); |
| // Take credit for instruction that will become dead. |
| if (EI->hasOneUse()) { |
| Instruction *Ext = EI->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. |
| CommonCost -= TTI->getExtractWithExtendCost( |
| Ext->getOpcode(), Ext->getType(), VecTy, I); |
| // Add back the cost of s|zext which is subtracted separately. |
| CommonCost += TTI->getCastInstrCost( |
| Ext->getOpcode(), Ext->getType(), EI->getType(), |
| TTI::getCastContextHint(Ext), CostKind, Ext); |
| continue; |
| } |
| } |
| CommonCost -= |
| TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, I); |
| } |
| } else { |
| AdjustExtractsCost(CommonCost, /*IsGather=*/false); |
| } |
| return CommonCost; |
| } |
| case Instruction::InsertElement: { |
| assert(E->ReuseShuffleIndices.empty() && |
| "Unique insertelements only are expected."); |
| auto *SrcVecTy = cast<FixedVectorType>(VL0->getType()); |
| |
| unsigned const NumElts = SrcVecTy->getNumElements(); |
| unsigned const NumScalars = VL.size(); |
| APInt DemandedElts = APInt::getZero(NumElts); |
| // TODO: Add support for Instruction::InsertValue. |
| SmallVector<int> Mask; |
| if (!E->ReorderIndices.empty()) { |
| inversePermutation(E->ReorderIndices, Mask); |
| Mask.append(NumElts - NumScalars, UndefMaskElem); |
| } else { |
| Mask.assign(NumElts, UndefMaskElem); |
| std::iota(Mask.begin(), std::next(Mask.begin(), NumScalars), 0); |
| } |
| unsigned Offset = *getInsertIndex(VL0, 0); |
| bool IsIdentity = true; |
| SmallVector<int> PrevMask(NumElts, UndefMaskElem); |
| Mask.swap(PrevMask); |
| for (unsigned I = 0; I < NumScalars; ++I) { |
| Optional<int> InsertIdx = getInsertIndex(VL[PrevMask[I]], 0); |
| if (!InsertIdx || *InsertIdx == UndefMaskElem) |
| continue; |
| DemandedElts.setBit(*InsertIdx); |
| IsIdentity &= *InsertIdx - Offset == I; |
| Mask[*InsertIdx - Offset] = I; |
| } |
| assert(Offset < NumElts && "Failed to find vector index offset"); |
| |
| InstructionCost Cost = 0; |
| Cost -= TTI->getScalarizationOverhead(SrcVecTy, DemandedElts, |
| /*Insert*/ true, /*Extract*/ false); |
| |
| if (IsIdentity && NumElts != NumScalars && Offset % NumScalars != 0) { |
| // FIXME: Replace with SK_InsertSubvector once it is properly supported. |
| unsigned Sz = PowerOf2Ceil(Offset + NumScalars); |
| Cost += TTI->getShuffleCost( |
| TargetTransformInfo::SK_PermuteSingleSrc, |
| FixedVectorType::get(SrcVecTy->getElementType(), Sz)); |
| } else if (!IsIdentity) { |
| auto *FirstInsert = |
| cast<Instruction>(*find_if(E->Scalars, [E](Value *V) { |
| return !is_contained(E->Scalars, |
| cast<Instruction>(V)->getOperand(0)); |
| })); |
| if (isa<UndefValue>(FirstInsert->getOperand(0))) { |
| Cost += TTI->getShuffleCost(TTI::SK_PermuteSingleSrc, SrcVecTy, Mask); |
| } else { |
| SmallVector<int> InsertMask(NumElts); |
| std::iota(InsertMask.begin(), InsertMask.end(), 0); |
| for (unsigned I = 0; I < NumElts; I++) { |
| if (Mask[I] != UndefMaskElem) |
| InsertMask[Offset + I] = NumElts + I; |
| } |
| Cost += |
| TTI->getShuffleCost(TTI::SK_PermuteTwoSrc, SrcVecTy, InsertMask); |
| } |
| } |
| |
| return Cost; |
| } |
| case Instruction::ZExt: |
| case Instruction::SExt: |
| case Instruction::FPToUI: |
| case Instruction::FPToSI: |
| case Instruction::FPExt: |
| case Instruction::PtrToInt: |
| case Instruction::IntToPtr: |
| case Instruction::SIToFP: |
| case Instruction::UIToFP: |
| case Instruction::Trunc: |
| case Instruction::FPTrunc: |
| case Instruction::BitCast: { |
| Type *SrcTy = VL0->getOperand(0)->getType(); |
| InstructionCost ScalarEltCost = |
| TTI->getCastInstrCost(E->getOpcode(), ScalarTy, SrcTy, |
| TTI::getCastContextHint(VL0), CostKind, VL0); |
| if (NeedToShuffleReuses) { |
| CommonCost -= (EntryVF - VL.size()) * ScalarEltCost; |
| } |
| |
| // Calculate the cost of this instruction. |
| InstructionCost ScalarCost = VL.size() * ScalarEltCost; |
| |
| auto *SrcVecTy = FixedVectorType::get(SrcTy, VL.size()); |
| InstructionCost VecCost = 0; |
| // Check if the values are candidates to demote. |
| if (!MinBWs.count(VL0) || VecTy != SrcVecTy) { |
| VecCost = CommonCost + TTI->getCastInstrCost( |
| E->getOpcode(), VecTy, SrcVecTy, |
| TTI::getCastContextHint(VL0), CostKind, VL0); |
| } |
| LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); |
| return VecCost - ScalarCost; |
| } |
| case Instruction::FCmp: |
| case Instruction::ICmp: |
| case Instruction::Select: { |
| // Calculate the cost of this instruction. |
| InstructionCost ScalarEltCost = |
| TTI->getCmpSelInstrCost(E->getOpcode(), ScalarTy, Builder.getInt1Ty(), |
| CmpInst::BAD_ICMP_PREDICATE, CostKind, VL0); |
| if (NeedToShuffleReuses) { |
| CommonCost -= (EntryVF - VL.size()) * ScalarEltCost; |
| } |
| auto *MaskTy = FixedVectorType::get(Builder.getInt1Ty(), VL.size()); |
| InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; |
| |
| // Check if all entries in VL are either compares or selects with compares |
| // as condition that have the same predicates. |
| CmpInst::Predicate VecPred = CmpInst::BAD_ICMP_PREDICATE; |
| bool First = true; |
| for (auto *V : VL) { |
| CmpInst::Predicate CurrentPred; |
| auto MatchCmp = m_Cmp(CurrentPred, m_Value(), m_Value()); |
| if ((!match(V, m_Select(MatchCmp, m_Value(), m_Value())) && |
| !match(V, MatchCmp)) || |
| (!First && VecPred != CurrentPred)) { |
| VecPred = CmpInst::BAD_ICMP_PREDICATE; |
| break; |
| } |
| First = false; |
| VecPred = CurrentPred; |
| } |
| |
| InstructionCost VecCost = TTI->getCmpSelInstrCost( |
| E->getOpcode(), VecTy, MaskTy, VecPred, CostKind, VL0); |
| // Check if it is possible and profitable to use min/max for selects in |
| // VL. |
| // |
| auto IntrinsicAndUse = canConvertToMinOrMaxIntrinsic(VL); |
| if (IntrinsicAndUse.first != Intrinsic::not_intrinsic) { |
| IntrinsicCostAttributes CostAttrs(IntrinsicAndUse.first, VecTy, |
| {VecTy, VecTy}); |
| InstructionCost IntrinsicCost = |
| TTI->getIntrinsicInstrCost(CostAttrs, CostKind); |
| // If the selects are the only uses of the compares, they will be dead |
| // and we can adjust the cost by removing their cost. |
| if (IntrinsicAndUse.second) |
| IntrinsicCost -= |
| TTI->getCmpSelInstrCost(Instruction::ICmp, VecTy, MaskTy, |
| CmpInst::BAD_ICMP_PREDICATE, CostKind); |
| VecCost = std::min(VecCost, IntrinsicCost); |
| } |
| LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); |
| return CommonCost + VecCost - ScalarCost; |
| } |
| case Instruction::FNeg: |
| case Instruction::Add: |
| case Instruction::FAdd: |
| case Instruction::Sub: |
| case Instruction::FSub: |
| case Instruction::Mul: |
| case Instruction::FMul: |
| case Instruction::UDiv: |
| case Instruction::SDiv: |
| case Instruction::FDiv: |
| case Instruction::URem: |
| case Instruction::SRem: |
| case Instruction::FRem: |
| case Instruction::Shl: |
| case Instruction::LShr: |
| case Instruction::AShr: |
| case Instruction::And: |
| case Instruction::Or: |
| case Instruction::Xor: { |
| // 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]); |
| unsigned OpIdx = isa<BinaryOperator>(I) ? 1 : 0; |
| ConstantInt *CInt = dyn_cast<ConstantInt>(I->getOperand(OpIdx)); |
| 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()); |
| InstructionCost ScalarEltCost = |
| TTI->getArithmeticInstrCost(E->getOpcode(), ScalarTy, CostKind, Op1VK, |
| Op2VK, Op1VP, Op2VP, Operands, VL0); |
| if (NeedToShuffleReuses) { |
| CommonCost -= (EntryVF - VL.size()) * ScalarEltCost; |
| } |
| InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; |
| InstructionCost VecCost = |
| TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind, Op1VK, |
| Op2VK, Op1VP, Op2VP, Operands, VL0); |
| LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); |
| return CommonCost + VecCost - ScalarCost; |
| } |
| case Instruction::GetElementPtr: { |
| TargetTransformInfo::OperandValueKind Op1VK = |
| TargetTransformInfo::OK_AnyValue; |
| TargetTransformInfo::OperandValueKind Op2VK = |
| TargetTransformInfo::OK_UniformConstantValue; |
| |
| InstructionCost ScalarEltCost = TTI->getArithmeticInstrCost( |
| Instruction::Add, ScalarTy, CostKind, Op1VK, Op2VK); |
| if (NeedToShuffleReuses) { |
| CommonCost -= (EntryVF - VL.size()) * ScalarEltCost; |
| } |
| InstructionCost ScalarCost = VecTy->getNumElements() * ScalarEltCost; |
| InstructionCost VecCost = TTI->getArithmeticInstrCost( |
| Instruction::Add, VecTy, CostKind, Op1VK, Op2VK); |
| LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); |
| return CommonCost + VecCost - ScalarCost; |
| } |
| case Instruction::Load: { |
| // Cost of wide load - cost of scalar loads. |
| Align Alignment = cast<LoadInst>(VL0)->getAlign(); |
| InstructionCost ScalarEltCost = TTI->getMemoryOpCost( |
| Instruction::Load, ScalarTy, Alignment, 0, CostKind, VL0); |
| if (NeedToShuffleReuses) { |
| CommonCost -= (EntryVF - VL.size()) * ScalarEltCost; |
| } |
| InstructionCost ScalarLdCost = VecTy->getNumElements() * ScalarEltCost; |
| InstructionCost VecLdCost; |
| if (E->State == TreeEntry::Vectorize) { |
| VecLdCost = TTI->getMemoryOpCost(Instruction::Load, VecTy, Alignment, 0, |
| CostKind, VL0); |
| } else { |
| assert(E->State == TreeEntry::ScatterVectorize && "Unknown EntryState"); |
| Align CommonAlignment = Alignment; |
| for (Value *V : VL) |
| CommonAlignment = |
| commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); |
| VecLdCost = TTI->getGatherScatterOpCost( |
| Instruction::Load, VecTy, cast<LoadInst>(VL0)->getPointerOperand(), |
| /*VariableMask=*/false, CommonAlignment, CostKind, VL0); |
| } |
| LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecLdCost, ScalarLdCost)); |
| return CommonCost + VecLdCost - ScalarLdCost; |
| } |
| case Instruction::Store: { |
| // We know that we can merge the stores. Calculate the cost. |
| bool IsReorder = !E->ReorderIndices.empty(); |
| auto *SI = |
| cast<StoreInst>(IsReorder ? VL[E->ReorderIndices.front()] : VL0); |
| Align Alignment = SI->getAlign(); |
| InstructionCost ScalarEltCost = TTI->getMemoryOpCost( |
| Instruction::Store, ScalarTy, Alignment, 0, CostKind, VL0); |
| InstructionCost ScalarStCost = VecTy->getNumElements() * ScalarEltCost; |
| InstructionCost VecStCost = TTI->getMemoryOpCost( |
| Instruction::Store, VecTy, Alignment, 0, CostKind, VL0); |
| LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecStCost, ScalarStCost)); |
| return CommonCost + 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. |
| IntrinsicCostAttributes CostAttrs(ID, *CI, 1); |
| InstructionCost ScalarEltCost = |
| TTI->getIntrinsicInstrCost(CostAttrs, CostKind); |
| if (NeedToShuffleReuses) { |
| CommonCost -= (EntryVF - VL.size()) * ScalarEltCost; |
| } |
| InstructionCost ScalarCallCost = VecTy->getNumElements() * ScalarEltCost; |
| |
| auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); |
| InstructionCost VecCallCost = |
| std::min(VecCallCosts.first, VecCallCosts.second); |
| |
| LLVM_DEBUG(dbgs() << "SLP: Call cost " << VecCallCost - ScalarCallCost |
| << " (" << VecCallCost << "-" << ScalarCallCost << ")" |
| << " for " << *CI << "\n"); |
| |
| return CommonCost + VecCallCost - ScalarCallCost; |
| } |
| case Instruction::ShuffleVector: { |
| assert(E->isAltShuffle() && |
| ((Instruction::isBinaryOp(E->getOpcode()) && |
| Instruction::isBinaryOp(E->getAltOpcode())) || |
| (Instruction::isCast(E->getOpcode()) && |
| Instruction::isCast(E->getAltOpcode()))) && |
| "Invalid Shuffle Vector Operand"); |
| InstructionCost ScalarCost = 0; |
| if (NeedToShuffleReuses) { |
| for (unsigned Idx : E->ReuseShuffleIndices) { |
| Instruction *I = cast<Instruction>(VL[Idx]); |
| CommonCost -= TTI->getInstructionCost(I, CostKind); |
| } |
| for (Value *V : VL) { |
| Instruction *I = cast<Instruction>(V); |
| CommonCost += TTI->getInstructionCost(I, CostKind); |
| } |
| } |
| for (Value *V : VL) { |
| Instruction *I = cast<Instruction>(V); |
| assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); |
| ScalarCost += TTI->getInstructionCost(I, CostKind); |
| } |
| // VecCost is equal to sum of the cost of creating 2 vectors |
| // and the cost of creating shuffle. |
| InstructionCost VecCost = 0; |
| // Try to find the previous shuffle node with the same operands and same |
| // main/alternate ops. |
| auto &&TryFindNodeWithEqualOperands = [this, E]() { |
| for (const std::unique_ptr<TreeEntry> &TE : VectorizableTree) { |
| if (TE.get() == E) |
| break; |
| if (TE->isAltShuffle() && |
| ((TE->getOpcode() == E->getOpcode() && |
| TE->getAltOpcode() == E->getAltOpcode()) || |
| (TE->getOpcode() == E->getAltOpcode() && |
| TE->getAltOpcode() == E->getOpcode())) && |
| TE->hasEqualOperands(*E)) |
| return true; |
| } |
| return false; |
| }; |
| if (TryFindNodeWithEqualOperands()) { |
| LLVM_DEBUG({ |
| dbgs() << "SLP: diamond match for alternate node found.\n"; |
| E->dump(); |
| }); |
| // No need to add new vector costs here since we're going to reuse |
| // same main/alternate vector ops, just do different shuffling. |
| } else if (Instruction::isBinaryOp(E->getOpcode())) { |
| VecCost = TTI->getArithmeticInstrCost(E->getOpcode(), VecTy, CostKind); |
| VecCost += TTI->getArithmeticInstrCost(E->getAltOpcode(), VecTy, |
| CostKind); |
| } else { |
| Type *Src0SclTy = E->getMainOp()->getOperand(0)->getType(); |
| Type *Src1SclTy = E->getAltOp()->getOperand(0)->getType(); |
| auto *Src0Ty = FixedVectorType::get(Src0SclTy, VL.size()); |
| auto *Src1Ty = FixedVectorType::get(Src1SclTy, VL.size()); |
| VecCost = TTI->getCastInstrCost(E->getOpcode(), VecTy, Src0Ty, |
| TTI::CastContextHint::None, CostKind); |
| VecCost += TTI->getCastInstrCost(E->getAltOpcode(), VecTy, Src1Ty, |
| TTI::CastContextHint::None, CostKind); |
| } |
| |
| SmallVector<int> Mask; |
| buildSuffleEntryMask( |
| E->Scalars, E->ReorderIndices, E->ReuseShuffleIndices, |
| [E](Instruction *I) { |
| assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); |
| return I->getOpcode() == E->getAltOpcode(); |
| }, |
| Mask); |
| CommonCost = |
| TTI->getShuffleCost(TargetTransformInfo::SK_Select, FinalVecTy, Mask); |
| LLVM_DEBUG(dumpTreeCosts(E, CommonCost, VecCost, ScalarCost)); |
| return CommonCost + VecCost - ScalarCost; |
| } |
| default: |
| llvm_unreachable("Unknown instruction"); |
| } |
| } |
| |
| bool BoUpSLP::isFullyVectorizableTinyTree(bool ForReduction) const { |
| LLVM_DEBUG(dbgs() << "SLP: Check whether the tree with height " |
| << VectorizableTree.size() << " is fully vectorizable .\n"); |
| |
| auto &&AreVectorizableGathers = [this](const TreeEntry *TE, unsigned Limit) { |
| SmallVector<int> Mask; |
| return TE->State == TreeEntry::NeedToGather && |
| !any_of(TE->Scalars, |
| [this](Value *V) { return EphValues.contains(V); }) && |
| (allConstant(TE->Scalars) || isSplat(TE->Scalars) || |
| TE->Scalars.size() < Limit || |
| (TE->getOpcode() == Instruction::ExtractElement && |
| isFixedVectorShuffle(TE->Scalars, Mask)) || |
| (TE->State == TreeEntry::NeedToGather && |
| TE->getOpcode() == Instruction::Load && !TE->isAltShuffle())); |
| }; |
| |
| // We only handle trees of heights 1 and 2. |
| if (VectorizableTree.size() == 1 && |
| (VectorizableTree[0]->State == TreeEntry::Vectorize || |
| (ForReduction && |
| AreVectorizableGathers(VectorizableTree[0].get(), |
| VectorizableTree[0]->Scalars.size()) && |
| VectorizableTree[0]->getVectorFactor() > 2))) |
| return true; |
| |
| if (VectorizableTree.size() != 2) |
| return false; |
| |
| // Handle splat and all-constants stores. Also try to vectorize tiny trees |
| // with the second gather nodes if they have less scalar operands rather than |
| // the initial tree element (may be profitable to shuffle the second gather) |
| // or they are extractelements, which form shuffle. |
| SmallVector<int> Mask; |
| if (VectorizableTree[0]->State == TreeEntry::Vectorize && |
| AreVectorizableGathers(VectorizableTree[1].get(), |
| VectorizableTree[0]->Scalars.size())) |
| return true; |
| |
| // Gathering cost would be too much for tiny trees. |
| if (VectorizableTree[0]->State == TreeEntry::NeedToGather || |
| (VectorizableTree[1]->State == TreeEntry::NeedToGather && |
| VectorizableTree[0]->State != TreeEntry::ScatterVectorize)) |
| return false; |
| |
| return true; |
| } |
| |
| static bool isLoadCombineCandidateImpl(Value *Root, unsigned NumElts, |
| TargetTransformInfo *TTI, |
| bool MustMatchOrInst) { |
| // Look past the root to find a source value. Arbitrarily follow the |
| // path through operand 0 of any 'or'. Also, peek through optional |
| // shift-left-by-multiple-of-8-bits. |
| Value *ZextLoad = Root; |
| const APInt *ShAmtC; |
| bool FoundOr = false; |
| while (!isa<ConstantExpr>(ZextLoad) && |
| (match(ZextLoad, m_Or(m_Value(), m_Value())) || |
| (match(ZextLoad, m_Shl(m_Value(), m_APInt(ShAmtC))) && |
| ShAmtC->urem(8) == 0))) { |
| auto *BinOp = cast<BinaryOperator>(ZextLoad); |
| ZextLoad = BinOp->getOperand(0); |
| if (BinOp->getOpcode() == Instruction::Or) |
| FoundOr = true; |
| } |
| // Check if the input is an extended load of the required or/shift expression. |
| Value *LoadPtr; |
| if ((MustMatchOrInst && !FoundOr) || ZextLoad == Root || |
| !match(ZextLoad, m_ZExt(m_Load(m_Value(LoadPtr))))) |
| return false; |
| |
| // Require that the total load bit width is a legal integer type. |
| // For example, <8 x i8> --> i64 is a legal integer on a 64-bit target. |
| // But <16 x i8> --> i128 is not, so the backend probably can't reduce it. |
| Type *SrcTy = LoadPtr->getType()->getPointerElementType(); |
| unsigned LoadBitWidth = SrcTy->getIntegerBitWidth() * NumElts; |
| if (!TTI->isTypeLegal(IntegerType::get(Root->getContext(), LoadBitWidth))) |
| return false; |
| |
| // Everything matched - assume that we can fold the whole sequence using |
| // load combining. |
| LLVM_DEBUG(dbgs() << "SLP: Assume load combining for tree starting at " |
| << *(cast<Instruction>(Root)) << "\n"); |
| |
| return true; |
| } |
| |
| bool BoUpSLP::isLoadCombineReductionCandidate(RecurKind RdxKind) const { |
| if (RdxKind != RecurKind::Or) |
| return false; |
| |
| unsigned NumElts = VectorizableTree[0]->Scalars.size(); |
| Value *FirstReduced = VectorizableTree[0]->Scalars[0]; |
| return isLoadCombineCandidateImpl(FirstReduced, NumElts, TTI, |
| /* MatchOr */ false); |
| } |
| |
| bool BoUpSLP::isLoadCombineCandidate() const { |
| // Peek through a final sequence of stores and check if all operations are |
| // likely to be load-combined. |
| unsigned NumElts = VectorizableTree[0]->Scalars.size(); |
| for (Value *Scalar : VectorizableTree[0]->Scalars) { |
| Value *X; |
| if (!match(Scalar, m_Store(m_Value(X), m_Value())) || |
| !isLoadCombineCandidateImpl(X, NumElts, TTI, /* MatchOr */ true)) |
| return false; |
| } |
| return true; |
| } |
| |
| bool BoUpSLP::isTreeTinyAndNotFullyVectorizable(bool ForReduction) const { |
| // No need to vectorize inserts of gathered values. |
| if (VectorizableTree.size() == 2 && |
| isa<InsertElementInst>(VectorizableTree[0]->Scalars[0]) && |
| VectorizableTree[1]->State == TreeEntry::NeedToGather) |
| return true; |
| |
| // We can vectorize the tree if its size is greater than or equal to the |
| // minimum size specified by the MinTreeSize command line option. |
| if (VectorizableTree.size() >= MinTreeSize) |
| return false; |
| |
| // If we have a tiny tree (a tree whose size is less than MinTreeSize), we |
| // can vectorize it if we can prove it fully vectorizable. |
| if (isFullyVectorizableTinyTree(ForReduction)) |
| return false; |
| |
| assert(VectorizableTree.empty() |
| ? ExternalUses.empty() |
| : true && "We shouldn't have any external users"); |
| |
| // Otherwise, we can't vectorize the tree. It is both tiny and not fully |
| // vectorizable. |
| return true; |
| } |
| |
| InstructionCost BoUpSLP::getSpillCost() const { |
| // Walk from the bottom of the tree to the top, tracking which values are |
| // live. When we see a call instruction that is not part of our tree, |
| // query TTI to see if there is a cost to keeping values live over it |
| // (for example, if spills and fills are required). |
| unsigned BundleWidth = VectorizableTree.front()->Scalars.size(); |
| InstructionCost Cost = 0; |
| |
| SmallPtrSet<Instruction*, 4> LiveValues; |
| Instruction *PrevInst = nullptr; |
| |
| // The entries in VectorizableTree are not necessarily ordered by their |
| // position in basic blocks. Collect them and order them by dominance so later |
| // instructions are guaranteed to be visited first. For instructions in |
| // different basic blocks, we only scan to the beginning of the block, so |
| // their order does not matter, as long as all instructions in a basic block |
| // are grouped together. Using dominance ensures a deterministic order. |
| SmallVector<Instruction *, 16> OrderedScalars; |
| for (const auto &TEPtr : VectorizableTree) { |
| Instruction *Inst = dyn_cast<Instruction>(TEPtr->Scalars[0]); |
| if (!Inst) |
| continue; |
| OrderedScalars.push_back(Inst); |
| } |
| llvm::sort(OrderedScalars, [&](Instruction *A, Instruction *B) { |
| auto *NodeA = DT->getNode(A->getParent()); |
| auto *NodeB = DT->getNode(B->getParent()); |
| assert(NodeA && "Should only process reachable instructions"); |
| assert(NodeB && "Should only process reachable instructions"); |
| assert((NodeA == NodeB) == (NodeA->getDFSNumIn() == NodeB->getDFSNumIn()) && |
| "Different nodes should have different DFS numbers"); |
| if (NodeA != NodeB) |
| return NodeA->getDFSNumIn() < NodeB->getDFSNumIn(); |
| return B->comesBefore(A); |
| }); |
| |
| for (Instruction *Inst : OrderedScalars) { |
| if (!PrevInst) { |
| PrevInst = Inst; |
| continue; |
| } |
| |
| // Update LiveValues. |
| LiveValues.erase(PrevInst); |
| for (auto &J : PrevInst->operands()) { |
| if (isa<Instruction>(&*J) && getTreeEntry(&*J)) |
| LiveValues.insert(cast<Instruction>(&*J)); |
| } |
| |
| LLVM_DEBUG({ |
| dbgs() << "SLP: #LV: " << LiveValues.size(); |
| for (auto *X : LiveValues) |
| dbgs() << " " << X->getName(); |
| dbgs() << ", Looking at "; |
| Inst->dump(); |
| }); |
| |
| // Now find the sequence of instructions between PrevInst and Inst. |
| unsigned NumCalls = 0; |
| BasicBlock::reverse_iterator InstIt = ++Inst->getIterator().getReverse(), |
| PrevInstIt = |
| PrevInst->getIterator().getReverse(); |
| while (InstIt != PrevInstIt) { |
| if (PrevInstIt == PrevInst->getParent()->rend()) { |
| PrevInstIt = Inst->getParent()->rbegin(); |
| continue; |
| } |
| |
| // Debug information does not impact spill cost. |
| if ((isa<CallInst>(&*PrevInstIt) && |
| !isa<DbgInfoIntrinsic>(&*PrevInstIt)) && |
| &*PrevInstIt != PrevInst) |
| NumCalls++; |
| |
| ++PrevInstIt; |
| } |
| |
| if (NumCalls) { |
| SmallVector<Type*, 4> V; |
| for (auto *II : LiveValues) { |
| auto *ScalarTy = II->getType(); |
| if (auto *VectorTy = dyn_cast<FixedVectorType>(ScalarTy)) |
| ScalarTy = VectorTy->getElementType(); |
| V.push_back(FixedVectorType::get(ScalarTy, BundleWidth)); |
| } |
| Cost += NumCalls * TTI->getCostOfKeepingLiveOverCall(V); |
| } |
| |
| PrevInst = Inst; |
| } |
| |
| return Cost; |
| } |
| |
| InstructionCost BoUpSLP::getTreeCost(ArrayRef<Value *> VectorizedVals) { |
| InstructionCost 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].get(); |
| |
| InstructionCost C = getEntryCost(&TE, VectorizedVals); |
| Cost += C; |
| LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C |
| << " for bundle that starts with " << *TE.Scalars[0] |
| << ".\n" |
| << "SLP: Current total cost = " << Cost << "\n"); |
| } |
| |
| SmallPtrSet<Value *, 16> ExtractCostCalculated; |
| InstructionCost ExtractCost = 0; |
| SmallVector<unsigned> VF; |
| SmallVector<SmallVector<int>> ShuffleMask; |
| SmallVector<Value *> FirstUsers; |
| SmallVector<APInt> DemandedElts; |
| 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; |
| |
| // No extract cost for vector "scalar" |
| if (isa<FixedVectorType>(EU.Scalar->getType())) |
| continue; |
| |
| // Already counted the cost for external uses when tried to adjust the cost |
| // for extractelements, no need to add it again. |
| if (isa<ExtractElementInst>(EU.Scalar)) |
| continue; |
| |
| // If found user is an insertelement, do not calculate extract cost but try |
| // to detect it as a final shuffled/identity match. |
| if (isa_and_nonnull<InsertElementInst>(EU.User)) { |
| if (auto *FTy = dyn_cast<FixedVectorType>(EU.User->getType())) { |
| Optional<int> InsertIdx = getInsertIndex(EU.User, 0); |
| if (!InsertIdx || *InsertIdx == UndefMaskElem) |
| continue; |
| Value *VU = EU.User; |
| auto *It = find_if(FirstUsers, [VU](Value *V) { |
| // Checks if 2 insertelements are from the same buildvector. |
| if (VU->getType() != V->getType()) |
| return false; |
| auto *IE1 = cast<InsertElementInst>(VU); |
| auto *IE2 = cast<InsertElementInst>(V); |
| // Go through of insertelement instructions trying to find either VU |
| // as the original vector for IE2 or V as the original vector for IE1. |
| do { |
| if (IE1 == VU || IE2 == V) |
| return true; |
| if (IE1) |
| IE1 = dyn_cast<InsertElementInst>(IE1->getOperand(0)); |
| if (IE2) |
| IE2 = dyn_cast<InsertElementInst>(IE2->getOperand(0)); |
| } while (IE1 || IE2); |
| return false; |
| }); |
| int VecId = -1; |
| if (It == FirstUsers.end()) { |
| VF.push_back(FTy->getNumElements()); |
| ShuffleMask.emplace_back(VF.back(), UndefMaskElem); |
| FirstUsers.push_back(EU.User); |
| DemandedElts.push_back(APInt::getZero(VF.back())); |
| VecId = FirstUsers.size() - 1; |
| } else { |
| VecId = std::distance(FirstUsers.begin(), It); |
| } |
| int Idx = *InsertIdx; |
| ShuffleMask[VecId][Idx] = EU.Lane; |
| DemandedElts[VecId].setBit(Idx); |
| } |
| } |
| |
| // If we plan to rewrite the tree in a smaller type, we will need to sign |
| // extend the extracted value back to the original type. Here, we account |
| // for the extract and the added cost of the sign extend if needed. |
| auto *VecTy = FixedVectorType::get(EU.Scalar->getType(), BundleWidth); |
| auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; |
| if (MinBWs.count(ScalarRoot)) { |
| auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); |
| auto Extend = |
| MinBWs[ScalarRoot].second ? Instruction::SExt : Instruction::ZExt; |
| VecTy = FixedVectorType::get(MinTy, BundleWidth); |
| ExtractCost += TTI->getExtractWithExtendCost(Extend, EU.Scalar->getType(), |
| VecTy, EU.Lane); |
| } else { |
| ExtractCost += |
| TTI->getVectorInstrCost(Instruction::ExtractElement, VecTy, EU.Lane); |
| } |
| } |
| |
| InstructionCost SpillCost = getSpillCost(); |
| Cost += SpillCost + ExtractCost; |
| for (int I = 0, E = FirstUsers.size(); I < E; ++I) { |
| // For the very first element - simple shuffle of the source vector. |
| int Limit = ShuffleMask[I].size() * 2; |
| if (I == 0 && |
| all_of(ShuffleMask[I], [Limit](int Idx) { return Idx < Limit; }) && |
| !ShuffleVectorInst::isIdentityMask(ShuffleMask[I])) { |
| InstructionCost C = TTI->getShuffleCost( |
| TTI::SK_PermuteSingleSrc, |
| cast<FixedVectorType>(FirstUsers[I]->getType()), ShuffleMask[I]); |
| LLVM_DEBUG(dbgs() << "SLP: Adding cost " << C |
| << " for final shuffle of insertelement external users " |
| << *VectorizableTree.front()->Scalars.front() << ".\n" |
| << "SLP: Current total cost = " << Cost << "\n"); |
| Cost += C; |
| continue; |
| } |
| // Other elements - permutation of 2 vectors (the initial one and the next |
| // Ith incoming vector). |
| unsigned VF = ShuffleMask[I].size(); |
| for (unsigned Idx = 0; Idx < VF; ++Idx) { |
| int &Mask = ShuffleMask[I][Idx]; |
| Mask = Mask == UndefMaskElem ? Idx : VF + Mask; |
| } |
| InstructionCost C = TTI->getShuffleCost( |
| TTI::SK_PermuteTwoSrc, cast<FixedVectorType>(FirstUsers[I]->getType()), |
| ShuffleMask[I]); |
| LLVM_DEBUG( |
| dbgs() |
| << "SLP: Adding cost " << C |
| << " for final shuffle of vector node and external insertelement users " |
| << *VectorizableTree.front()->Scalars.front() << ".\n" |
| << "SLP: Current total cost = " << Cost << "\n"); |
| Cost += C; |
| InstructionCost InsertCost = TTI->getScalarizationOverhead( |
| cast<FixedVectorType>(FirstUsers[I]->getType()), DemandedElts[I], |
| /*Insert*/ true, |
| /*Extract*/ false); |
| Cost -= InsertCost; |
| LLVM_DEBUG(dbgs() << "SLP: subtracting the cost " << InsertCost |
| << " for insertelements gather.\n" |
| << "SLP: Current total cost = " << Cost << "\n"); |
| } |
| |
| #ifndef NDEBUG |
| SmallString<256> Str; |
| { |
| raw_svector_ostream OS(Str); |
| OS << "SLP: Spill Cost = " << SpillCost << ".\n" |
| << "SLP: Extract Cost = " << ExtractCost << ".\n" |
| << "SLP: Total Cost = " << Cost << ".\n"; |
| } |
| LLVM_DEBUG(dbgs() << Str); |
| if (ViewSLPTree) |
| ViewGraph(this, "SLP" + F->getName(), false, Str); |
| #endif |
| |
| return Cost; |
| } |
| |
| Optional<TargetTransformInfo::ShuffleKind> |
| BoUpSLP::isGatherShuffledEntry(const TreeEntry *TE, SmallVectorImpl<int> &Mask, |
| SmallVectorImpl<const TreeEntry *> &Entries) { |
| // TODO: currently checking only for Scalars in the tree entry, need to count |
| // reused elements too for better cost estimation. |
| Mask.assign(TE->Scalars.size(), UndefMaskElem); |
| Entries.clear(); |
| // Build a lists of values to tree entries. |
| DenseMap<Value *, SmallPtrSet<const TreeEntry *, 4>> ValueToTEs; |
| for (const std::unique_ptr<TreeEntry> &EntryPtr : VectorizableTree) { |
| if (EntryPtr.get() == TE) |
| break; |
| if (EntryPtr->State != TreeEntry::NeedToGather) |
| continue; |
| for (Value *V : EntryPtr->Scalars) |
| ValueToTEs.try_emplace(V).first->getSecond().insert(EntryPtr.get()); |
| } |
| // Find all tree entries used by the gathered values. If no common entries |
| // found - not a shuffle. |
| // Here we build a set of tree nodes for each gathered value and trying to |
| // find the intersection between these sets. If we have at least one common |
| // tree node for each gathered value - we have just a permutation of the |
| // single vector. If we have 2 different sets, we're in situation where we |
| // have a permutation of 2 input vectors. |
| SmallVector<SmallPtrSet<const TreeEntry *, 4>> UsedTEs; |
| DenseMap<Value *, int> UsedValuesEntry; |
| for (Value *V : TE->Scalars) { |
| if (isa<UndefValue>(V)) |
| continue; |
| // Build a list of tree entries where V is used. |
| SmallPtrSet<const TreeEntry *, 4> VToTEs; |
| auto It = ValueToTEs.find(V); |
| if (It != ValueToTEs.end()) |
| VToTEs = It->second; |
| if (const TreeEntry *VTE = getTreeEntry(V)) |
| VToTEs.insert(VTE); |
| if (VToTEs.empty()) |
| return None; |
| if (UsedTEs.empty()) { |
| // The first iteration, just insert the list of nodes to vector. |
| UsedTEs.push_back(VToTEs); |
| } else { |
| // Need to check if there are any previously used tree nodes which use V. |
| // If there are no such nodes, consider that we have another one input |
| // vector. |
| SmallPtrSet<const TreeEntry *, 4> SavedVToTEs(VToTEs); |
| unsigned Idx = 0; |
| for (SmallPtrSet<const TreeEntry *, 4> &Set : UsedTEs) { |
| // Do we have a non-empty intersection of previously listed tree entries |
| // and tree entries using current V? |
| set_intersect(VToTEs, Set); |
| if (!VToTEs.empty()) { |
| // Yes, write the new subset and continue analysis for the next |
| // scalar. |
| Set.swap(VToTEs); |
| break; |
| } |
| VToTEs = SavedVToTEs; |
| ++Idx; |
| } |
| // No non-empty intersection found - need to add a second set of possible |
| // source vectors. |
| if (Idx == UsedTEs.size()) { |
| // If the number of input vectors is greater than 2 - not a permutation, |
| // fallback to the regular gather. |
| if (UsedTEs.size() == 2) |
| return None; |
| UsedTEs.push_back(SavedVToTEs); |
| Idx = UsedTEs.size() - 1; |
| } |
| UsedValuesEntry.try_emplace(V, Idx); |
| } |
| } |
| |
| unsigned VF = 0; |
| if (UsedTEs.size() == 1) { |
| // Try to find the perfect match in another gather node at first. |
| auto It = find_if(UsedTEs.front(), [TE](const TreeEntry *EntryPtr) { |
| return EntryPtr->isSame(TE->Scalars); |
| }); |
| if (It != UsedTEs.front().end()) { |
| Entries.push_back(*It); |
| std::iota(Mask.begin(), Mask.end(), 0); |
| return TargetTransformInfo::SK_PermuteSingleSrc; |
| } |
| // No perfect match, just shuffle, so choose the first tree node. |
| Entries.push_back(*UsedTEs.front().begin()); |
| } else { |
| // Try to find nodes with the same vector factor. |
| assert(UsedTEs.size() == 2 && "Expected at max 2 permuted entries."); |
| DenseMap<int, const TreeEntry *> VFToTE; |
| for (const TreeEntry *TE : UsedTEs.front()) |
| VFToTE.try_emplace(TE->getVectorFactor(), TE); |
| for (const TreeEntry *TE : UsedTEs.back()) { |
| auto It = VFToTE.find(TE->getVectorFactor()); |
| if (It != VFToTE.end()) { |
| VF = It->first; |
| Entries.push_back(It->second); |
| Entries.push_back(TE); |
| break; |
| } |
| } |
| // No 2 source vectors with the same vector factor - give up and do regular |
| // gather. |
| if (Entries.empty()) |
| return None; |
| } |
| |
| // Build a shuffle mask for better cost estimation and vector emission. |
| for (int I = 0, E = TE->Scalars.size(); I < E; ++I) { |
| Value *V = TE->Scalars[I]; |
| if (isa<UndefValue>(V)) |
| continue; |
| unsigned Idx = UsedValuesEntry.lookup(V); |
| const TreeEntry *VTE = Entries[Idx]; |
| int FoundLane = VTE->findLaneForValue(V); |
| Mask[I] = Idx * VF + FoundLane; |
| // Extra check required by isSingleSourceMaskImpl function (called by |
| // ShuffleVectorInst::isSingleSourceMask). |
| if (Mask[I] >= 2 * E) |
| return None; |
| } |
| switch (Entries.size()) { |
| case 1: |
| return TargetTransformInfo::SK_PermuteSingleSrc; |
| case 2: |
| return TargetTransformInfo::SK_PermuteTwoSrc; |
| default: |
| break; |
| } |
| return None; |
| } |
| |
| InstructionCost |
| BoUpSLP::getGatherCost(FixedVectorType *Ty, |
| const DenseSet<unsigned> &ShuffledIndices, |
| bool NeedToShuffle) const { |
| unsigned NumElts = Ty->getNumElements(); |
| APInt DemandedElts = APInt::getZero(NumElts); |
| for (unsigned I = 0; I < NumElts; ++I) |
| if (!ShuffledIndices.count(I)) |
| DemandedElts.setBit(I); |
| InstructionCost Cost = |
| TTI->getScalarizationOverhead(Ty, DemandedElts, /*Insert*/ true, |
| /*Extract*/ false); |
| if (NeedToShuffle) |
| Cost += TTI->getShuffleCost(TargetTransformInfo::SK_PermuteSingleSrc, Ty); |
| return Cost; |
| } |
| |
| InstructionCost BoUpSLP::getGatherCost(ArrayRef<Value *> VL) const { |
| // Find the type of the operands in VL. |
| Type *ScalarTy = VL[0]->getType(); |
| if (StoreInst *SI = dyn_cast<StoreInst>(VL[0])) |
| ScalarTy = SI->getValueOperand()->getType(); |
| auto *VecTy = FixedVectorType::get(ScalarTy, VL.size()); |
| bool DuplicateNonConst = false; |
| // Find the cost of inserting/extracting values from the vector. |
| // Check if the same elements are inserted several times and count them as |
| // shuffle candidates. |
| 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; |
| // No need to shuffle duplicates for constants. |
| if (isConstant(VL[Idx])) { |
| ShuffledElements.insert(Idx); |
| continue; |
| } |
| if (!UniqueElements.insert(VL[Idx]).second) { |
| DuplicateNonConst = true; |
| ShuffledElements.insert(Idx); |
| } |
| } |
| return getGatherCost(VecTy, ShuffledElements, DuplicateNonConst); |
| } |
| |
| // Perform operand reordering on the instructions in VL and return the reordered |
| // operands in Left and Right. |
| void BoUpSLP::reorderInputsAccordingToOpcode(ArrayRef<Value *> VL, |
| SmallVectorImpl<Value *> &Left, |
| SmallVectorImpl<Value *> &Right, |
| const DataLayout &DL, |
| ScalarEvolution &SE, |
| const BoUpSLP &R) { |
| if (VL.empty()) |
| return; |
| VLOperands Ops(VL, DL, SE, R); |
| // Reorder the operands in place. |
| Ops.reorder(); |
| Left = Ops.getVL(0); |
| Right = Ops.getVL(1); |
| } |
| |
| void BoUpSLP::setInsertPointAfterBundle(const TreeEntry *E) { |
| // Get the basic block this bundle is in. All instructions in the bundle |
| // should be in this block. |
| auto *Front = E->getMainOp(); |
| auto *BB = Front->getParent(); |
| assert(llvm::all_of(E->Scalars, [=](Value *V) -> bool { |
| auto *I = cast<Instruction>(V); |
| return !E->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(E->isOneOf(E->Scalars.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(E->Scalars.begin(), E->Scalars.end()); |
| for (auto &I : make_range(BasicBlock::iterator(Front), BB->end())) { |
| if (Bundle.erase(&I) && E->isOpcodeOrAlt(&I)) |
| LastInst = &I; |
| if (Bundle.empty()) |
| break; |
| } |
| } |
| assert(LastInst && "Failed to find last instruction in bundle"); |
| |
| // 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) { |
| // List of instructions/lanes from current block and/or the blocks which are |
| // part of the current loop. These instructions will be inserted at the end to |
| // make it possible to optimize loops and hoist invariant instructions out of |
| // the loops body with better chances for success. |
| SmallVector<std::pair<Value *, unsigned>, 4> PostponedInsts; |
| SmallSet<int, 4> PostponedIndices; |
| Loop *L = LI->getLoopFor(Builder.GetInsertBlock()); |
| auto &&CheckPredecessor = [](BasicBlock *InstBB, BasicBlock *InsertBB) { |
| SmallPtrSet<BasicBlock *, 4> Visited; |
| while (InsertBB && InsertBB != InstBB && Visited.insert(InsertBB).second) |
| InsertBB = InsertBB->getSinglePredecessor(); |
| return InsertBB && InsertBB == InstBB; |
| }; |
| for (int I = 0, E = VL.size(); I < E; ++I) { |
| if (auto *Inst = dyn_cast<Instruction>(VL[I])) |
| if ((CheckPredecessor(Inst->getParent(), Builder.GetInsertBlock()) || |
| getTreeEntry(Inst) || (L && (L->contains(Inst)))) && |
| PostponedIndices.insert(I).second) |
| PostponedInsts.emplace_back(Inst, I); |
| } |
| |
| auto &&CreateInsertElement = [this](Value *Vec, Value *V, unsigned Pos) { |
| Vec = Builder.CreateInsertElement(Vec, V, Builder.getInt32(Pos)); |
| auto *InsElt = dyn_cast<InsertElementInst>(Vec); |
| if (!InsElt) |
| return Vec; |
| GatherShuffleSeq.insert(InsElt); |
| CSEBlocks.insert(InsElt->getParent()); |
| // Add to our 'need-to-extract' list. |
| if (TreeEntry *Entry = getTreeEntry(V)) { |
| // Find which lane we need to extract. |
| unsigned FoundLane = Entry->findLaneForValue(V); |
| ExternalUses.emplace_back(V, InsElt, FoundLane); |
| } |
| return Vec; |
| }; |
| Value *Val0 = |
| isa<StoreInst>(VL[0]) ? cast<StoreInst>(VL[0])->getValueOperand() : VL[0]; |
| FixedVectorType *VecTy = FixedVectorType::get(Val0->getType(), VL.size()); |
| Value *Vec = PoisonValue::get(VecTy); |
| SmallVector<int> NonConsts; |
| // Insert constant values at first. |
| for (int I = 0, E = VL.size(); I < E; ++I) { |
| if (PostponedIndices.contains(I)) |
| continue; |
| if (!isConstant(VL[I])) { |
| NonConsts.push_back(I); |
| continue; |
| } |
| Vec = CreateInsertElement(Vec, VL[I], I); |
| } |
| // Insert non-constant values. |
| for (int I : NonConsts) |
| Vec = CreateInsertElement(Vec, VL[I], I); |
| // Append instructions, which are/may be part of the loop, in the end to make |
| // it possible to hoist non-loop-based instructions. |
| for (const std::pair<Value *, unsigned> &Pair : PostponedInsts) |
| Vec = CreateInsertElement(Vec, Pair.first, Pair.second); |
| |
| return Vec; |
| } |
| |
| namespace { |
| /// Merges shuffle masks and emits final shuffle instruction, if required. |
| class ShuffleInstructionBuilder { |
| IRBuilderBase &Builder; |
| const unsigned VF = 0; |
| bool IsFinalized = false; |
| SmallVector<int, 4> Mask; |
| |
| public: |
| ShuffleInstructionBuilder(IRBuilderBase &Builder, unsigned VF) |
| : Builder(Builder), VF(VF) {} |
| |
| /// Adds a mask, inverting it before applying. |
| void addInversedMask(ArrayRef<unsigned> SubMask) { |
| if (SubMask.empty()) |
| return; |
| SmallVector<int, 4> NewMask; |
| inversePermutation(SubMask, NewMask); |
| addMask(NewMask); |
| } |
| |
| /// Functions adds masks, merging them into single one. |
| void addMask(ArrayRef<unsigned> SubMask) { |
| SmallVector<int, 4> NewMask(SubMask.begin(), SubMask.end()); |
| addMask(NewMask); |
| } |
| |
| void addMask(ArrayRef<int> SubMask) { ::addMask(Mask, SubMask); } |
| |
| Value *finalize(Value *V) { |
| IsFinalized = true; |
| unsigned ValueVF = cast<FixedVectorType>(V->getType())->getNumElements(); |
| if (VF == ValueVF && Mask.empty()) |
| return V; |
| SmallVector<int, 4> NormalizedMask(VF, UndefMaskElem); |
| std::iota(NormalizedMask.begin(), NormalizedMask.end(), 0); |
| addMask(NormalizedMask); |
| |
| if (VF == ValueVF && ShuffleVectorInst::isIdentityMask(Mask)) |
| return V; |
| return Builder.CreateShuffleVector(V, Mask, "shuffle"); |
| } |
| |
| ~ShuffleInstructionBuilder() { |
| assert((IsFinalized || Mask.empty()) && |
| "Shuffle construction must be finalized."); |
| } |
| }; |
| } // namespace |
| |
| Value *BoUpSLP::vectorizeTree(ArrayRef<Value *> VL) { |
| unsigned VF = VL.size(); |
| InstructionsState S = getSameOpcode(VL); |
| if (S.getOpcode()) { |
| if (TreeEntry *E = getTreeEntry(S.OpValue)) |
| if (E->isSame(VL)) { |
| Value *V = vectorizeTree(E); |
| if (VF != cast<FixedVectorType>(V->getType())->getNumElements()) { |
| if (!E->ReuseShuffleIndices.empty()) { |
| // Reshuffle to get only unique values. |
| // If some of the scalars are duplicated in the vectorization tree |
| // entry, we do not vectorize them but instead generate a mask for |
| // the reuses. But if there are several users of the same entry, |
| // they may have different vectorization factors. This is especially |
| // important for PHI nodes. In this case, we need to adapt the |
| // resulting instruction for the user vectorization factor and have |
| // to reshuffle it again to take only unique elements of the vector. |
| // Without this code the function incorrectly returns reduced vector |
| // instruction with the same elements, not with the unique ones. |
| |
| // block: |
| // %phi = phi <2 x > { .., %entry} {%shuffle, %block} |
| // %2 = shuffle <2 x > %phi, poison, <4 x > <1, 1, 0, 0> |
| // ... (use %2) |
| // %shuffle = shuffle <2 x> %2, poison, <2 x> {2, 0} |
| // br %block |
| SmallVector<int> UniqueIdxs(VF, UndefMaskElem); |
| SmallSet<int, 4> UsedIdxs; |
| int Pos = 0; |
| int Sz = VL.size(); |
| for (int Idx : E->ReuseShuffleIndices) { |
| if (Idx != Sz && Idx != UndefMaskElem && |
| UsedIdxs.insert(Idx).second) |
| UniqueIdxs[Idx] = Pos; |
| ++Pos; |
| } |
| assert(VF >= UsedIdxs.size() && "Expected vectorization factor " |
| "less than original vector size."); |
| UniqueIdxs.append(VF - UsedIdxs.size(), UndefMaskElem); |
| V = Builder.CreateShuffleVector(V, UniqueIdxs, "shrink.shuffle"); |
| } else { |
| assert(VF < cast<FixedVectorType>(V->getType())->getNumElements() && |
| "Expected vectorization factor less " |
| "than original vector size."); |
| SmallVector<int> UniformMask(VF, 0); |
| std::iota(UniformMask.begin(), UniformMask.end(), 0); |
| V = Builder.CreateShuffleVector(V, UniformMask, "shrink.shuffle"); |
| } |
| } |
| return V; |
| } |
| } |
| |
| // Check that every instruction appears once in this bundle. |
| SmallVector<int> ReuseShuffleIndicies; |
| SmallVector<Value *> UniqueValues; |
| if (VL.size() > 2) { |
| DenseMap<Value *, unsigned> UniquePositions; |
| unsigned NumValues = |
| std::distance(VL.begin(), find_if(reverse(VL), [](Value *V) { |
| return !isa<UndefValue>(V); |
| }).base()); |
| VF = std::max<unsigned>(VF, PowerOf2Ceil(NumValues)); |
| int UniqueVals = 0; |
| for (Value *V : VL.drop_back(VL.size() - VF)) { |
| if (isa<UndefValue>(V)) { |
| ReuseShuffleIndicies.emplace_back(UndefMaskElem); |
| continue; |
| } |
| if (isConstant(V)) { |
| ReuseShuffleIndicies.emplace_back(UniqueValues.size()); |
| UniqueValues.emplace_back(V); |
| continue; |
| } |
| auto Res = UniquePositions.try_emplace(V, UniqueValues.size()); |
| ReuseShuffleIndicies.emplace_back(Res.first->second); |
| if (Res.second) { |
| UniqueValues.emplace_back(V); |
| ++UniqueVals; |
| } |
| } |
| if (UniqueVals == 1 && UniqueValues.size() == 1) { |
| // Emit pure splat vector. |
| ReuseShuffleIndicies.append(VF - ReuseShuffleIndicies.size(), |
| UndefMaskElem); |
| } else if (UniqueValues.size() >= VF - 1 || UniqueValues.size() <= 1) { |
| ReuseShuffleIndicies.clear(); |
| UniqueValues.clear(); |
| UniqueValues.append(VL.begin(), std::next(VL.begin(), NumValues)); |
| } |
| UniqueValues.append(VF - UniqueValues.size(), |
| PoisonValue::get(VL[0]->getType())); |
| VL = UniqueValues; |
| } |
| |
| ShuffleInstructionBuilder ShuffleBuilder(Builder, VF); |
| Value *Vec = gather(VL); |
| if (!ReuseShuffleIndicies.empty()) { |
| ShuffleBuilder.addMask(ReuseShuffleIndicies); |
| Vec = ShuffleBuilder.finalize(Vec); |
| if (auto *I = dyn_cast<Instruction>(Vec)) { |
| GatherShuffleSeq.insert(I); |
| CSEBlocks.insert(I->getParent()); |
| } |
| } |
| return Vec; |
| } |
| |
| 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; |
| } |
| |
| bool NeedToShuffleReuses = !E->ReuseShuffleIndices.empty(); |
| unsigned VF = E->getVectorFactor(); |
| ShuffleInstructionBuilder ShuffleBuilder(Builder, VF); |
| if (E->State == TreeEntry::NeedToGather) { |
| if (E->getMainOp()) |
| setInsertPointAfterBundle(E); |
| Value *Vec; |
| SmallVector<int> Mask; |
| SmallVector<const TreeEntry *> Entries; |
| Optional<TargetTransformInfo::ShuffleKind> Shuffle = |
| isGatherShuffledEntry(E, Mask, Entries); |
| if (Shuffle.hasValue()) { |
| assert((Entries.size() == 1 || Entries.size() == 2) && |
| "Expected shuffle of 1 or 2 entries."); |
| Vec = Builder.CreateShuffleVector(Entries.front()->VectorizedValue, |
| Entries.back()->VectorizedValue, Mask); |
| } else { |
| Vec = gather(E->Scalars); |
| } |
| if (NeedToShuffleReuses) { |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| Vec = ShuffleBuilder.finalize(Vec); |
| if (auto *I = dyn_cast<Instruction>(Vec)) { |
| GatherShuffleSeq.insert(I); |
| CSEBlocks.insert(I->getParent()); |
| } |
| } |
| E->VectorizedValue = Vec; |
| return Vec; |
| } |
| |
| assert((E->State == TreeEntry::Vectorize || |
| E->State == TreeEntry::ScatterVectorize) && |
| "Unhandled state"); |
| unsigned ShuffleOrOp = |
| E->isAltShuffle() ? (unsigned)Instruction::ShuffleVector : E->getOpcode(); |
| Instruction *VL0 = E->getMainOp(); |
| Type *ScalarTy = VL0->getType(); |
| if (auto *Store = dyn_cast<StoreInst>(VL0)) |
| ScalarTy = Store->getValueOperand()->getType(); |
| else if (auto *IE = dyn_cast<InsertElementInst>(VL0)) |
| ScalarTy = IE->getOperand(1)->getType(); |
| auto *VecTy = FixedVectorType::get(ScalarTy, E->Scalars.size()); |
| switch (ShuffleOrOp) { |
| case Instruction::PHI: { |
| assert( |
| (E->ReorderIndices.empty() || E != VectorizableTree.front().get()) && |
| "PHI reordering is free."); |
| auto *PH = cast<PHINode>(VL0); |
| Builder.SetInsertPoint(PH->getParent()->getFirstNonPHI()); |
| Builder.SetCurrentDebugLocation(PH->getDebugLoc()); |
| PHINode *NewPhi = Builder.CreatePHI(VecTy, PH->getNumIncomingValues()); |
| Value *V = NewPhi; |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| |
| 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: { |
| Value *V = E->getSingleOperand(0); |
| Builder.SetInsertPoint(VL0); |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| E->VectorizedValue = V; |
| return V; |
| } |
| case Instruction::ExtractValue: { |
| auto *LI = cast<LoadInst>(E->getSingleOperand(0)); |
| Builder.SetInsertPoint(LI); |
| auto *PtrTy = PointerType::get(VecTy, LI->getPointerAddressSpace()); |
| Value *Ptr = Builder.CreateBitCast(LI->getOperand(0), PtrTy); |
| LoadInst *V = Builder.CreateAlignedLoad(VecTy, Ptr, LI->getAlign()); |
| Value *NewV = propagateMetadata(V, E->Scalars); |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| NewV = ShuffleBuilder.finalize(NewV); |
| E->VectorizedValue = NewV; |
| return NewV; |
| } |
| case Instruction::InsertElement: { |
| assert(E->ReuseShuffleIndices.empty() && "All inserts should be unique"); |
| Builder.SetInsertPoint(cast<Instruction>(E->Scalars.back())); |
| Value *V = vectorizeTree(E->getOperand(1)); |
| |
| // Create InsertVector shuffle if necessary |
| auto *FirstInsert = cast<Instruction>(*find_if(E->Scalars, [E](Value *V) { |
| return !is_contained(E->Scalars, cast<Instruction>(V)->getOperand(0)); |
| })); |
| const unsigned NumElts = |
| cast<FixedVectorType>(FirstInsert->getType())->getNumElements(); |
| const unsigned NumScalars = E->Scalars.size(); |
| |
| unsigned Offset = *getInsertIndex(VL0, 0); |
| assert(Offset < NumElts && "Failed to find vector index offset"); |
| |
| // Create shuffle to resize vector |
| SmallVector<int> Mask; |
| if (!E->ReorderIndices.empty()) { |
| inversePermutation(E->ReorderIndices, Mask); |
| Mask.append(NumElts - NumScalars, UndefMaskElem); |
| } else { |
| Mask.assign(NumElts, UndefMaskElem); |
| std::iota(Mask.begin(), std::next(Mask.begin(), NumScalars), 0); |
| } |
| // Create InsertVector shuffle if necessary |
| bool IsIdentity = true; |
| SmallVector<int> PrevMask(NumElts, UndefMaskElem); |
| Mask.swap(PrevMask); |
| for (unsigned I = 0; I < NumScalars; ++I) { |
| Value *Scalar = E->Scalars[PrevMask[I]]; |
| Optional<int> InsertIdx = getInsertIndex(Scalar, 0); |
| if (!InsertIdx || *InsertIdx == UndefMaskElem) |
| continue; |
| IsIdentity &= *InsertIdx - Offset == I; |
| Mask[*InsertIdx - Offset] = I; |
| } |
| if (!IsIdentity || NumElts != NumScalars) |
| V = Builder.CreateShuffleVector(V, Mask); |
| |
| if ((!IsIdentity || Offset != 0 || |
| !isa<UndefValue>(FirstInsert->getOperand(0))) && |
| NumElts != NumScalars) { |
| SmallVector<int> InsertMask(NumElts); |
| std::iota(InsertMask.begin(), InsertMask.end(), 0); |
| for (unsigned I = 0; I < NumElts; I++) { |
| if (Mask[I] != UndefMaskElem) |
| InsertMask[Offset + I] = NumElts + I; |
| } |
| |
| V = Builder.CreateShuffleVector( |
| FirstInsert->getOperand(0), V, InsertMask, |
| cast<Instruction>(E->Scalars.back())->getName()); |
| } |
| |
| ++NumVectorInstructions; |
| E->VectorizedValue = V; |
| return V; |
| } |
| case Instruction::ZExt: |
| case Instruction::SExt: |
| case Instruction::FPToUI: |
| case Instruction::FPToSI: |
| case Instruction::FPExt: |
| case Instruction::PtrToInt: |
| case Instruction::IntToPtr: |
| case Instruction::SIToFP: |
| case Instruction::UIToFP: |
| case Instruction::Trunc: |
| case Instruction::FPTrunc: |
| case Instruction::BitCast: { |
| setInsertPointAfterBundle(E); |
| |
| Value *InVec = vectorizeTree(E->getOperand(0)); |
| |
| if (E->VectorizedValue) { |
| LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); |
| return E->VectorizedValue; |
| } |
| |
| auto *CI = cast<CastInst>(VL0); |
| Value *V = Builder.CreateCast(CI->getOpcode(), InVec, VecTy); |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| return V; |
| } |
| case Instruction::FCmp: |
| case Instruction::ICmp: { |
| setInsertPointAfterBundle(E); |
| |
| 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 = Builder.CreateCmp(P0, L, R); |
| propagateIRFlags(V, E->Scalars, VL0); |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| return V; |
| } |
| case Instruction::Select: { |
| setInsertPointAfterBundle(E); |
| |
| 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); |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| return V; |
| } |
| case Instruction::FNeg: { |
| setInsertPointAfterBundle(E); |
| |
| Value *Op = vectorizeTree(E->getOperand(0)); |
| |
| if (E->VectorizedValue) { |
| LLVM_DEBUG(dbgs() << "SLP: Diamond merged for " << *VL0 << ".\n"); |
| return E->VectorizedValue; |
| } |
| |
| Value *V = Builder.CreateUnOp( |
| static_cast<Instruction::UnaryOps>(E->getOpcode()), Op); |
| propagateIRFlags(V, E->Scalars, VL0); |
| if (auto *I = dyn_cast<Instruction>(V)) |
| V = propagateMetadata(I, E->Scalars); |
| |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| |
| return V; |
| } |
| case Instruction::Add: |
| case Instruction::FAdd: |
| case Instruction::Sub: |
| case Instruction::FSub: |
| case Instruction::Mul: |
| case Instruction::FMul: |
| case Instruction::UDiv: |
| case Instruction::SDiv: |
| case Instruction::FDiv: |
| case Instruction::URem: |
| case Instruction::SRem: |
| case Instruction::FRem: |
| case Instruction::Shl: |
| case Instruction::LShr: |
| case Instruction::AShr: |
| case Instruction::And: |
| case Instruction::Or: |
| case Instruction::Xor: { |
| setInsertPointAfterBundle(E); |
| |
| Value *LHS = 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>(E->getOpcode()), LHS, |
| RHS); |
| propagateIRFlags(V, E->Scalars, VL0); |
| if (auto *I = dyn_cast<Instruction>(V)) |
| V = propagateMetadata(I, E->Scalars); |
| |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| |
| return V; |
| } |
| case Instruction::Load: { |
| // Loads are inserted at the head of the tree because we don't want to |
| // sink them all the way down past store instructions. |
| setInsertPointAfterBundle(E); |
| |
| LoadInst *LI = cast<LoadInst>(VL0); |
| Instruction *NewLI; |
| unsigned AS = LI->getPointerAddressSpace(); |
| Value *PO = LI->getPointerOperand(); |
| if (E->State == TreeEntry::Vectorize) { |
| |
| Value *VecPtr = Builder.CreateBitCast(PO, VecTy->getPointerTo(AS)); |
| |
| // 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. |
| if (TreeEntry *Entry = getTreeEntry(PO)) { |
| // Find which lane we need to extract. |
| unsigned FoundLane = Entry->findLaneForValue(PO); |
| ExternalUses.emplace_back(PO, cast<User>(VecPtr), FoundLane); |
| } |
| |
| NewLI = Builder.CreateAlignedLoad(VecTy, VecPtr, LI->getAlign()); |
| } else { |
| assert(E->State == TreeEntry::ScatterVectorize && "Unhandled state"); |
| Value *VecPtr = vectorizeTree(E->getOperand(0)); |
| // Use the minimum alignment of the gathered loads. |
| Align CommonAlignment = LI->getAlign(); |
| for (Value *V : E->Scalars) |
| CommonAlignment = |
| commonAlignment(CommonAlignment, cast<LoadInst>(V)->getAlign()); |
| NewLI = Builder.CreateMaskedGather(VecTy, VecPtr, CommonAlignment); |
| } |
| Value *V = propagateMetadata(NewLI, E->Scalars); |
| |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| return V; |
| } |
| case Instruction::Store: { |
| auto *SI = cast<StoreInst>(VL0); |
| unsigned AS = SI->getPointerAddressSpace(); |
| |
| setInsertPointAfterBundle(E); |
| |
| Value *VecValue = vectorizeTree(E->getOperand(0)); |
| ShuffleBuilder.addMask(E->ReorderIndices); |
| VecValue = ShuffleBuilder.finalize(VecValue); |
| |
| Value *ScalarPtr = SI->getPointerOperand(); |
| Value *VecPtr = Builder.CreateBitCast( |
| ScalarPtr, VecValue->getType()->getPointerTo(AS)); |
| StoreInst *ST = Builder.CreateAlignedStore(VecValue, VecPtr, |
| SI->getAlign()); |
| |
| // The pointer operand uses an in-tree scalar, so add the new BitCast to |
| // ExternalUses to make sure that an extract will be generated in the |
| // future. |
| if (TreeEntry *Entry = getTreeEntry(ScalarPtr)) { |
| // Find which lane we need to extract. |
| unsigned FoundLane = Entry->findLaneForValue(ScalarPtr); |
| ExternalUses.push_back( |
| ExternalUser(ScalarPtr, cast<User>(VecPtr), FoundLane)); |
| } |
| |
| Value *V = propagateMetadata(ST, E->Scalars); |
| |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| return V; |
| } |
| case Instruction::GetElementPtr: { |
| auto *GEP0 = cast<GetElementPtrInst>(VL0); |
| setInsertPointAfterBundle(E); |
| |
| Value *Op0 = vectorizeTree(E->getOperand(0)); |
| |
| SmallVector<Value *> OpVecs; |
| for (int J = 1, N = GEP0->getNumOperands(); J < N; ++J) { |
| Value *OpVec = vectorizeTree(E->getOperand(J)); |
| OpVecs.push_back(OpVec); |
| } |
| |
| Value *V = Builder.CreateGEP(GEP0->getSourceElementType(), Op0, OpVecs); |
| if (Instruction *I = dyn_cast<Instruction>(V)) |
| V = propagateMetadata(I, E->Scalars); |
| |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| |
| return V; |
| } |
| case Instruction::Call: { |
| CallInst *CI = cast<CallInst>(VL0); |
| setInsertPointAfterBundle(E); |
| |
| Intrinsic::ID IID = Intrinsic::not_intrinsic; |
| if (Function *FI = CI->getCalledFunction()) |
| IID = FI->getIntrinsicID(); |
| |
| Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI); |
| |
| auto VecCallCosts = getVectorCallCosts(CI, VecTy, TTI, TLI); |
| bool UseIntrinsic = ID != Intrinsic::not_intrinsic && |
| VecCallCosts.first <= VecCallCosts.second; |
| |
| Value *ScalarArg = nullptr; |
| std::vector<Value *> OpVecs; |
| SmallVector<Type *, 2> TysForDecl = |
| {FixedVectorType::get(CI->getType(), E->Scalars.size())}; |
| for (int j = 0, e = CI->arg_size(); j < e; ++j) { |
| ValueList OpVL; |
| // Some intrinsics have scalar arguments. This argument should not be |
| // vectorized. |
| if (UseIntrinsic && hasVectorInstrinsicScalarOpd(IID, j)) { |
| CallInst *CEI = cast<CallInst>(VL0); |
| ScalarArg = CEI->getArgOperand(j); |
| OpVecs.push_back(CEI->getArgOperand(j)); |
| if (hasVectorInstrinsicOverloadedScalarOpd(IID, j)) |
| TysForDecl.push_back(ScalarArg->getType()); |
| continue; |
| } |
| |
| Value *OpVec = vectorizeTree(E->getOperand(j)); |
| LLVM_DEBUG(dbgs() << "SLP: OpVec[" << j << "]: " << *OpVec << "\n"); |
| OpVecs.push_back(OpVec); |
| } |
| |
| Function *CF; |
| if (!UseIntrinsic) { |
| VFShape Shape = |
| VFShape::get(*CI, ElementCount::getFixed(static_cast<unsigned>( |
| VecTy->getNumElements())), |
| false /*HasGlobalPred*/); |
| CF = VFDatabase(*CI).getVectorizedFunction(Shape); |
| } else { |
| CF = Intrinsic::getDeclaration(F->getParent(), ID, TysForDecl); |
| } |
| |
| SmallVector<OperandBundleDef, 1> OpBundles; |
| CI->getOperandBundlesAsDefs(OpBundles); |
| Value *V = Builder.CreateCall(CF, OpVecs, OpBundles); |
| |
| // The scalar argument uses an in-tree scalar so we add the new vectorized |
| // call to ExternalUses list to make sure that an extract will be |
| // generated in the future. |
| if (ScalarArg) { |
| if (TreeEntry *Entry = getTreeEntry(ScalarArg)) { |
| // Find which lane we need to extract. |
| unsigned FoundLane = Entry->findLaneForValue(ScalarArg); |
| ExternalUses.push_back( |
| ExternalUser(ScalarArg, cast<User>(V), FoundLane)); |
| } |
| } |
| |
| propagateIRFlags(V, E->Scalars, VL0); |
| ShuffleBuilder.addInversedMask(E->ReorderIndices); |
| ShuffleBuilder.addMask(E->ReuseShuffleIndices); |
| V = ShuffleBuilder.finalize(V); |
| |
| E->VectorizedValue = V; |
| ++NumVectorInstructions; |
| return V; |
| } |
| case Instruction::ShuffleVector: { |
| assert(E->isAltShuffle() && |
| ((Instruction::isBinaryOp(E->getOpcode()) && |
| Instruction::isBinaryOp(E->getAltOpcode())) || |
| (Instruction::isCast(E->getOpcode()) && |
| Instruction::isCast(E->getAltOpcode()))) && |
| "Invalid Shuffle Vector Operand"); |
| |
| Value *LHS = nullptr, *RHS = nullptr; |
| if (Instruction::isBinaryOp(E->getOpcode())) { |
| setInsertPointAfterBundle(E); |
| LHS = vectorizeTree(E->getOperand(0)); |
| RHS = vectorizeTree(E->getOperand(1)); |
| } else { |
| setInsertPointAfterBundle(E); |
| 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(E->getOpcode())) { |
| V0 = Builder.CreateBinOp( |
| static_cast<Instruction::BinaryOps>(E->getOpcode()), LHS, RHS); |
| V1 = Builder.CreateBinOp( |
| static_cast<Instruction::BinaryOps>(E->getAltOpcode()), LHS, RHS); |
| } else { |
| V0 = Builder.CreateCast( |
| static_cast<Instruction::CastOps>(E->getOpcode()), LHS, VecTy); |
| V1 = Builder.CreateCast( |
| static_cast<Instruction::CastOps>(E->getAltOpcode()), LHS, VecTy); |
| } |
| // Add V0 and V1 to later analysis to try to find and remove matching |
| // instruction, if any. |
| for (Value *V : {V0, V1}) { |
| if (auto *I = dyn_cast<Instruction>(V)) { |
| GatherShuffleSeq.insert(I); |
| CSEBlocks.insert(I->getParent()); |
| } |
| } |
| |
| // Create shuffle to take alternate operations from the vector. |
| // Also, gather up main and alt scalar ops to propagate IR flags to |
| // each vector operation. |
| ValueList OpScalars, AltScalars; |
| SmallVector<int> Mask; |
| buildSuffleEntryMask( |
| E->Scalars, E->ReorderIndices, E->ReuseShuffleIndices, |
| [E](Instruction *I) { |
| assert(E->isOpcodeOrAlt(I) && "Unexpected main/alternate opcode"); |
| return I->getOpcode() == E->getAltOpcode(); |
| }, |
| Mask, &OpScalars, &AltScalars); |
| |
| propagateIRFlags(V0, OpScalars); |
| propagateIRFlags(V1, AltScalars); |
| |
| Value *V = Builder.CreateShuffleVector(V0, V1, Mask); |
| if (Instruction *I = dyn_cast<Instruction>(V)) |
| V = propagateMetadata(I, E->Scalars); |
| V = ShuffleBuilder.finalize(V); |
| |
| 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].get()); |
| |
| // If the vectorized tree can be rewritten in a smaller type, we truncate the |
| // vectorized root. InstCombine will then rewrite the entire expression. We |
| // sign extend the extracted values below. |
| auto *ScalarRoot = VectorizableTree[0]->Scalars[0]; |
| if (MinBWs.count(ScalarRoot)) { |
| if (auto *I = dyn_cast<Instruction>(VectorRoot)) { |
| // If current instr is a phi and not the last phi, insert it after the |
| // last phi node. |
| if (isa<PHINode>(I)) |
| Builder.SetInsertPoint(&*I->getParent()->getFirstInsertionPt()); |
| else |
| Builder.SetInsertPoint(&*++BasicBlock::iterator(I)); |
| } |
| auto BundleWidth = VectorizableTree[0]->Scalars.size(); |
| auto *MinTy = IntegerType::get(F->getContext(), MinBWs[ScalarRoot].first); |
| auto *VecTy = FixedVectorType::get(MinTy, BundleWidth); |
| auto *Trunc = Builder.CreateTrunc(VectorRoot, VecTy); |
| VectorizableTree[0]->VectorizedValue = Trunc; |
| } |
| |
| LLVM_DEBUG(dbgs() << "SLP: Extracting " << ExternalUses.size() |
| << " values .\n"); |
| |
| // Extract all of the elements with the external uses. |
| for (const auto &ExternalUse : ExternalUses) { |
| Value *Scalar = ExternalUse.Scalar; |
| llvm::User *User = ExternalUse.User; |
| |
| // Skip users that we already RAUW. This happens when one instruction |
| // has multiple uses of the same value. |
| if (User && !is_contained(Scalar->users(), User)) |
| continue; |
| TreeEntry *E = getTreeEntry(Scalar); |
| assert(E && "Invalid scalar"); |
| assert(E->State != TreeEntry::NeedToGather && |
| "Extracting from a gather list"); |
| |
| Value *Vec = E->VectorizedValue; |
| assert(Vec && "Can't find vectorizable value"); |
| |
| Value *Lane = Builder.getInt32(ExternalUse.Lane); |
| auto ExtractAndExtendIfNeeded = [&](Value *Vec) { |
| if (Scalar->getType() != Vec->getType()) { |
| Value *Ex; |
| // "Reuse" the existing extract to improve final codegen. |
| if (auto *ES = dyn_cast<ExtractElementInst>(Scalar)) { |
| Ex = Builder.CreateExtractElement(ES->getOperand(0), |
| ES->getOperand(1)); |
| } else { |
| Ex = Builder.CreateExtractElement(Vec, Lane); |
| } |
| // If necessary, sign-extend or zero-extend ScalarRoot |
| // to the larger type. |
| if (!MinBWs.count(ScalarRoot)) |
| return Ex; |
| if (MinBWs[ScalarRoot].second) |
| return Builder.CreateSExt(Ex, Scalar->getType()); |
| return Builder.CreateZExt(Ex, Scalar->getType()); |
| } |
| assert(isa<FixedVectorType>(Scalar->getType()) && |
| isa<InsertElementInst>(Scalar) && |
| "In-tree scalar of vector type is not insertelement?"); |
| return Vec; |
| }; |
| // If User == nullptr, the Scalar is used as extra arg. Generate |
| // ExtractElement instruction and update the record for this scalar in |
| // ExternallyUsedValues. |
| if (!User) { |
| assert(ExternallyUsedValues.count(Scalar) && |
| "Scalar with nullptr as an external user must be registered in " |
| "ExternallyUsedValues map"); |
| if (auto *VecI = dyn_cast<Instruction>(Vec)) { |
| Builder.SetInsertPoint(VecI->getParent(), |
| std::next(VecI->getIterator())); |
| } else { |
| Builder.SetInsertPoint(&F->getEntryBlock().front()); |
| } |
| Value *NewInst = ExtractAndExtendIfNeeded(Vec); |
| CSEBlocks.insert(cast<Instruction>(Scalar)->getParent()); |
| auto &NewInstLocs = ExternallyUsedValues[NewInst]; |
| auto It = ExternallyUsedValues.find(Scalar); |
| assert(It != ExternallyUsedValues.end() && |
| "Externally used scalar is not found in ExternallyUsedValues"); |
| NewInstLocs.append(It->second); |
| ExternallyUsedValues.erase(Scalar); |
| // Required to update internally referenced instructions. |
| Scalar->replaceAllUsesWith(NewInst); |
| continue; |
| } |
| |
| // Generate extracts for out-of-tree users. |
| // Find the insertion point for the extractelement lane. |
| if (auto *VecI = dyn_cast<Instruction>(Vec)) { |
| if (PHINode *PH = dyn_cast<PHINode>(User)) { |
| for (int i = 0, e = PH->getNumIncomingValues(); i != e; ++i) { |
| if (PH->getIncomingValue(i) == Scalar) { |
| Instruction *IncomingTerminator = |
| PH->getIncomingBlock(i)->getTerminator(); |
| if (isa<CatchSwitchInst>(IncomingTerminator)) { |
| Builder.SetInsertPoint(VecI->getParent(), |
| std::next(VecI->getIterator())); |
| } else { |
| Builder.SetInsertPoint(PH->getIncomingBlock(i)->getTerminator()); |
| } |
| Value *NewInst = ExtractAndExtendIfNeeded(Vec); |
| CSEBlocks.insert(PH->getIncomingBlock(i)); |
| PH->setOperand(i, NewInst); |
| } |
| } |
| } else { |
| Builder.SetInsertPoint(cast<Instruction>(User)); |
| Value *NewInst = ExtractAndExtendIfNeeded(Vec); |
| CSEBlocks.insert(cast<Instruction>(User)->getParent()); |
| User->replaceUsesOfWith(Scalar, NewInst); |
| } |
| } else { |
| Builder.SetInsertPoint(&F->getEntryBlock().front()); |
| Value *NewInst = ExtractAndExtendIfNeeded(Vec); |
| CSEBlocks.insert(&F->getEntryBlock()); |
| User->replaceUsesOfWith(Scalar, NewInst); |
| } |
| |
| LLVM_DEBUG(dbgs() << "SLP: Replaced:" << *User << ".\n"); |
| } |
| |
| // For each vectorized value: |
| for (auto &TEPtr : VectorizableTree) { |
| TreeEntry *Entry = TEPtr.get(); |
| |
| // No need to handle users of gathered values. |
| if (Entry->State == TreeEntry::NeedToGather) |
| continue; |
| |
| assert(Entry->VectorizedValue && "Can't find vectorizable value"); |
| |
| // For each lane: |
| for (int Lane = 0, LE = Entry->Scalars.size(); Lane != LE; ++Lane) { |
| Value *Scalar = Entry->Scalars[Lane]; |
| |
| #ifndef NDEBUG |
| Type *Ty = Scalar->getType(); |
| if (!Ty->isVoidTy()) { |
| for (User *U : Scalar->users()) { |
| LLVM_DEBUG(dbgs() << "SLP: \tvalidating user:" << *U << ".\n"); |
| |
| // It is legal to delete users in the ignorelist. |
| assert((getTreeEntry(U) || is_contained(UserIgnoreList, U) || |
| (isa_and_nonnull<Instruction>(U) && |
| isDeleted(cast<Instruction>(U)))) && |
| "Deleting out-of-tree value"); |
| } |
| } |
| #endif |
| LLVM_DEBUG(dbgs() << "SLP: \tErasing scalar:" << *Scalar << ".\n"); |
| eraseInstruction(cast<Instruction>(Scalar)); |
| } |
| } |
| |
| Builder.ClearInsertionPoint(); |
| InstrElementSize.clear(); |
| |
| return VectorizableTree[0]->VectorizedValue; |
| } |
| |
| void BoUpSLP::optimizeGatherSequence() { |
| LLVM_DEBUG(dbgs() << "SLP: Optimizing " << GatherShuffleSeq.size() |
| << " gather sequences instructions.\n"); |
| // LICM InsertElementInst sequences. |
| for (Instruction *I : GatherShuffleSeq) { |
| if (isDeleted(I)) |
| continue; |
| |
| // Check if this block is inside a loop. |
| Loop *L = LI->getLoopFor(I->getParent()); |
| if (!L) |
| continue; |
| |
| // Check if it has a preheader. |
| BasicBlock *PreHeader = L->getLoopPreheader(); |
| if (!PreHeader) |
| continue; |
| |
| // If the vector or the element that we insert into it are |
| // instructions that are defined in this basic block then we can't |
| // hoist this instruction. |
| if (any_of(I->operands(), [L](Value *V) { |
| auto *OpI = dyn_cast<Instruction>(V); |
| return OpI && L->contains(OpI); |
| })) |
| continue; |
| |
| // We can hoist this instruction. Move it to the pre-header. |
| I->moveBefore(PreHeader->getTerminator()); |
| } |
| |
| // Make a list of all reachable blocks in our CSE queue. |
| SmallVector<const DomTreeNode *, 8> CSEWorkList; |
| CSEWorkList.reserve(CSEBlocks.size()); |
| for (BasicBlock *BB : CSEBlocks) |
| if (DomTreeNode *N = DT->getNode(BB)) { |
| assert(DT->isReachableFromEntry(N)); |
| CSEWorkList.push_back(N); |
| } |
| |
| // Sort blocks by domination. This ensures we visit a block after all blocks |
| // dominating it are visited. |
| llvm::sort(CSEWorkList, [](const DomTreeNode *A, const DomTreeNode *B) { |
| assert((A == B) == (A->getDFSNumIn() == B->getDFSNumIn()) && |
| "Different nodes should have different DFS numbers"); |
| return A->getDFSNumIn() < B->getDFSNumIn(); |
| }); |
| |
| // 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 && |
| (I == CSEWorkList.begin() || !DT->dominates(*I, *std::prev(I))) && |
| "Worklist not sorted properly!"); |
| BasicBlock *BB = (*I)->getBlock(); |
| // For all instructions in blocks containing gather sequences: |
| for (Instruction &In : llvm::make_early_inc_range(*BB)) { |
| if (isDeleted(&In)) |
| continue; |
| if (!isa<InsertElementInst>(&In) && !isa<ExtractElementInst>(&In) && |
| !isa<ShuffleVectorInst>(&In) && !GatherShuffleSeq.contains(&In)) |
| continue; |
| |
| // Check if we can replace this instruction with any of the |
| // visited instructions. |
| bool Replaced = false; |
| for (Instruction *v : Visited) { |
| if (In.isIdenticalTo(v) && |
| DT->dominates(v->getParent(), In.getParent())) { |
| In.replaceAllUsesWith(v); |
| eraseInstruction(&In); |
| Replaced = true; |
| break; |
| } |
| } |
| if (!Replaced) { |
| assert(!is_contained(Visited, &In)); |
| Visited.push_back(&In); |
| } |
| } |
| } |
| CSEBlocks.clear(); |
| GatherShuffleSeq.clear(); |
| } |
| |
| // Groups the instructions to a bundle (which is then a single scheduling entity) |
| // and schedules instructions until the bundle gets ready. |
| Optional<BoUpSLP::ScheduleData *> |
| BoUpSLP::BlockScheduling::tryScheduleBundle(ArrayRef<Value *> VL, BoUpSLP *SLP, |
| const InstructionsState &S) { |
| // No need to schedule PHIs, insertelement, extractelement and extractvalue |
| // instructions. |
| if (isa<PHINode>(S.OpValue) || isVectorLikeInstWithConstOps(S.OpValue)) |
| return nullptr; |
| |
| // Initialize the instruction bundle. |
| Instruction *OldScheduleEnd = ScheduleEnd; |
| ScheduleData *PrevInBundle = nullptr; |
| ScheduleData *Bundle = nullptr; |
| bool ReSchedule = false; |
| LLVM_DEBUG(dbgs() << "SLP: bundle: " << *S.OpValue << "\n"); |
| |
| auto &&TryScheduleBundle = [this, OldScheduleEnd, SLP](bool ReSchedule, |
| ScheduleData *Bundle) { |
| // The scheduling region got new instructions at the lower end (or it is a |
| // new region for the first bundle). This makes it necessary to |
| // recalculate all dependencies. |
| // It is seldom that this needs to be done a second time after adding the |
| // initial bundle to the region. |
| if (ScheduleEnd != OldScheduleEnd) { |
| for (auto *I = ScheduleStart; I != ScheduleEnd; I = I->getNextNode()) |
| doForAllOpcodes(I, [](ScheduleData *SD) { SD->clearDependencies(); }); |
| ReSchedule = true; |
| } |
| if (ReSchedule) { |
| resetSchedule(); |
| initialFillReadyList(ReadyInsts); |
| } |
| if (Bundle) { |
| LLVM_DEBUG(dbgs() << "SLP: try schedule bundle " << *Bundle |
| << " in block " << BB->getName() << "\n"); |
| calculateDependencies(Bundle, /*InsertInReadyList=*/true, SLP); |
| } |
| |
| // Now try to schedule the new bundle or (if no bundle) just calculate |
| // dependencies. As soon as the bundle is "ready" it means that there are no |
| // cyclic dependencies and we can schedule it. Note that's important that we |
| // don't "schedule" the bundle yet (see cancelScheduling). |
| while (((!Bundle && ReSchedule) || (Bundle && !Bundle->isReady())) && |
| !ReadyInsts.empty()) { |
| ScheduleData *Picked = ReadyInsts.pop_back_val(); |
| if (Picked->isSchedulingEntity() && Picked->isReady()) |
| schedule(Picked, ReadyInsts); |
| } |
| }; |
| |
| // Make sure that the scheduling region contains all |
| // instructions of the bundle. |
| for (Value *V : VL) { |
| if (!extendSchedulingRegion(V, S)) { |
| // If the scheduling region got new instructions at the lower end (or it |
| // is a new region for the first bundle). This makes it necessary to |
| // recalculate all dependencies. |
| // Otherwise the compiler may crash trying to incorrectly calculate |
| // dependencies and emit instruction in the wrong order at the actual |
| // scheduling. |
| TryScheduleBundle(/*ReSchedule=*/false, nullptr); |
| return None; |
| } |
| } |
| |
| 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; |
| } |
| assert(Bundle && "Failed to find schedule bundle"); |
| TryScheduleBundle(ReSchedule, Bundle); |
| if (!Bundle->isReady()) { |
| cancelScheduling(VL, S.OpValue); |
| return None; |
| } |
| return Bundle; |
| } |
| |
| void BoUpSLP::BlockScheduling::cancelScheduling(ArrayRef<Value *> VL, |
| Value *OpValue) { |
| if (isa<PHINode>(OpValue) || isVectorLikeInstWithConstOps(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(std::make_unique<ScheduleData[]>(ChunkSize)); |
| ChunkPos = 0; |
| } |
| return &(ScheduleDataChunks.back()[ChunkPos++]); |
| } |
| |
| bool BoUpSLP::BlockScheduling::extendSchedulingRegion(Value *V, |
| const InstructionsState &S) { |
| if (getScheduleData(V, isOneOf(S, V))) |
| return true; |
| Instruction *I = dyn_cast<Instruction>(V); |
| assert(I && "bundle member must be an instruction"); |
| assert(!isa<PHINode>(I) && !isVectorLikeInstWithConstOps(I) && |
| "phi nodes/insertelements/extractelements/extractvalues 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 (UpIter != UpperEnd && DownIter != LowerEnd && &*UpIter != I && |
| &*DownIter != I) { |
| if (++ScheduleRegionSize > ScheduleRegionSizeLimit) { |
| LLVM_DEBUG(dbgs() << "SLP: exceeded schedule region size limit\n"); |
| return false; |
| } |
| |
| ++UpIter; |
| ++DownIter; |
| } |
| if (DownIter == LowerEnd || (UpIter != UpperEnd && &*UpIter == I)) { |
| assert(I->getParent() == ScheduleStart->getParent() && |
| "Instruction is in wrong basic block."); |
| initScheduleData(I, ScheduleStart, nullptr, FirstLoadStoreInRegion); |
| ScheduleStart = I; |
| if (isOneOf(S, I) != I) |
| CheckSheduleForI(I); |
| LLVM_DEBUG(dbgs() << "SLP: extend schedule region start to " << *I |
| << "\n"); |
| return true; |
| } |
| assert((UpIter == UpperEnd || (DownIter != LowerEnd && &*DownIter == I)) && |
| "Expected to reach top of the basic block or instruction down the " |
| "lower end."); |
| assert(I->getParent() == ScheduleEnd->getParent() && |
| "Instruction is in wrong basic block."); |
| initScheduleData(ScheduleEnd, I->getNextNode(), LastLoadStoreInRegion, |
| nullptr); |
| ScheduleEnd = I->getNextNode(); |
| if (isOneOf(S, I) != I) |
| CheckSheduleForI(I); |
| assert(ScheduleEnd && "tried to vectorize a terminator?"); |
| LLVM_DEBUG(dbgs() << "SLP: extend schedule region end to " << *I << "\n"); |
| return true; |
| } |
| |
| void BoUpSLP::BlockScheduling::initScheduleData(Instruction *FromI, |
| Instruction *ToI, |
| ScheduleData *PrevLoadStore, |
| ScheduleData *NextLoadStore) { |
| ScheduleData *CurrentLoadStore = PrevLoadStore; |
| for (Instruction *I = FromI; I != ToI; I = I->getNextNode()) { |
| 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 && |
| cast<IntrinsicInst>(I)->getIntrinsicID() != |
| Intrinsic::pseudoprobe))) { |
| // Update the linked list of memory accessing instructions. |
| if (CurrentLoadStore) { |
| CurrentLoadStore->NextLoadStore = SD; |
| } else { |
| FirstLoadStoreInRegion = SD; |
| } |
| CurrentLoadStore = SD; |
| } |
| } |
| if (NextLoadStore) { |
| if (CurrentLoadStore) |
| CurrentLoadStore->NextLoadStore = NextLoadStore; |
| } else { |
| LastLoadStoreInRegion = CurrentLoadStore; |
| } |
| } |
| |
| void BoUpSLP::BlockScheduling::calculateDependencies(ScheduleData *SD, |
| bool InsertInReadyList, |
| BoUpSLP *SLP) { |
| assert(SD->isSchedulingEntity()); |
| |
| SmallVector<ScheduleData *, 10> WorkList; |
| WorkList.push_back(SD); |
| |
| while (!WorkList.empty()) { |
| ScheduleData *SD = WorkList.pop_back_val(); |
| |
| 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((isVectorLikeInstWithConstOps(SD->Inst) || |
| 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 (pickedInst->getNextNode() != LastScheduledInst) { |
| 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 (or value |
| // truncated just before storing) without traversing the expression tree. |
| // This is the common case. |
| if (auto *Store = dyn_cast<StoreInst>(V)) { |
| if (auto *Trunc = dyn_cast<TruncInst>(Store->getValueOperand())) |
| return DL->getTypeSizeInBits(Trunc->getSrcTy()); |
| return DL->getTypeSizeInBits(Store->getValueOperand()->getType()); |
| } |
| |
| if (auto *IEI = dyn_cast<InsertElementInst>(V)) |
| return getVectorElementSize(IEI->getOperand(1)); |
| |
| auto E = InstrElementSize.find(V); |
| if (E != InstrElementSize.end()) |
| return E->second; |
| |
| // If V is not a store, we can traverse the expression tree to find loads |
| // that feed it. The type of the loaded value may indicate a more suitable |
| // width than V's type. We want to base the vector element size on the width |
| // of memory operations where possible. |
| SmallVector<std::pair<Instruction *, BasicBlock *>, 16> Worklist; |
| SmallPtrSet<Instruction *, 16> Visited; |
| if (auto *I = dyn_cast<Instruction>(V)) { |
| Worklist.emplace_back(I, I->getParent()); |
| Visited.insert(I); |
| } |
| |
| // Traverse the expression tree in bottom-up order looking for loads. If we |
| // encounter an instruction we don't yet handle, we give up. |
| auto Width = 0u; |
| while (!Worklist.empty()) { |
| Instruction *I; |
| BasicBlock *Parent; |
| std::tie(I, Parent) = Worklist.pop_back_val(); |
| |
| // We should only be looking at scalar instructions here. If the current |
| // instruction has a vector type, skip. |
| auto *Ty = I->getType(); |
| if (isa<VectorType>(Ty)) |
| continue; |
| |
| // If the current instruction is a load, update MaxWidth to reflect the |
| // width of the loaded value. |
| if (isa<LoadInst>(I) || isa<ExtractElementInst>(I) || |
| isa<ExtractValueInst>(I)) |
| Width = std::max<unsigned>(Width, DL->getTypeSizeInBits(Ty)); |
| |
| // Otherwise, we need to visit the operands of the instruction. We only |
| // handle the interesting cases from buildTree here. If an operand is an |
| // instruction we haven't yet visited and from the same basic block as the |
| // user or the use is a PHI node, we add it to the worklist. |
| else if (isa<PHINode>(I) || isa<CastInst>(I) || isa<GetElementPtrInst>(I) || |
| isa<CmpInst>(I) || isa<SelectInst>(I) || isa<BinaryOperator>(I) || |
| isa<UnaryOperator>(I)) { |
| for (Use &U : I->operands()) |
| if (auto *J = dyn_cast<Instruction>(U.get())) |
| if (Visited.insert(J).second && |
| (isa<PHINode>(I) || J->getParent() == Parent)) |
| Worklist.emplace_back(J, J->getParent()); |
| } else { |
| break; |
| } |
| } |
| |
| // If we didn't encounter a memory access in the expression tree, or if we |
| // gave up for some reason, just return the width of V. Otherwise, return the |
| // maximum width we found. |
| if (!Width) { |
| if (auto *CI = dyn_cast<CmpInst>(V)) |
| V = CI->getOperand(0); |
| Width = DL->getTypeSizeInBits(V->getType()); |
| } |
| |
| for (Instruction *I : Visited) |
| InstrElementSize[I] = Width; |
| |
| return Width; |
| } |
| |
| // Determine if a value V in a vectorizable expression Expr can be demoted to a |
| // smaller type with a truncation. We collect the values that will be demoted |
| // in ToDemote and additional roots that require investigating in Roots. |
| static bool collectValuesToDemote(Value *V, SmallPtrSetImpl<Value *> &Expr, |
| SmallVectorImpl<Value *> &ToDemote, |
| SmallVectorImpl<Value *> &Roots) { |
| // We can always demote constants. |
| if (isa<Constant>(V)) { |
| ToDemote.push_back(V); |
| return true; |
| } |
| |
| // If the value is not an instruction in the expression with only one use, it |
| // cannot be demoted. |
| auto *I = dyn_cast<Instruction>(V); |
| if (!I || !I->hasOneUse() || !Expr.count(I)) |
| return false; |
| |
| switch (I->getOpcode()) { |
| |
| // We can always demote truncations and extensions. Since truncations can |
| // seed additional demotion, we save the truncated value. |
| case Instruction::Trunc: |
| Roots.push_back(I->getOperand(0)); |
| break; |
| case Instruction::ZExt: |
| case Instruction::SExt: |
| if (isa<ExtractElementInst>(I->getOperand(0)) || |
| isa<InsertElementInst>(I->getOperand(0))) |
| return false; |
| break; |
| |
| // We can demote certain binary operations if we can demote both of their |
| // operands. |
| case Instruction::Add: |
| case Instruction::Sub: |
| case Instruction::Mul: |
| case Instruction::And: |
| case Instruction::Or: |
| case Instruction::Xor: |
| if (!collectValuesToDemote(I->getOperand(0), Expr, ToDemote, Roots) || |
| !collectValuesToDemote(I->getOperand(1), Expr, ToDemote, Roots)) |
| return false; |
| break; |
| |
| // We can demote selects if we can demote their true and false values. |
| case Instruction::Select: { |
| SelectInst *SI = cast<SelectInst>(I); |
| if (!collectValuesToDemote(SI->getTrueValue(), Expr, ToDemote, Roots) || |
| !collectValuesToDemote(SI->getFalseValue(), Expr, ToDemote, Roots)) |
| return false; |
| break; |
| } |
| |
| // We can demote phis if we can demote all their incoming operands. Note that |
| // we don't need to worry about cycles since we ensure single use above. |
| case Instruction::PHI: { |
| PHINode *PN = cast<PHINode>(I); |
| for (Value *IncValue : PN->incoming_values()) |
| if (!collectValuesToDemote(IncValue, Expr, ToDemote, Roots)) |
| return false; |
| break; |
| } |
| |
| // Otherwise, conservatively give up. |
| default: |
| return false; |
| } |
| |
| // Record the value that we can demote. |
| ToDemote.push_back(V); |
| return true; |
| } |
| |
| void BoUpSLP::computeMinimumValueSizes() { |
| // If there are no external uses, the expression tree must be rooted by a |
| // store. We can't demote in-memory values, so there is nothing to do here. |
| if (ExternalUses.empty()) |
| return; |
| |
| // We only attempt to truncate integer expressions. |
| auto &TreeRoot = VectorizableTree[0]->Scalars; |
| auto *TreeRootIT = dyn_cast<IntegerType>(TreeRoot[0]->getType()); |
| if (!TreeRootIT) |
| return; |
| |
| // If the expression is not rooted by a store, these roots should have |
| // external uses. We will rely on InstCombine to rewrite the expression in |
| // the narrower type. However, InstCombine only rewrites single-use values. |
| // This means that if a tree entry other than a root is used externally, it |
| // must have multiple uses and InstCombine will not rewrite it. The code |
| // below ensures that only the roots are used externally. |
| SmallPtrSet<Value *, 32> Expr(TreeRoot.begin(), TreeRoot.end()); |
| for (auto &EU : ExternalUses) |
| if (!Expr.erase(EU.Scalar)) |
| return; |
| if (!Expr.empty()) |
| return; |
| |
| // Collect the scalar values of the vectorizable expression. We will use this |
| // context to determine which values can be demoted. If we see a truncation, |
| // we mark it as seeding another demotion. |
| for (auto &EntryPtr : VectorizableTree) |
| Expr.insert(EntryPtr->Scalars.begin(), EntryPtr->Scalars.end()); |
| |
| // Ensure the roots of the vectorizable tree don't form a cycle. They must |
| // have a single external user that is not in the vectorizable tree. |
| for (auto *Root : TreeRoot) |
| if (!Root->hasOneUse() || Expr.count(*Root->user_begin())) |
| return; |
| |
| // Conservatively determine if we can actually truncate the roots of the |
| // expression. Collect the values that can be demoted in ToDemote and |
| // additional roots that require investigating in Roots. |
| SmallVector<Value *, 32> ToDemote; |
| SmallVector<Value *, 4> Roots; |
| for (auto *Root : TreeRoot) |
| if (!collectValuesToDemote(Root, Expr, ToDemote, Roots)) |
| return; |
| |
| // The maximum bit width required to represent all the values that can be |
| // demoted without loss of precision. It would be safe to truncate the roots |
| // of the expression to this width. |
| auto MaxBitWidth = 8u; |
| |
| // We first check if all the bits of the roots are demanded. If they're not, |
| // we can truncate the roots to this narrower type. |
| for (auto *Root : TreeRoot) { |
| auto Mask = DB->getDemandedBits(cast<Instruction>(Root)); |
| MaxBitWidth = std::max<unsigned>( |
| Mask.getBitWidth() - Mask.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(F) : 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.addRequired<InjectTLIMappingsLegacy>(); |
| 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>(); |
| return PA; |
| } |
| |
| bool SLPVectorizerPass::runImpl(Function &F, ScalarEvolution *SE_, |
| TargetTransformInfo *TTI_, |
| TargetLibraryInfo *TLI_, AAResults *AA_, |
| LoopInfo *LI_, DominatorTree *DT_, |
| AssumptionCache *AC_, DemandedBits *DB_, |
| OptimizationRemarkEmitter *ORE_) { |
| if (!RunSLPVectorization) |
| return false; |
| SE = SE_; |
| TTI = TTI_; |
| TLI = TLI_; |
| AA = AA_; |
| LI = LI_; |
| DT = DT_; |
| AC = AC_; |
| DB = DB_; |
| DL = &F.getParent()->getDataLayout(); |
| |
| Stores.clear(); |
| GEPs.clear(); |
| bool Changed = false; |
| |
| // If the target claims to have no vector registers don't attempt |
| // vectorization. |
| if (!TTI->getNumberOfRegisters(TTI->getRegisterClassForType(true))) |
| return false; |
| |
| // Don't vectorize when the attribute NoImplicitFloat is used. |
| if (F.hasFnAttribute(Attribute::NoImplicitFloat)) |
| return false; |
| |
| LLVM_DEBUG(dbgs() << "SLP: Analyzing blocks in " << F.getName() << ".\n"); |
| |
| // Use the bottom up slp vectorizer to construct chains that start with |
| // store instructions. |
| BoUpSLP R(&F, SE, TTI, TLI, AA, LI, DT, AC, DB, DL, ORE_); |
| |
| // A general note: the vectorizer must use BoUpSLP::eraseInstruction() to |
| // delete instructions. |
| |
| // Update DFS numbers now so that we can use them for ordering. |
| DT->updateDFSNumbers(); |
| |
| // Scan the blocks in the function in post order. |
| for (auto BB : post_order(&F.getEntryBlock())) { |
| collectSeedInstructions(BB); |
| |
| // Vectorize trees that end at stores. |
| if (!Stores.empty()) { |
| LLVM_DEBUG(dbgs() << "SLP: Found stores for " << Stores.size() |
| << " underlying objects.\n"); |
| Changed |= vectorizeStoreChains(R); |
| } |
| |
| // Vectorize trees that end at reductions. |
| Changed |= vectorizeChainsInBlock(BB, R); |
| |
| // Vectorize the index computations of getelementptr instructions. This |
| // is primarily intended to catch gather-like idioms ending at |
| // non-consecutive loads. |
| if (!GEPs.empty()) { |
| LLVM_DEBUG(dbgs() << "SLP: Found GEPs for " << GEPs.size() |
| << " underlying objects.\n"); |
| Changed |= vectorizeGEPIndices(BB, R); |
| } |
| } |
| |
| if (Changed) { |
| R.optimizeGatherSequence(); |
| LLVM_DEBUG(dbgs() << "SLP: vectorized \"" << F.getName() << "\"\n"); |
| } |
| return Changed; |
| } |
| |
| bool SLPVectorizerPass::vectorizeStoreChain(ArrayRef<Value *> Chain, BoUpSLP &R, |
| unsigned Idx) { |
| LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " << Chain.size() |
| << "\n"); |
| const unsigned Sz = R.getVectorElementSize(Chain[0]); |
| const unsigned MinVF = R.getMinVecRegSize() / Sz; |
| unsigned VF = Chain.size(); |
| |
| if (!isPowerOf2_32(Sz) || !isPowerOf2_32(VF) || VF < 2 || VF < MinVF) |
| return false; |
| |
| LLVM_DEBUG(dbgs() << "SLP: Analyzing " << VF << " stores at offset " << Idx |
| << "\n"); |
| |
| R.buildTree(Chain); |
| if (R.isTreeTinyAndNotFullyVectorizable()) |
| return false; |
| if (R.isLoadCombineCandidate()) |
| return false; |
| R.reorderTopToBottom(); |
| R.reorderBottomToTop(); |
| R.buildExternalUses(); |
| |
| R.computeMinimumValueSizes(); |
| |
| InstructionCost Cost = R.getTreeCost(); |
| |
| LLVM_DEBUG(dbgs() << "SLP: Found cost = " << Cost << " for VF =" << VF << "\n"); |
| if (Cost < -SLPCostThreshold) { |
| LLVM_DEBUG(dbgs() << "SLP: Decided to vectorize cost = " << Cost << "\n"); |
| |
| using namespace ore; |
| |
| R.getORE()->emit(OptimizationRemark(SV_NAME, "StoresVectorized", |
| cast<StoreInst>(Chain[0])) |
| << "Stores SLP vectorized with cost " << NV("Cost", Cost) |
| << " and with tree size " |
| << NV("TreeSize", R.getTreeSize())); |
| |
| R.vectorizeTree(); |
| return true; |
| } |
| |
| return false; |
| } |
| |
| bool SLPVectorizerPass::vectorizeStores(ArrayRef<StoreInst *> Stores, |
| BoUpSLP &R) { |
| // We may run into multiple chains that merge into a single chain. We mark the |
| // stores that we vectorized so that we don't visit the same store twice. |
| BoUpSLP::ValueSet VectorizedStores; |
| bool Changed = false; |
| |
| int E = Stores.size(); |
| SmallBitVector Tails(E, false); |
| int MaxIter = MaxStoreLookup.getValue(); |
| SmallVector<std::pair<int, int>, 16> ConsecutiveChain( |
| E, std::make_pair(E, INT_MAX)); |
| SmallVector<SmallBitVector, 4> CheckedPairs(E, SmallBitVector(E, false)); |
| int IterCnt; |
| auto &&FindConsecutiveAccess = [this, &Stores, &Tails, &IterCnt, MaxIter, |
| &CheckedPairs, |
| &ConsecutiveChain](int K, int Idx) { |
| if (IterCnt >= MaxIter) |
| return true; |
| if (CheckedPairs[Idx].test(K)) |
| return ConsecutiveChain[K].second == 1 && |
| ConsecutiveChain[K].first == Idx; |
| ++IterCnt; |
| CheckedPairs[Idx].set(K); |
| CheckedPairs[K].set(Idx); |
| Optional<int> Diff = getPointersDiff( |
| Stores[K]->getValueOperand()->getType(), Stores[K]->getPointerOperand(), |
| Stores[Idx]->getValueOperand()->getType(), |
| Stores[Idx]->getPointerOperand(), *DL, *SE, /*StrictCheck=*/true); |
| if (!Diff || *Diff == 0) |
| return false; |
| int Val = *Diff; |
| if (Val < 0) { |
| if (ConsecutiveChain[Idx].second > -Val) { |
| Tails.set(K); |
| ConsecutiveChain[Idx] = std::make_pair(K, -Val); |
| } |
| return false; |
| } |
| if (ConsecutiveChain[K].second <= Val) |
| return false; |
| |
| Tails.set(Idx); |
| ConsecutiveChain[K] = std::make_pair(Idx, Val); |
| return Val == 1; |
| }; |
| // Do a quadratic search on all of the given stores in reverse order and find |
| // all of the pairs of stores that follow each other. |
| for (int Idx = E - 1; Idx >= 0; --Idx) { |
| // If a store has multiple consecutive store candidates, search according |
| // to the sequence: Idx-1, Idx+1, Idx-2, Idx+2, ... |
| // This is because usually pairing with immediate succeeding or preceding |
| // candidate create the best chance to find slp vectorization opportunity. |
| const int MaxLookDepth = std::max(E - Idx, Idx + 1); |
| IterCnt = 0; |
| for (int Offset = 1, F = MaxLookDepth; Offset < F; ++Offset) |
| if ((Idx >= Offset && FindConsecutiveAccess(Idx - Offset, Idx)) || |
| (Idx + Offset < E && FindConsecutiveAccess(Idx + Offset, Idx))) |
| break; |
| } |
| |
| // Tracks if we tried to vectorize stores starting from the given tail |
| // already. |
| SmallBitVector TriedTails(E, false); |
| // For stores that start but don't end a link in the chain: |
| for (int Cnt = E; Cnt > 0; --Cnt) { |
| int I = Cnt - 1; |
| if (ConsecutiveChain[I].first == E || Tails.test(I)) |
| continue; |
| // We found a store instr that starts a chain. Now follow the chain and try |
| // to vectorize it. |
| BoUpSLP::ValueList Operands; |
| // Collect the chain into a list. |
| while (I != E && !VectorizedStores.count(Stores[I])) { |
| Operands.push_back(Stores[I]); |
| Tails.set(I); |
| if (ConsecutiveChain[I].second != 1) { |
| // Mark the new end in the chain and go back, if required. It might be |
| // required if the original stores come in reversed order, for example. |
| if (ConsecutiveChain[I].first != E && |
| Tails.test(ConsecutiveChain[I].first) && !TriedTails.test(I) && |
| !VectorizedStores.count(Stores[ConsecutiveChain[I].first])) { |
| TriedTails.set(I); |
| Tails.reset(ConsecutiveChain[I].first); |
| if (Cnt < ConsecutiveChain[I].first + 2) |
| Cnt = ConsecutiveChain[I].first + 2; |
| } |
| break; |
| } |
| // Move to the next value in the chain. |
| I = ConsecutiveChain[I].first; |
| } |
| assert(!Operands.empty() && "Expected non-empty list of stores."); |
| |
| unsigned MaxVecRegSize = R.getMaxVecRegSize(); |
| unsigned EltSize = R.getVectorElementSize(Operands[0]); |
| unsigned MaxElts = llvm::PowerOf2Floor(MaxVecRegSize / EltSize); |
| |
| unsigned MinVF = R.getMinVF(EltSize); |
| unsigned MaxVF = std::min(R.getMaximumVF(EltSize, Instruction::Store), |
| MaxElts); |
| |
| // FIXME: Is division-by-2 the correct step? Should we assert that the |
| // register size is a power-of-2? |
| unsigned StartIdx = 0; |
| for (unsigned Size = MaxVF; Size >= MinVF; Size /= 2) { |
| for (unsigned Cnt = StartIdx, E = Operands.size(); Cnt + Size <= E;) { |
| ArrayRef<Value *> Slice = makeArrayRef(Operands).slice(Cnt, Size); |
| if (!VectorizedStores.count(Slice.front()) && |
| !VectorizedStores.count(Slice.back()) && |
| vectorizeStoreChain(Slice, R, Cnt)) { |
| // Mark the vectorized stores so that we don't vectorize them again. |
| VectorizedStores.insert(Slice.begin(), Slice.end()); |
| Changed = true; |
| // If we vectorized initial block, no need to try to vectorize it |
| // again. |
| if (Cnt == StartIdx) |
| StartIdx += Size; |
| Cnt += Size; |
| continue; |
| } |
| ++Cnt; |
| } |
| // Check if the whole array was vectorized already - exit. |
| if (StartIdx >= Operands.size()) |
| break; |
| } |
| } |
| |
| return Changed; |
| } |
| |
| void SLPVectorizerPass::collectSeedInstructions(BasicBlock *BB) { |
| // Initialize the collections. We will make a single pass over the block. |
| Stores.clear(); |
| GEPs.clear(); |
| |
| // Visit the store and getelementptr instructions in BB and organize them in |
| // Stores and GEPs according to the underlying objects of their pointer |
| // operands. |
| for (Instruction &I : *BB) { |
| // Ignore store instructions that are volatile or have a pointer operand |
| // that doesn't point to a scalar type. |
| if (auto *SI = dyn_cast<StoreInst>(&I)) { |
| if (!SI->isSimple()) |
| continue; |
| if (!isValidElementType(SI->getValueOperand()->getType())) |
| continue; |
| Stores[getUnderlyingObject(SI->getPointerOperand())].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); |
| } |
| |
| bool SLPVectorizerPass::tryToVectorizeList(ArrayRef<Value *> VL, BoUpSLP &R, |
| bool LimitForRegisterSize) { |
| 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 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); |
| // Make sure invalid types (including vector type) are rejected before |
| // determining vectorization factor for scalar instructions. |
| for (Value *V : VL) { |
| Type *Ty = V->getType(); |
| if (!isa<InsertElementInst>(V) && !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; |
| } |
| } |
| |
| unsigned Sz = R.getVectorElementSize(I0); |
| unsigned MinVF = R.getMinVF(Sz); |
| unsigned MaxVF = std::max<unsigned>(PowerOf2Floor(VL.size()), MinVF); |
| MaxVF = std::min(R.getMaximumVF(Sz, S.getOpcode()), MaxVF); |
| 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; |
| } |
| |
| bool Changed = false; |
| bool CandidateFound = false; |
| InstructionCost MinCost = SLPCostThreshold.getValue(); |
| Type *ScalarTy = VL[0]->getType(); |
| if (auto *IE = dyn_cast<InsertElementInst>(VL[0])) |
| ScalarTy = IE->getOperand(1)->getType(); |
| |
| 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 = FixedVectorType::get(ScalarTy, 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)) |
| continue; |
| |
| if ((LimitForRegisterSize && OpsWidth < MaxVF) || |
| (VF > MinVF && OpsWidth <= VF / 2) || (VF == MinVF && OpsWidth < 2)) |
| break; |
| |
| ArrayRef<Value *> Ops = VL.slice(I, OpsWidth); |
| // Check that a previous iteration of this loop did not delete the Value. |
| if (llvm::any_of(Ops, [&R](Value *V) { |
| auto *I = dyn_cast<Instruction>(V); |
| return I && R.isDeleted(I); |
| })) |
| continue; |
| |
| LLVM_DEBUG(dbgs() << "SLP: Analyzing " << OpsWidth << " operations " |
| << "\n"); |
| |
| R.buildTree(Ops); |
| if (R.isTreeTinyAndNotFullyVectorizable()) |
| continue; |
| R.reorderTopToBottom(); |
| R.reorderBottomToTop(); |
| R.buildExternalUses(); |
| |
| R.computeMinimumValueSizes(); |
| InstructionCost Cost = R.getTreeCost(); |
| 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; |
| } |
| |
| namespace { |
| |
| /// Model horizontal reductions. |
| /// |
| /// A horizontal reduction is a tree of reduction instructions that has values |
| /// that can be put into a vector as its leaves. For example: |
| /// |
| /// mul mul mul mul |
| /// \ / \ / |
| /// + + |
| /// \ / |
| /// + |
| /// This tree has "mul" as its leaf values and "+" as its reduction |
| /// instructions. A reduction can feed 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; |
| WeakTrackingVH ReductionRoot; |
| /// The type of reduction operation. |
| RecurKind RdxKind; |
| |
| const unsigned INVALID_OPERAND_INDEX = std::numeric_limits<unsigned>::max(); |
| |
| static bool isCmpSelMinMax(Instruction *I) { |
| return match(I, m_Select(m_Cmp(), m_Value(), m_Value())) && |
| RecurrenceDescriptor::isMinMaxRecurrenceKind(getRdxKind(I)); |
| } |
| |
| // And/or are potentially poison-safe logical patterns like: |
| // select x, y, false |
| // select x, true, y |
| static bool isBoolLogicOp(Instruction *I) { |
| return match(I, m_LogicalAnd(m_Value(), m_Value())) || |
| match(I, m_LogicalOr(m_Value(), m_Value())); |
| } |
| |
| /// Checks if instruction is associative and can be vectorized. |
| static bool isVectorizable(RecurKind Kind, Instruction *I) { |
| if (Kind == RecurKind::None) |
| return false; |
| |
| // Integer ops that map to select instructions or intrinsics are fine. |
| if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(Kind) || |
| isBoolLogicOp(I)) |
| return true; |
| |
| if (Kind == RecurKind::FMax || Kind == RecurKind::FMin) { |
| // FP min/max are associative except for NaN and -0.0. We do not |
| // have to rule out -0.0 here because the intrinsic semantics do not |
| // specify a fixed result for it. |
| return I->getFastMathFlags().noNaNs(); |
| } |
| |
| return I->isAssociative(); |
| } |
| |
| static Value *getRdxOperand(Instruction *I, unsigned Index) { |
| // Poison-safe 'or' takes the form: select X, true, Y |
| // To make that work with the normal operand processing, we skip the |
| // true value operand. |
| // TODO: Change the code and data structures to handle this without a hack. |
| if (getRdxKind(I) == RecurKind::Or && isa<SelectInst>(I) && Index == 1) |
| return I->getOperand(2); |
| return I->getOperand(Index); |
| } |
| |
| /// 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 = INVALID_OPERAND_INDEX; |
| } else { |
| // We ran into something like: |
| // ParentStackElem.first += ... + ExtraArg + ... |
| ExtraArgs[ParentStackElem.first] = ExtraArg; |
| } |
| } |
| |
| /// Creates reduction operation with the current opcode. |
| static Value *createOp(IRBuilder<> &Builder, RecurKind Kind, Value *LHS, |
| Value *RHS, const Twine &Name, bool UseSelect) { |
| unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(Kind); |
| switch (Kind) { |
| case RecurKind::Or: |
| if (UseSelect && |
| LHS->getType() == CmpInst::makeCmpResultType(LHS->getType())) |
| return Builder.CreateSelect(LHS, Builder.getTrue(), RHS, Name); |
| return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, |
| Name); |
| case RecurKind::And: |
| if (UseSelect && |
| LHS->getType() == CmpInst::makeCmpResultType(LHS->getType())) |
| return Builder.CreateSelect(LHS, RHS, Builder.getFalse(), Name); |
| return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, |
| Name); |
| case RecurKind::Add: |
| case RecurKind::Mul: |
| case RecurKind::Xor: |
| case RecurKind::FAdd: |
| case RecurKind::FMul: |
| return Builder.CreateBinOp((Instruction::BinaryOps)RdxOpcode, LHS, RHS, |
| Name); |
| case RecurKind::FMax: |
| return Builder.CreateBinaryIntrinsic(Intrinsic::maxnum, LHS, RHS); |
| case RecurKind::FMin: |
| return Builder.CreateBinaryIntrinsic(Intrinsic::minnum, LHS, RHS); |
| case RecurKind::SMax: |
| if (UseSelect) { |
| Value *Cmp = Builder.CreateICmpSGT(LHS, RHS, Name); |
| return Builder.CreateSelect(Cmp, LHS, RHS, Name); |
| } |
| return Builder.CreateBinaryIntrinsic(Intrinsic::smax, LHS, RHS); |
| case RecurKind::SMin: |
| if (UseSelect) { |
| Value *Cmp = Builder.CreateICmpSLT(LHS, RHS, Name); |
| return Builder.CreateSelect(Cmp, LHS, RHS, Name); |
| } |
| return Builder.CreateBinaryIntrinsic(Intrinsic::smin, LHS, RHS); |
| case RecurKind::UMax: |
| if (UseSelect) { |
| Value *Cmp = Builder.CreateICmpUGT(LHS, RHS, Name); |
| return Builder.CreateSelect(Cmp, LHS, RHS, Name); |
| } |
| return Builder.CreateBinaryIntrinsic(Intrinsic::umax, LHS, RHS); |
| case RecurKind::UMin: |
| if (UseSelect) { |
| Value *Cmp = Builder.CreateICmpULT(LHS, RHS, Name); |
| return Builder.CreateSelect(Cmp, LHS, RHS, Name); |
| } |
| return Builder.CreateBinaryIntrinsic(Intrinsic::umin, LHS, RHS); |
| default: |
| llvm_unreachable("Unknown reduction operation."); |
| } |
| } |
| |
| /// Creates reduction operation with the current opcode with the IR flags |
| /// from \p ReductionOps. |
| static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, |
| Value *RHS, const Twine &Name, |
| const ReductionOpsListType &ReductionOps) { |
| bool UseSelect = ReductionOps.size() == 2 || |
| // Logical or/and. |
| (ReductionOps.size() == 1 && |
| isa<SelectInst>(ReductionOps.front().front())); |
| assert((!UseSelect || ReductionOps.size() != 2 || |
| isa<SelectInst>(ReductionOps[1][0])) && |
| "Expected cmp + select pairs for reduction"); |
| Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, UseSelect); |
| if (RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { |
| if (auto *Sel = dyn_cast<SelectInst>(Op)) { |
| propagateIRFlags(Sel->getCondition(), ReductionOps[0]); |
| propagateIRFlags(Op, ReductionOps[1]); |
| return Op; |
| } |
| } |
| propagateIRFlags(Op, ReductionOps[0]); |
| return Op; |
| } |
| |
| /// Creates reduction operation with the current opcode with the IR flags |
| /// from \p I. |
| static Value *createOp(IRBuilder<> &Builder, RecurKind RdxKind, Value *LHS, |
| Value *RHS, const Twine &Name, Instruction *I) { |
| auto *SelI = dyn_cast<SelectInst>(I); |
| Value *Op = createOp(Builder, RdxKind, LHS, RHS, Name, SelI != nullptr); |
| if (SelI && RecurrenceDescriptor::isIntMinMaxRecurrenceKind(RdxKind)) { |
| if (auto *Sel = dyn_cast<SelectInst>(Op)) |
| propagateIRFlags(Sel->getCondition(), SelI->getCondition()); |
| } |
| propagateIRFlags(Op, I); |
| return Op; |
| } |
| |
| static RecurKind getRdxKind(Instruction *I) { |
| assert(I && "Expected instruction for reduction matching"); |
| TargetTransformInfo::ReductionFlags RdxFlags; |
| if (match(I, m_Add(m_Value(), m_Value()))) |
| return RecurKind::Add; |
| if (match(I, m_Mul(m_Value(), m_Value()))) |
| return RecurKind::Mul; |
| if (match(I, m_And(m_Value(), m_Value())) || |
| match(I, m_LogicalAnd(m_Value(), m_Value()))) |
| return RecurKind::And; |
| if (match(I, m_Or(m_Value(), m_Value())) || |
| match(I, m_LogicalOr(m_Value(), m_Value()))) |
| return RecurKind::Or; |
| if (match(I, m_Xor(m_Value(), m_Value()))) |
| return RecurKind::Xor; |
| if (match(I, m_FAdd(m_Value(), m_Value()))) |
| return RecurKind::FAdd; |
| if (match(I, m_FMul(m_Value(), m_Value()))) |
| return RecurKind::FMul; |
| |
| if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(), m_Value()))) |
| return RecurKind::FMax; |
| if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(), m_Value()))) |
| return RecurKind::FMin; |
| |
| // This matches either cmp+select or intrinsics. SLP is expected to handle |
| // either form. |
| // TODO: If we are canonicalizing to intrinsics, we can remove several |
| // special-case paths that deal with selects. |
| if (match(I, m_SMax(m_Value(), m_Value()))) |
| return RecurKind::SMax; |
| if (match(I, m_SMin(m_Value(), m_Value()))) |
| return RecurKind::SMin; |
| if (match(I, m_UMax(m_Value(), m_Value()))) |
| return RecurKind::UMax; |
| if (match(I, m_UMin(m_Value(), m_Value()))) |
| return RecurKind::UMin; |
| |
| if (auto *Select = dyn_cast<SelectInst>(I)) { |
| // 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; |
| |
| Value *LHS = Select->getTrueValue(); |
| Value *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 RecurKind::None; |
| } else if (match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Specific(RHS)))) { |
| if (!isa<ExtractElementInst>(LHS) || |
| !L1->isIdenticalTo(cast<Instruction>(LHS))) |
| return RecurKind::None; |
| } else { |
| if (!isa<ExtractElementInst>(LHS) || !isa<ExtractElementInst>(RHS)) |
| return RecurKind::None; |
| if (!match(Cond, m_Cmp(Pred, m_Instruction(L1), m_Instruction(L2))) || |
| !L1->isIdenticalTo(cast<Instruction>(LHS)) || |
| !L2->isIdenticalTo(cast<Instruction>(RHS))) |
| return RecurKind::None; |
| } |
| |
| TargetTransformInfo::ReductionFlags RdxFlags; |
| switch (Pred) { |
| default: |
| return RecurKind::None; |
| case CmpInst::ICMP_SGT: |
| case CmpInst::ICMP_SGE: |
| return RecurKind::SMax; |
| case CmpInst::ICMP_SLT: |
| case CmpInst::ICMP_SLE: |
| return RecurKind::SMin; |
| case CmpInst::ICMP_UGT: |
| case CmpInst::ICMP_UGE: |
| return RecurKind::UMax; |
| case CmpInst::ICMP_ULT: |
| case CmpInst::ICMP_ULE: |
| return RecurKind::UMin; |
| } |
| } |
| return RecurKind::None; |
| } |
| |
| /// Get the index of the first operand. |
| static unsigned getFirstOperandIndex(Instruction *I) { |
| return isCmpSelMinMax(I) ? 1 : 0; |
| } |
| |
| /// Total number of operands in the reduction operation. |
| static unsigned getNumberOfOperands(Instruction *I) { |
| return isCmpSelMinMax(I) ? 3 : 2; |
| } |
| |
| /// Checks if the instruction is in basic block \p BB. |
| /// For a cmp+sel min/max reduction check that both ops are in \p BB. |
| static bool hasSameParent(Instruction *I, BasicBlock *BB) { |
| if (isCmpSelMinMax(I) || (isBoolLogicOp(I) && isa<SelectInst>(I))) { |
| auto *Sel = cast<SelectInst>(I); |
| auto *Cmp = dyn_cast<Instruction>(Sel->getCondition()); |
| return Sel->getParent() == BB && Cmp && Cmp->getParent() == BB; |
| } |
| return I->getParent() == BB; |
| } |
| |
| /// Expected number of uses for reduction operations/reduced values. |
| static bool hasRequiredNumberOfUses(bool IsCmpSelMinMax, Instruction *I) { |
| if (IsCmpSelMinMax) { |
| // SelectInst must be used twice while the condition op must have single |
| // use only. |
| if (auto *Sel = dyn_cast<SelectInst>(I)) |
| return Sel->hasNUses(2) && Sel->getCondition()->hasOneUse(); |
| return I->hasNUses(2); |
| } |
| |
| // Arithmetic reduction operation must be used once only. |
| return I->hasOneUse(); |
| } |
| |
| /// Initializes the list of reduction operations. |
| void initReductionOps(Instruction *I) { |
| if (isCmpSelMinMax(I)) |
| ReductionOps.assign(2, ReductionOpsType()); |
| else |
| ReductionOps.assign(1, ReductionOpsType()); |
| } |
| |
| /// Add all reduction operations for the reduction instruction \p I. |
| void addReductionOps(Instruction *I) { |
| if (isCmpSelMinMax(I)) { |
| ReductionOps[0].emplace_back(cast<SelectInst>(I)->getCondition()); |
| ReductionOps[1].emplace_back(I); |
| } else { |
| ReductionOps[0].emplace_back(I); |
| } |
| } |
| |
| static Value *getLHS(RecurKind Kind, Instruction *I) { |
| if (Kind == RecurKind::None) |
| return nullptr; |
| return I->getOperand(getFirstOperandIndex(I)); |
| } |
| static Value *getRHS(RecurKind Kind, Instruction *I) { |
| if (Kind == RecurKind::None) |
| return nullptr; |
| return I->getOperand(getFirstOperandIndex(I) + 1); |
| } |
| |
| public: |
| HorizontalReduction() = default; |
| |
| /// Try to find a reduction tree. |
| bool matchAssociativeReduction(PHINode *Phi, Instruction *Inst) { |
| assert((!Phi || is_contained(Phi->operands(), Inst)) && |
| "Phi needs to use the binary operator"); |
| assert((isa<BinaryOperator>(Inst) || isa<SelectInst>(Inst) || |
| isa<IntrinsicInst>(Inst)) && |
| "Expected binop, select, or intrinsic for reduction matching"); |
| RdxKind = getRdxKind(Inst); |
| |
| // 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 (getLHS(RdxKind, Inst) == Phi) { |
| Phi = nullptr; |
| Inst = dyn_cast<Instruction>(getRHS(RdxKind, Inst)); |
| if (!Inst) |
| return false; |
| RdxKind = getRdxKind(Inst); |
| } else if (getRHS(RdxKind, Inst) == Phi) { |
| Phi = nullptr; |
| Inst = dyn_cast<Instruction>(getLHS(RdxKind, Inst)); |
| if (!Inst) |
| return false; |
| RdxKind = getRdxKind(Inst); |
| } |
| } |
| |
| if (!isVectorizable(RdxKind, Inst)) |
| return false; |
| |
| // Analyze "regular" integer/FP types for reductions - no target-specific |
| // types or pointers. |
| Type *Ty = Inst->getType(); |
| if (!isValidElementType(Ty) || Ty->isPointerTy()) |
| return false; |
| |
| // Though the ultimate reduction may have multiple uses, its condition must |
| // have only single use. |
| if (auto *Sel = dyn_cast<SelectInst>(Inst)) |
| if (!Sel->getCondition()->hasOneUse()) |
| return false; |
| |
| ReductionRoot = Inst; |
| |
| // The opcode for leaf values that we perform a reduction on. |
| // For example: load(x) + load(y) + load(z) + fptoui(w) |
| // The leaf opcode for 'w' does not match, so we don't include it as a |
| // potential candidate for the reduction. |
| unsigned LeafOpcode = 0; |
| |
| // Post-order traverse the reduction tree starting at Inst. We only handle |
| // true trees containing binary operators or selects. |
| SmallVector<std::pair<Instruction *, unsigned>, 32> Stack; |
| Stack.push_back(std::make_pair(Inst, getFirstOperandIndex(Inst))); |
| initReductionOps(Inst); |
| while (!Stack.empty()) { |
| Instruction *TreeN = Stack.back().first; |
| unsigned EdgeToVisit = Stack.back().second++; |
| const RecurKind TreeRdxKind = getRdxKind(TreeN); |
| bool IsReducedValue = TreeRdxKind != RdxKind; |
| |
| // Postorder visit. |
| if (IsReducedValue || EdgeToVisit >= getNumberOfOperands(TreeN)) { |
| if (IsReducedValue) |
| ReducedVals.push_back(TreeN); |
| else { |
| auto ExtraArgsIter = ExtraArgs.find(TreeN); |
| if (ExtraArgsIter != ExtraArgs.end() && !ExtraArgsIter->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 |
| addReductionOps(TreeN); |
| } |
| // Retract. |
| Stack.pop_back(); |
| continue; |
| } |
| |
| // Visit operands. |
| Value *EdgeVal = getRdxOperand(TreeN, EdgeToVisit); |
| auto *EdgeInst = dyn_cast<Instruction>(EdgeVal); |
| if (!EdgeInst) { |
| // Edge value is not a reduction instruction or a leaf instruction. |
| // (It may be a constant, function argument, or something else.) |
| markExtraArg(Stack.back(), EdgeVal); |
| continue; |
| } |
| RecurKind EdgeRdxKind = getRdxKind(EdgeInst); |
| // Continue analysis if the next operand is a reduction operation or |
| // (possibly) a leaf value. If the leaf value opcode is not set, |
| // the first met operation != reduction operation is considered as the |
| // leaf opcode. |
| // Only handle trees in the current basic block. |
| // Each tree node needs to have minimal number of users except for the |
| // ultimate reduction. |
| const bool IsRdxInst = EdgeRdxKind == RdxKind; |
| if (EdgeInst != Phi && EdgeInst != Inst && |
| hasSameParent(EdgeInst, Inst->getParent()) && |
| hasRequiredNumberOfUses(isCmpSelMinMax(Inst), EdgeInst) && |
| (!LeafOpcode || LeafOpcode == EdgeInst->getOpcode() || IsRdxInst)) { |
| if (IsRdxInst) { |
| // We need to be able to reassociate the reduction operations. |
| if (!isVectorizable(EdgeRdxKind, EdgeInst)) { |
| // I is an extra argument for TreeN (its parent operation). |
| markExtraArg(Stack.back(), EdgeInst); |
| continue; |
| } |
| } else if (!LeafOpcode) { |
| LeafOpcode = EdgeInst->getOpcode(); |
| } |
| Stack.push_back( |
| std::make_pair(EdgeInst, getFirstOperandIndex(EdgeInst))); |
| continue; |
| } |
| // I is an extra argument for TreeN (its parent operation). |
| markExtraArg(Stack.back(), EdgeInst); |
| } |
| return true; |
| } |
| |
| /// Attempt to vectorize the tree found by matchAssociativeReduction. |
| Value *tryToReduce(BoUpSLP &V, TargetTransformInfo *TTI) { |
| // If there are a sufficient number of reduction values, reduce |
| // to a nearby power-of-2. We can safely generate oversized |
| // vectors and rely on the backend to split them to legal sizes. |
| unsigned NumReducedVals = ReducedVals.size(); |
| if (NumReducedVals < 4) |
| return nullptr; |
| |
| // Intersect the fast-math-flags from all reduction operations. |
| FastMathFlags RdxFMF; |
| RdxFMF.set(); |
| for (ReductionOpsType &RdxOp : ReductionOps) { |
| for (Value *RdxVal : RdxOp) { |
| if (auto *FPMO = dyn_cast<FPMathOperator>(RdxVal)) |
| RdxFMF &= FPMO->getFastMathFlags(); |
| } |
| } |
| |
| IRBuilder<> Builder(cast<Instruction>(ReductionRoot)); |
| Builder.setFastMathFlags(RdxFMF); |
| |
| BoUpSLP::ExtraValueToDebugLocsMap ExternallyUsedValues; |
| // The same extra argument may be used several times, so log each attempt |
| // to use it. |
| for (const std::pair<Instruction *, Value *> &Pair : ExtraArgs) { |
| assert(Pair.first && "DebugLoc must be set."); |
| ExternallyUsedValues[Pair.second].push_back(Pair.first); |
| } |
| |
| // The compare instruction of a min/max is the insertion point for new |
| // instructions and may be replaced with a new compare instruction. |
| auto getCmpForMinMaxReduction = [](Instruction *RdxRootInst) { |
| assert(isa<SelectInst>(RdxRootInst) && |
| "Expected min/max reduction to have select root instruction"); |
| Value *ScalarCond = cast<SelectInst>(RdxRootInst)->getCondition(); |
| assert(isa<Instruction>(ScalarCond) && |
| "Expected min/max reduction to have compare condition"); |
| return cast<Instruction>(ScalarCond); |
| }; |
| |
| // 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 (ReductionOpsType &RdxOp : ReductionOps) |
| IgnoreList.append(RdxOp.begin(), RdxOp.end()); |
| |
| unsigned ReduxWidth = PowerOf2Floor(NumReducedVals); |
| if (NumReducedVals > ReduxWidth) { |
| // In the loop below, we are building a tree based on a window of |
| // 'ReduxWidth' values. |
| // If the operands of those values have common traits (compare predicate, |
| // constant operand, etc), then we want to group those together to |
| // minimize the cost of the reduction. |
| |
| // TODO: This should be extended to count common operands for |
| // compares and binops. |
| |
| // Step 1: Count the number of times each compare predicate occurs. |
| SmallDenseMap<unsigned, unsigned> PredCountMap; |
| for (Value *RdxVal : ReducedVals) { |
| CmpInst::Predicate Pred; |
| if (match(RdxVal, m_Cmp(Pred, m_Value(), m_Value()))) |
| ++PredCountMap[Pred]; |
| } |
| // Step 2: Sort the values so the most common predicates come first. |
| stable_sort(ReducedVals, [&PredCountMap](Value *A, Value *B) { |
| CmpInst::Predicate PredA, PredB; |
| if (match(A, m_Cmp(PredA, m_Value(), m_Value())) && |
| match(B, m_Cmp(PredB, m_Value(), m_Value()))) { |
| return PredCountMap[PredA] > PredCountMap[PredB]; |
| } |
| return false; |
| }); |
| } |
| |
| Value *VectorizedTree = nullptr; |
| unsigned i = 0; |
| while (i < NumReducedVals - ReduxWidth + 1 && ReduxWidth > 2) { |
| ArrayRef<Value *> VL(&ReducedVals[i], ReduxWidth); |
| V.buildTree(VL, IgnoreList); |
| if (V.isTreeTinyAndNotFullyVectorizable(/*ForReduction=*/true)) |
| break; |
| if (V.isLoadCombineReductionCandidate(RdxKind)) |
| break; |
| V.reorderTopToBottom(); |
| V.reorderBottomToTop(/*IgnoreReorder=*/true); |
| V.buildExternalUses(ExternallyUsedValues); |
| |
| // For a poison-safe boolean logic reduction, do not replace select |
| // instructions with logic ops. All reduced values will be frozen (see |
| // below) to prevent leaking poison. |
| if (isa<SelectInst>(ReductionRoot) && |
| isBoolLogicOp(cast<Instruction>(ReductionRoot)) && |
| NumReducedVals != ReduxWidth) |
| break; |
| |
| V.computeMinimumValueSizes(); |
| |
| // Estimate cost. |
| InstructionCost TreeCost = |
| V.getTreeCost(makeArrayRef(&ReducedVals[i], ReduxWidth)); |
| InstructionCost ReductionCost = |
| getReductionCost(TTI, ReducedVals[i], ReduxWidth, RdxFMF); |
| InstructionCost Cost = TreeCost + ReductionCost; |
| if (!Cost.isValid()) { |
| LLVM_DEBUG(dbgs() << "Encountered invalid baseline cost.\n"); |
| return nullptr; |
| } |
| 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. If the root is a select (min/max idiom), the insert |
| // point is the compare condition of that select. |
| Instruction *RdxRootInst = cast<Instruction>(ReductionRoot); |
| if (isCmpSelMinMax(RdxRootInst)) |
| Builder.SetInsertPoint(getCmpForMinMaxReduction(RdxRootInst)); |
| else |
| Builder.SetInsertPoint(RdxRootInst); |
| |
| // To prevent poison from leaking across what used to be sequential, safe, |
| // scalar boolean logic operations, the reduction operand must be frozen. |
| if (isa<SelectInst>(RdxRootInst) && isBoolLogicOp(RdxRootInst)) |
| VectorizedRoot = Builder.CreateFreeze(VectorizedRoot); |
| |
| Value *ReducedSubTree = |
| emitReduction(VectorizedRoot, Builder, ReduxWidth, TTI); |
| |
| if (!VectorizedTree) { |
| // Initialize the final value in the reduction. |
| VectorizedTree = ReducedSubTree; |
| } else { |
| // Update the final value in the reduction. |
| Builder.SetCurrentDebugLocation(Loc); |
| VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, |
| ReducedSubTree, "op.rdx", ReductionOps); |
| } |
| 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()); |
| VectorizedTree = |
| createOp(Builder, RdxKind, VectorizedTree, I, "", ReductionOps); |
| } |
| for (auto &Pair : ExternallyUsedValues) { |
| // Add each externally used value to the final reduction. |
| for (auto *I : Pair.second) { |
| Builder.SetCurrentDebugLocation(I->getDebugLoc()); |
| VectorizedTree = createOp(Builder, RdxKind, VectorizedTree, |
| Pair.first, "op.extra", I); |
| } |
| } |
| |
| ReductionRoot->replaceAllUsesWith(VectorizedTree); |
| |
| // Mark all scalar reduction ops for deletion, they are replaced by the |
| // vector reductions. |
| V.eraseInstructions(IgnoreList); |
| } |
| return VectorizedTree; |
| } |
| |
| unsigned numReductionValues() const { return ReducedVals.size(); } |
| |
| private: |
| /// Calculate the cost of a reduction. |
| InstructionCost getReductionCost(TargetTransformInfo *TTI, |
| Value *FirstReducedVal, unsigned ReduxWidth, |
| FastMathFlags FMF) { |
| TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput; |
| Type *ScalarTy = FirstReducedVal->getType(); |
| FixedVectorType *VectorTy = FixedVectorType::get(ScalarTy, ReduxWidth); |
| InstructionCost VectorCost, ScalarCost; |
| switch (RdxKind) { |
| case RecurKind::Add: |
| case RecurKind::Mul: |
| case RecurKind::Or: |
| case RecurKind::And: |
| case RecurKind::Xor: |
| case RecurKind::FAdd: |
| case RecurKind::FMul: { |
| unsigned RdxOpcode = RecurrenceDescriptor::getOpcode(RdxKind); |
| VectorCost = |
| TTI->getArithmeticReductionCost(RdxOpcode, VectorTy, FMF, CostKind); |
| ScalarCost = TTI->getArithmeticInstrCost(RdxOpcode, ScalarTy, CostKind); |
| break; |
| } |
| case RecurKind::FMax: |
| case RecurKind::FMin: { |
| auto *SclCondTy = CmpInst::makeCmpResultType(ScalarTy); |
| auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); |
| VectorCost = TTI->getMinMaxReductionCost(VectorTy, VecCondTy, |
| /*unsigned=*/false, CostKind); |
| CmpInst::Predicate RdxPred = getMinMaxReductionPredicate(RdxKind); |
| ScalarCost = TTI->getCmpSelInstrCost(Instruction::FCmp, ScalarTy, |
| SclCondTy, RdxPred, CostKind) + |
| TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, |
| SclCondTy, RdxPred, CostKind); |
| break; |
| } |
| case RecurKind::SMax: |
| case RecurKind::SMin: |
| case RecurKind::UMax: |
| case RecurKind::UMin: { |
| auto *SclCondTy = CmpInst::makeCmpResultType(ScalarTy); |
| auto *VecCondTy = cast<VectorType>(CmpInst::makeCmpResultType(VectorTy)); |
| bool IsUnsigned = |
| RdxKind == RecurKind::UMax || RdxKind == RecurKind::UMin; |
| VectorCost = TTI->getMinMaxReductionCost(VectorTy, VecCondTy, IsUnsigned, |
| CostKind); |
| CmpInst::Predicate RdxPred = getMinMaxReductionPredicate(RdxKind); |
| ScalarCost = TTI->getCmpSelInstrCost(Instruction::ICmp, ScalarTy, |
| SclCondTy, RdxPred, CostKind) + |
| TTI->getCmpSelInstrCost(Instruction::Select, ScalarTy, |
| SclCondTy, RdxPred, CostKind); |
| break; |
| } |
| default: |
| llvm_unreachable("Expected arithmetic or min/max reduction operation"); |
| } |
| |
| // Scalar cost is repeated for N-1 elements. |
| ScalarCost *= (ReduxWidth - 1); |
| LLVM_DEBUG(dbgs() << "SLP: Adding cost " << VectorCost - ScalarCost |
| << " for reduction that starts with " << *FirstReducedVal |
| << " (It is a splitting reduction)\n"); |
| return VectorCost - ScalarCost; |
| } |
| |
| /// 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"); |
| assert(RdxKind != RecurKind::FMulAdd && |
| "A call to the llvm.fmuladd intrinsic is not handled yet"); |
| |
| ++NumVectorInstructions; |
| return createSimpleTargetReduction(Builder, TTI, VectorizedValue, RdxKind, |
| ReductionOps.back()); |
| } |
| }; |
| |
| } // end anonymous namespace |
| |
| static Optional<unsigned> getAggregateSize(Instruction *InsertInst) { |
| if (auto *IE = dyn_cast<InsertElementInst>(InsertInst)) |
| return cast<FixedVectorType>(IE->getType())->getNumElements(); |
| |
| unsigned AggregateSize = 1; |
| auto *IV = cast<InsertValueInst>(InsertInst); |
| Type *CurrentType = IV->getType(); |
| do { |
| if (auto *ST = dyn_cast<StructType>(CurrentType)) { |
| for (auto *Elt : ST->elements()) |
| if (Elt != ST->getElementType(0)) // check homogeneity |
| return None; |
| AggregateSize *= ST->getNumElements(); |
| CurrentType = ST->getElementType(0); |
| } else if (auto *AT = dyn_cast<ArrayType>(CurrentType)) { |
| AggregateSize *= AT->getNumElements(); |
| CurrentType = AT->getElementType(); |
| } else if (auto *VT = dyn_cast<FixedVectorType>(CurrentType)) { |
| AggregateSize *= VT->getNumElements(); |
| return AggregateSize; |
| } else if (CurrentType->isSingleValueType()) { |
| return AggregateSize; |
| } else { |
| return None; |
| } |
| } while (true); |
| } |
| |
| static bool findBuildAggregate_rec(Instruction *LastInsertInst, |
| TargetTransformInfo *TTI, |
| SmallVectorImpl<Value *> &BuildVectorOpds, |
| SmallVectorImpl<Value *> &InsertElts, |
| unsigned OperandOffset) { |
| do { |
| Value *InsertedOperand = LastInsertInst->getOperand(1); |
| Optional<int> OperandIndex = getInsertIndex(LastInsertInst, OperandOffset); |
| if (!OperandIndex) |
| return false; |
| if (isa<InsertElementInst>(InsertedOperand) || |
| isa<InsertValueInst>(InsertedOperand)) { |
| if (!findBuildAggregate_rec(cast<Instruction>(InsertedOperand), TTI, |
| BuildVectorOpds, InsertElts, *OperandIndex)) |
| return false; |
| } else { |
| BuildVectorOpds[*OperandIndex] = InsertedOperand; |
| InsertElts[*OperandIndex] = LastInsertInst; |
| } |
| LastInsertInst = dyn_cast<Instruction>(LastInsertInst->getOperand(0)); |
| } while (LastInsertInst != nullptr && |
| (isa<InsertValueInst>(LastInsertInst) || |
| isa<InsertElementInst>(LastInsertInst)) && |
| LastInsertInst->hasOneUse()); |
| return true; |
| } |
| |
| /// Recognize construction of vectors like |
| /// %ra = insertelement <4 x float> poison, 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 or insertvalue instruction. |
| /// |
| /// Also recognize homogeneous aggregates like {<2 x float>, <2 x float>}, |
| /// {{float, float}, {float, float}}, [2 x {float, float}] and so on. |
| /// See llvm/test/Transforms/SLPVectorizer/X86/pr42022.ll for examples. |
| /// |
| /// Assume LastInsertInst is of InsertElementInst or InsertValueInst type. |
| /// |
| /// \return true if it matches. |
| static bool findBuildAggregate(Instruction *LastInsertInst, |
| TargetTransformInfo *TTI, |
| SmallVectorImpl<Value *> &BuildVectorOpds, |
| SmallVectorImpl<Value *> &InsertElts) { |
| |
| assert((isa<InsertElementInst>(LastInsertInst) || |
| isa<InsertValueInst>(LastInsertInst)) && |
| "Expected insertelement or insertvalue instruction!"); |
| |
| assert((BuildVectorOpds.empty() && InsertElts.empty()) && |
| "Expected empty result vectors!"); |
| |
| Optional<unsigned> AggregateSize = getAggregateSize(LastInsertInst); |
| if (!AggregateSize) |
| return false; |
| BuildVectorOpds.resize(*AggregateSize); |
| InsertElts.resize(*AggregateSize); |
| |
| if (findBuildAggregate_rec(LastInsertInst, TTI, BuildVectorOpds, InsertElts, |
| 0)) { |
| llvm::erase_value(BuildVectorOpds, nullptr); |
| llvm::erase_value(InsertElts, nullptr); |
| if (BuildVectorOpds.size() >= 2) |
| return true; |
| } |
| |
| return false; |
| } |
| |
| /// 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; |
| } |
| |
| static bool matchRdxBop(Instruction *I, Value *&V0, Value *&V1) { |
| if (match(I, m_BinOp(m_Value(V0), m_Value(V1)))) |
| return true; |
| if (match(I, m_Intrinsic<Intrinsic::maxnum>(m_Value(V0), m_Value(V1)))) |
| return true; |
| if (match(I, m_Intrinsic<Intrinsic::minnum>(m_Value(V0), m_Value(V1)))) |
| return true; |
| if (match(I, m_Intrinsic<Intrinsic::smax>(m_Value(V0), m_Value(V1)))) |
| return true; |
| if (match(I, m_Intrinsic<Intrinsic::smin>(m_Value(V0), m_Value(V1)))) |
| return true; |
| if (match(I, m_Intrinsic<Intrinsic::umax>(m_Value(V0), m_Value(V1)))) |
| return true; |
| if (match(I, m_Intrinsic<Intrinsic::umin>(m_Value(V0), m_Value(V1)))) |
| return true; |
| return false; |
| } |
| |
| /// 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. |
| // Skip the analysis of CmpInsts.Compiler implements postanalysis of the |
| // CmpInsts so we can skip extra attempts in |
| // tryToVectorizeHorReductionOrInstOperands and save compile time. |
| std::queue<std::pair<Instruction *, unsigned>> Stack; |
| Stack.emplace(Root, 0); |
| SmallPtrSet<Value *, 8> VisitedInstrs; |
| SmallVector<WeakTrackingVH> PostponedInsts; |
| bool Res = false; |
| auto &&TryToReduce = [TTI, &P, &R](Instruction *Inst, Value *&B0, |
| Value *&B1) -> Value * { |
| bool IsBinop = matchRdxBop(Inst, B0, B1); |
| bool IsSelect = match(Inst, m_Select(m_Value(), m_Value(), m_Value())); |
| if (IsBinop || IsSelect) { |
| HorizontalReduction HorRdx; |
| if (HorRdx.matchAssociativeReduction(P, Inst)) |
| return HorRdx.tryToReduce(R, TTI); |
| } |
| return nullptr; |
| }; |
| while (!Stack.empty()) { |
| Instruction *Inst; |
| unsigned Level; |
| std::tie(Inst, Level) = Stack.front(); |
| Stack.pop(); |
| // Do not try to analyze instruction that has already been vectorized. |
| // This may happen when we vectorize instruction operands on a previous |
| // iteration while stack was populated before that happened. |
| if (R.isDeleted(Inst)) |
| continue; |
| Value *B0 = nullptr, *B1 = nullptr; |
| if (Value *V = TryToReduce(Inst, B0, B1)) { |
| Res = true; |
| // Set P to nullptr to avoid re-analysis of phi node in |
| // matchAssociativeReduction function unless this is the root node. |
| P = nullptr; |
| if (auto *I = dyn_cast<Instruction>(V)) { |
| // Try to find another reduction. |
| Stack.emplace(I, Level); |
| continue; |
| } |
| } else { |
| bool IsBinop = B0 && B1; |
| if (P && IsBinop) { |
| Inst = dyn_cast<Instruction>(B0); |
| if (Inst == P) |
| Inst = dyn_cast<Instruction>(B1); |
| 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; |
| // Do not try to vectorize CmpInst operands, this is done separately. |
| // Final attempt for binop args vectorization should happen after the loop |
| // to try to find reductions. |
| if (!isa<CmpInst>(Inst)) |
| PostponedInsts.push_back(Inst); |
| } |
| |
| // 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)) |
| // Do not try to vectorize CmpInst operands, this is done |
| // separately. |
| if (!isa<PHINode>(I) && !isa<CmpInst>(I) && !R.isDeleted(I) && |
| I->getParent() == BB) |
| Stack.emplace(I, Level); |
| } |
| // Try to vectorized binops where reductions were not found. |
| for (Value *V : PostponedInsts) |
| if (auto *Inst = dyn_cast<Instruction>(V)) |
| if (!R.isDeleted(Inst)) |
| Res |= Vectorize(Inst, R); |
| return Res; |
| } |
| |
| bool SLPVectorizerPass::vectorizeRootInstruction(PHINode *P, Value *V, |
| BasicBlock *BB, BoUpSLP &R, |
| TargetTransformInfo *TTI) { |
| auto *I = dyn_cast_or_null<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; |
| SmallVector<Value *, 16> BuildVectorInsts; |
| if (!findBuildAggregate(IVI, TTI, BuildVectorOpds, BuildVectorInsts)) |
| 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) { |
| SmallVector<Value *, 16> BuildVectorInsts; |
| SmallVector<Value *, 16> BuildVectorOpds; |
| SmallVector<int> Mask; |
| if (!findBuildAggregate(IEI, TTI, BuildVectorOpds, BuildVectorInsts) || |
| (llvm::all_of(BuildVectorOpds, |
| [](Value *V) { return isa<ExtractElementInst>(V); }) && |
| isFixedVectorShuffle(BuildVectorOpds, Mask))) |
| return false; |
| |
| LLVM_DEBUG(dbgs() << "SLP: array mappable to vector: " << *IEI << "\n"); |
| return tryToVectorizeList(BuildVectorInsts, R); |
| } |
| |
| bool SLPVectorizerPass::vectorizeSimpleInstructions( |
| SmallVectorImpl<Instruction *> &Instructions, BasicBlock *BB, BoUpSLP &R, |
| bool AtTerminator) { |
| bool OpsChanged = false; |
| SmallVector<Instruction *, 4> PostponedCmps; |
| for (auto *I : reverse(Instructions)) { |
| if (R.isDeleted(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 (isa<CmpInst>(I)) |
| PostponedCmps.push_back(I); |
| } |
| if (AtTerminator) { |
| // Try to find reductions first. |
| for (Instruction *I : PostponedCmps) { |
| if (R.isDeleted(I)) |
| continue; |
| for (Value *Op : I->operands()) |
| OpsChanged |= vectorizeRootInstruction(nullptr, Op, BB, R, TTI); |
| } |
| // Try to vectorize operands as vector bundles. |
| for (Instruction *I : PostponedCmps) { |
| if (R.isDeleted(I)) |
| continue; |
| OpsChanged |= tryToVectorize(I, R); |
| } |
| Instructions.clear(); |
| } else { |
| // Insert in reverse order since the PostponedCmps vector was filled in |
| // reverse order. |
| Instructions.assign(PostponedCmps.rbegin(), PostponedCmps.rend()); |
| } |
| return OpsChanged; |
| } |
| |
| template <typename T> |
| static bool |
| tryToVectorizeSequence(SmallVectorImpl<T *> &Incoming, |
| function_ref<unsigned(T *)> Limit, |
| function_ref<bool(T *, T *)> Comparator, |
| function_ref<bool(T *, T *)> AreCompatible, |
| function_ref<bool(ArrayRef<T *>, bool)> TryToVectorize, |
| bool LimitForRegisterSize) { |
| bool Changed = false; |
| // Sort by type, parent, operands. |
| stable_sort(Incoming, Comparator); |
| |
| // Try to vectorize elements base on their type. |
| SmallVector<T *> Candidates; |
| for (auto *IncIt = Incoming.begin(), *E = Incoming.end(); IncIt != E;) { |
| // Look for the next elements with the same type, parent and operand |
| // kinds. |
| auto *SameTypeIt = IncIt; |
| while (SameTypeIt != E && AreCompatible(*SameTypeIt, *IncIt)) |
| ++SameTypeIt; |
| |
| // Try to vectorize them. |
| unsigned NumElts = (SameTypeIt - IncIt); |
| LLVM_DEBUG(dbgs() << "SLP: Trying to vectorize starting at nodes (" |
| << NumElts << ")\n"); |
| // The vectorization is a 3-state attempt: |
| // 1. Try to vectorize instructions with the same/alternate opcodes with the |
| // size of maximal register at first. |
| // 2. Try to vectorize remaining instructions with the same type, if |
| // possible. This may result in the better vectorization results rather than |
| // if we try just to vectorize instructions with the same/alternate opcodes. |
| // 3. Final attempt to try to vectorize all instructions with the |
| // same/alternate ops only, this may result in some extra final |
| // vectorization. |
| if (NumElts > 1 && |
| TryToVectorize(makeArrayRef(IncIt, NumElts), LimitForRegisterSize)) { |
| // Success start over because instructions might have been changed. |
| Changed = true; |
| } else if (NumElts < Limit(*IncIt) && |
| (Candidates.empty() || |
| Candidates.front()->getType() == (*IncIt)->getType())) { |
| Candidates.append(IncIt, std::next(IncIt, NumElts)); |
| } |
| // Final attempt to vectorize instructions with the same types. |
| if (Candidates.size() > 1 && |
| (SameTypeIt == E || (*SameTypeIt)->getType() != (*IncIt)->getType())) { |
| if (TryToVectorize(Candidates, /*LimitForRegisterSize=*/false)) { |
| // Success start over because instructions might have been changed. |
| Changed = true; |
| } else if (LimitForRegisterSize) { |
| // Try to vectorize using small vectors. |
| for (auto *It = Candidates.begin(), *End = Candidates.end(); |
| It != End;) { |
| auto *SameTypeIt = It; |
| while (SameTypeIt != End && AreCompatible(*SameTypeIt, *It)) |
| ++SameTypeIt; |
| unsigned NumElts = (SameTypeIt - It); |
| if (NumElts > 1 && TryToVectorize(makeArrayRef(It, NumElts), |
| /*LimitForRegisterSize=*/false)) |
| Changed = true; |
| It = SameTypeIt; |
| } |
| } |
| Candidates.clear(); |
| } |
| |
| // Start over at the next instruction of a different type (or the end). |
| IncIt = SameTypeIt; |
| } |
| return Changed; |
| } |
| |
| bool SLPVectorizerPass::vectorizeChainsInBlock(BasicBlock *BB, BoUpSLP &R) { |
| bool Changed = false; |
| SmallVector<Value *, 4> Incoming; |
| SmallPtrSet<Value *, 16> VisitedInstrs; |
| // Maps phi nodes to the non-phi nodes found in the use tree for each phi |
| // node. Allows better to identify the chains that can be vectorized in the |
| // better way. |
| DenseMap<Value *, SmallVector<Value *, 4>> PHIToOpcodes; |
| auto PHICompare = [this, &PHIToOpcodes](Value *V1, Value *V2) { |
| assert(isValidElementType(V1->getType()) && |
| isValidElementType(V2->getType()) && |
| "Expected vectorizable types only."); |
| // It is fine to compare type IDs here, since we expect only vectorizable |
| // types, like ints, floats and pointers, we don't care about other type. |
| if (V1->getType()->getTypeID() < V2->getType()->getTypeID()) |
| return true; |
| if (V1->getType()->getTypeID() > V2->getType()->getTypeID()) |
| return false; |
| ArrayRef<Value *> Opcodes1 = PHIToOpcodes[V1]; |
| ArrayRef<Value *> Opcodes2 = PHIToOpcodes[V2]; |
| if (Opcodes1.size() < Opcodes2.size()) |
| return true; |
| if (Opcodes1.size() > Opcodes2.size()) |
| return false; |
| for (int I = 0, E = Opcodes1.size(); I < E; ++I) { |
| // Undefs are compatible with any other value. |
| if (isa<UndefValue>(Opcodes1[I]) || isa<UndefValue>(Opcodes2[I])) |
| continue; |
| if (auto *I1 = dyn_cast<Instruction>(Opcodes1[I])) |
| if (auto *I2 = dyn_cast<Instruction>(Opcodes2[I])) { |
| DomTreeNodeBase<BasicBlock> *NodeI1 = DT->getNode(I1->getParent()); |
| DomTreeNodeBase<BasicBlock> *NodeI2 = DT->getNode(I2->getParent()); |
| if (!NodeI1) |
| return NodeI2 != nullptr; |
| if (!NodeI2) |
| return false; |
| assert((NodeI1 == NodeI2) == |
| (NodeI1->getDFSNumIn() == NodeI2->getDFSNumIn()) && |
| "Different nodes should have different DFS numbers"); |
| if (NodeI1 != NodeI2) |
| return NodeI1->getDFSNumIn() < NodeI2->getDFSNumIn(); |
| InstructionsState S = getSameOpcode({I1, I2}); |
| if (S.getOpcode()) |
| continue; |
| return I1->getOpcode() < I2->getOpcode(); |
| } |
| if (isa<Constant>(Opcodes1[I]) && isa<Constant>(Opcodes2[I])) |
| continue; |
| if (Opcodes1[I]->getValueID() < Opcodes2[I]->getValueID()) |
| return true; |
| if (Opcodes1[I]->getValueID() > Opcodes2[I]->getValueID()) |
| return false; |
| } |
| return false; |
| }; |
| auto AreCompatiblePHIs = [&PHIToOpcodes](Value *V1, Value *V2) { |
| if (V1 == V2) |
| return true; |
| if (V1->getType() != V2->getType()) |
| return false; |
| ArrayRef<Value *> Opcodes1 = PHIToOpcodes[V1]; |
| ArrayRef<Value *> Opcodes2 = PHIToOpcodes[V2]; |
| if (Opcodes1.size() != Opcodes2.size()) |
| return false; |
| for (int I = 0, E = Opcodes1.size(); I < E; ++I) { |
| // Undefs are compatible with any other value. |
| if (isa<UndefValue>(Opcodes1[I]) || isa<UndefValue>(Opcodes2[I])) |
| continue; |
| if (auto *I1 = dyn_cast<Instruction>(Opcodes1[I])) |
| if (auto *I2 = dyn_cast<Instruction>(Opcodes2[I])) { |
| if (I1->getParent() != I2->getParent()) |
| return false; |
| InstructionsState S = getSameOpcode({I1, I2}); |
| if (S.getOpcode()) |
| continue; |
| return false; |
| } |
| if (isa<Constant>(Opcodes1[I]) && isa<Constant>(Opcodes2[I])) |
| continue; |
| if (Opcodes1[I]->getValueID() != Opcodes2[I]->getValueID()) |
| return false; |
| } |
| return true; |
| }; |
| auto Limit = [&R](Value *V) { |
| unsigned EltSize = R.getVectorElementSize(V); |
| return std::max(2U, R.getMaxVecRegSize() / EltSize); |
| }; |
| |
| bool HaveVectorizedPhiNodes = false; |
| do { |
| // Collect the incoming values from the PHIs. |
| Incoming.clear(); |
| for (Instruction &I : *BB) { |
| PHINode *P = dyn_cast<PHINode>(&I); |
| if (!P) |
| break; |
| |
| // No need to analyze deleted, vectorized and non-vectorizable |
| // instructions. |
| if (!VisitedInstrs.count(P) && !R.isDeleted(P) && |
| isValidElementType(P->getType())) |
| Incoming.push_back(P); |
| } |
| |
| // Find the corresponding non-phi nodes for better matching when trying to |
| // build the tree. |
| for (Value *V : Incoming) { |
| SmallVectorImpl<Value *> &Opcodes = |
| PHIToOpcodes.try_emplace(V).first->getSecond(); |
| if (!Opcodes.empty()) |
| continue; |
| SmallVector<Value *, 4> Nodes(1, V); |
| SmallPtrSet<Value *, 4> Visited; |
| while (!Nodes.empty()) { |
| auto *PHI = cast<PHINode>(Nodes.pop_back_val()); |
| if (!Visited.insert(PHI).second) |
| continue; |
| for (Value *V : PHI->incoming_values()) { |
| if (auto *PHI1 = dyn_cast<PHINode>((V))) { |
| Nodes.push_back(PHI1); |
| continue; |
| } |
| Opcodes.emplace_back(V); |
| } |
| } |
| } |
| |
| HaveVectorizedPhiNodes = tryToVectorizeSequence<Value>( |
| Incoming, Limit, PHICompare, AreCompatiblePHIs, |
| [this, &R](ArrayRef<Value *> Candidates, bool LimitForRegisterSize) { |
| return tryToVectorizeList(Candidates, R, LimitForRegisterSize); |
| }, |
| /*LimitForRegisterSize=*/true); |
| Changed |= HaveVectorizedPhiNodes; |
| VisitedInstrs.insert(Incoming.begin(), Incoming.end()); |
| } while (HaveVectorizedPhiNodes); |
| |
| VisitedInstrs.clear(); |
| |
| SmallVector<Instruction *, 8> PostProcessInstructions; |
| SmallDenseSet<Instruction *, 4> KeyNodes; |
| for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) { |
| // Skip instructions with scalable type. The num of elements is unknown at |
| // compile-time for scalable type. |
| if (isa<ScalableVectorType>(it->getType())) |
| continue; |
| |
| // Skip instructions marked for the deletion. |
| if (R.isDeleted(&*it)) |
| continue; |
| // We may go through BB multiple times so skip the one we have checked. |
| if (!VisitedInstrs.insert(&*it).second) { |
| if (it->use_empty() && KeyNodes.contains(&*it) && |
| vectorizeSimpleInstructions(PostProcessInstructions, BB, R, |
| it->isTerminator())) { |
| // 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) { |
| // 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; |
| } |
| } |
| // Try to vectorize the incoming values of the PHI, to catch reductions |
| // that feed into PHIs. |
| for (unsigned I = 0, E = P->getNumIncomingValues(); I != E; I++) { |
| // Skip if the incoming block is the current BB for now. Also, bypass |
| // unreachable IR for efficiency and to avoid crashing. |
| // TODO: Collect the skipped incoming values and try to vectorize them |
| // after processing BB. |
| if (BB == P->getIncomingBlock(I) || |
| !DT->isReachableFromEntry(P->getIncomingBlock(I))) |
| continue; |
| |
| Changed |= vectorizeRootInstruction(nullptr, P->getIncomingValue(I), |
| P->getIncomingBlock(I), R, TTI); |
| } |
| 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, |
| it->isTerminator()); |
| 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"); |
| |
| // Process the GEP list in chunks suitable for the target's supported |
| // vector size. If a vector register can't hold 1 element, we are done. We |
| // are trying to vectorize the index computations, so the maximum number of |
| // elements is based on the size of the index expression, rather than the |
| // size of the GEP itself (the target's pointer size). |
| unsigned MaxVecRegSize = R.getMaxVecRegSize(); |
| unsigned EltSize = R.getVectorElementSize(*Entry.second[0]->idx_begin()); |
| if (MaxVecRegSize < EltSize) |
| continue; |
| |
| unsigned MaxElts = MaxVecRegSize / EltSize; |
| for (unsigned BI = 0, BE = Entry.second.size(); BI < BE; BI += MaxElts) { |
| auto Len = std::min<unsigned>(BE - BI, MaxElts); |
| ArrayRef<GetElementPtrInst *> GEPList(&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, they are marked as deleted, so remove |
| // them from the set of candidates. |
| Candidates.remove_if( |
| [&R](Value *I) { return R.isDeleted(cast<Instruction>(I)); }); |
| |
| // 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 = 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 = GEPList[J]; |
| auto *SCEVJ = SE->getSCEV(GEPList[J]); |
| if (isa<SCEVConstant>(SE->getMinusSCEV(SCEVI, SCEVJ))) { |
| Candidates.remove(GEPI); |
| Candidates.remove(GEPJ); |
| } else if (GEPI->idx_begin()->get() == GEPJ->idx_begin()->get()) { |
| Candidates.remove(GEPJ); |
| } |
| } |
| } |
| |
| // 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; |
| // Sort by type, base pointers and values operand. Value operands must be |
| // compatible (have the same opcode, same parent), otherwise it is |
| // definitely not profitable to try to vectorize them. |
| auto &&StoreSorter = [this](StoreInst *V, StoreInst *V2) { |
| if (V->getPointerOperandType()->getTypeID() < |
| V2->getPointerOperandType()->getTypeID()) |
| return true; |
| if (V->getPointerOperandType()->getTypeID() > |
| V2->getPointerOperandType()->getTypeID()) |
| return false; |
| // UndefValues are compatible with all other values. |
| if (isa<UndefValue>(V->getValueOperand()) || |
| isa<UndefValue>(V2->getValueOperand())) |
| return false; |
| if (auto *I1 = dyn_cast<Instruction>(V->getValueOperand())) |
| if (auto *I2 = dyn_cast<Instruction>(V2->getValueOperand())) { |
| DomTreeNodeBase<llvm::BasicBlock> *NodeI1 = |
| DT->getNode(I1->getParent()); |
| DomTreeNodeBase<llvm::BasicBlock> *NodeI2 = |
| DT->getNode(I2->getParent()); |
| assert(NodeI1 && "Should only process reachable instructions"); |
| assert(NodeI1 && "Should only process reachable instructions"); |
| assert((NodeI1 == NodeI2) == |
| (NodeI1->getDFSNumIn() == NodeI2->getDFSNumIn()) && |
| "Different nodes should have different DFS numbers"); |
| if (NodeI1 != NodeI2) |
| return NodeI1->getDFSNumIn() < NodeI2->getDFSNumIn(); |
| InstructionsState S = getSameOpcode({I1, I2}); |
| if (S.getOpcode()) |
| return false; |
| return I1->getOpcode() < I2->getOpcode(); |
| } |
| if (isa<Constant>(V->getValueOperand()) && |
| isa<Constant>(V2->getValueOperand())) |
| return false; |
| return V->getValueOperand()->getValueID() < |
| V2->getValueOperand()->getValueID(); |
| }; |
| |
| auto &&AreCompatibleStores = [](StoreInst *V1, StoreInst *V2) { |
| if (V1 == V2) |
| return true; |
| if (V1->getPointerOperandType() != V2->getPointerOperandType()) |
| return false; |
| // Undefs are compatible with any other value. |
| if (isa<UndefValue>(V1->getValueOperand()) || |
| isa<UndefValue>(V2->getValueOperand())) |
| return true; |
| if (auto *I1 = dyn_cast<Instruction>(V1->getValueOperand())) |
| if (auto *I2 = dyn_cast<Instruction>(V2->getValueOperand())) { |
| if (I1->getParent() != I2->getParent()) |
| return false; |
| InstructionsState S = getSameOpcode({I1, I2}); |
| return S.getOpcode() > 0; |
| } |
| if (isa<Constant>(V1->getValueOperand()) && |
| isa<Constant>(V2->getValueOperand())) |
| return true; |
| return V1->getValueOperand()->getValueID() == |
| V2->getValueOperand()->getValueID(); |
| }; |
| auto Limit = [&R, this](StoreInst *SI) { |
| unsigned EltSize = DL->getTypeSizeInBits(SI->getValueOperand()->getType()); |
| return R.getMinVF(EltSize); |
| }; |
| |
| // Attempt to sort and vectorize each of the store-groups. |
| for (auto &Pair : Stores) { |
| if (Pair.second.size() < 2) |
| continue; |
| |
| LLVM_DEBUG(dbgs() << "SLP: Analyzing a store chain of length " |
| << Pair.second.size() << ".\n"); |
| |
| if (!isValidElementType(Pair.second.front()->getValueOperand()->getType())) |
| continue; |
| |
| Changed |= tryToVectorizeSequence<StoreInst>( |
| Pair.second, Limit, StoreSorter, AreCompatibleStores, |
| [this, &R](ArrayRef<StoreInst *> Candidates, bool) { |
| return vectorizeStores(Candidates, R); |
| }, |
| /*LimitForRegisterSize=*/false); |
| } |
| 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_DEPENDENCY(InjectTLIMappingsLegacy) |
| INITIALIZE_PASS_END(SLPVectorizer, SV_NAME, lv_name, false, false) |
| |
| Pass *llvm::createSLPVectorizerPass() { return new SLPVectorizer(); } |