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77d21dcd3f
Arm MVE has multiple instructions such as VMLAVA.s8, which (in this case) can take two 128bit vectors, sign extend the inputs to i32, multiplying them together and sum the result into a 32bit general purpose register. So taking 16 i8's as inputs, they can multiply and accumulate the result into a single i32 without any rounding/truncating along the way. There are also reduction instructions for plain integer add and min/max, and operations that sum into a pair of 32bit registers together treated as a 64bit integer (even though MVE does not have a plain 64bit addition instruction). So giving the vectorizer the ability to use these instructions both enables us to vectorize at higher bitwidths, and to vectorize things we previously could not. In order to do that we need a way to represent that the reduction operation, specified with a llvm.experimental.vector.reduce when vectorizing for Arm, occurs inside the loop not after it like most reductions. This patch attempts to do that, teaching the vectorizer about in-loop reductions. It does this through a vplan recipe representing the reductions that the original chain of reduction operations is replaced by. Cost modelling is currently just done through a prefersInloopReduction TTI hook (which follows in a later patch). Differential Revision: https://reviews.llvm.org/D75069
1197 lines
45 KiB
C++
1197 lines
45 KiB
C++
//===- llvm/Analysis/IVDescriptors.cpp - IndVar Descriptors -----*- C++ -*-===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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// This file "describes" induction and recurrence variables.
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/Analysis/IVDescriptors.h"
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#include "llvm/ADT/ScopeExit.h"
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#include "llvm/Analysis/AliasAnalysis.h"
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#include "llvm/Analysis/BasicAliasAnalysis.h"
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#include "llvm/Analysis/DemandedBits.h"
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#include "llvm/Analysis/DomTreeUpdater.h"
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#include "llvm/Analysis/GlobalsModRef.h"
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#include "llvm/Analysis/InstructionSimplify.h"
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#include "llvm/Analysis/LoopInfo.h"
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#include "llvm/Analysis/LoopPass.h"
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#include "llvm/Analysis/MustExecute.h"
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#include "llvm/Analysis/ScalarEvolution.h"
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#include "llvm/Analysis/ScalarEvolutionAliasAnalysis.h"
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#include "llvm/Analysis/ScalarEvolutionExpressions.h"
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#include "llvm/Analysis/TargetTransformInfo.h"
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#include "llvm/Analysis/ValueTracking.h"
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#include "llvm/IR/Dominators.h"
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#include "llvm/IR/Instructions.h"
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#include "llvm/IR/Module.h"
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#include "llvm/IR/PatternMatch.h"
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#include "llvm/IR/ValueHandle.h"
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#include "llvm/Pass.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/KnownBits.h"
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using namespace llvm;
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using namespace llvm::PatternMatch;
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#define DEBUG_TYPE "iv-descriptors"
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bool RecurrenceDescriptor::areAllUsesIn(Instruction *I,
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SmallPtrSetImpl<Instruction *> &Set) {
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for (User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use)
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if (!Set.count(dyn_cast<Instruction>(*Use)))
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return false;
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return true;
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}
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bool RecurrenceDescriptor::isIntegerRecurrenceKind(RecurrenceKind Kind) {
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switch (Kind) {
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default:
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break;
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case RK_IntegerAdd:
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case RK_IntegerMult:
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case RK_IntegerOr:
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case RK_IntegerAnd:
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case RK_IntegerXor:
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case RK_IntegerMinMax:
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return true;
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}
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return false;
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}
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bool RecurrenceDescriptor::isFloatingPointRecurrenceKind(RecurrenceKind Kind) {
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return (Kind != RK_NoRecurrence) && !isIntegerRecurrenceKind(Kind);
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}
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bool RecurrenceDescriptor::isArithmeticRecurrenceKind(RecurrenceKind Kind) {
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switch (Kind) {
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default:
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break;
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case RK_IntegerAdd:
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case RK_IntegerMult:
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case RK_FloatAdd:
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case RK_FloatMult:
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return true;
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}
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return false;
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}
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/// Determines if Phi may have been type-promoted. If Phi has a single user
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/// that ANDs the Phi with a type mask, return the user. RT is updated to
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/// account for the narrower bit width represented by the mask, and the AND
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/// instruction is added to CI.
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static Instruction *lookThroughAnd(PHINode *Phi, Type *&RT,
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SmallPtrSetImpl<Instruction *> &Visited,
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SmallPtrSetImpl<Instruction *> &CI) {
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if (!Phi->hasOneUse())
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return Phi;
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const APInt *M = nullptr;
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Instruction *I, *J = cast<Instruction>(Phi->use_begin()->getUser());
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// Matches either I & 2^x-1 or 2^x-1 & I. If we find a match, we update RT
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// with a new integer type of the corresponding bit width.
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if (match(J, m_c_And(m_Instruction(I), m_APInt(M)))) {
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int32_t Bits = (*M + 1).exactLogBase2();
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if (Bits > 0) {
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RT = IntegerType::get(Phi->getContext(), Bits);
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Visited.insert(Phi);
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CI.insert(J);
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return J;
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}
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}
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return Phi;
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}
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/// Compute the minimal bit width needed to represent a reduction whose exit
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/// instruction is given by Exit.
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static std::pair<Type *, bool> computeRecurrenceType(Instruction *Exit,
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DemandedBits *DB,
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AssumptionCache *AC,
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DominatorTree *DT) {
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bool IsSigned = false;
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const DataLayout &DL = Exit->getModule()->getDataLayout();
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uint64_t MaxBitWidth = DL.getTypeSizeInBits(Exit->getType());
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if (DB) {
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// Use the demanded bits analysis to determine the bits that are live out
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// of the exit instruction, rounding up to the nearest power of two. If the
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// use of demanded bits results in a smaller bit width, we know the value
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// must be positive (i.e., IsSigned = false), because if this were not the
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// case, the sign bit would have been demanded.
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auto Mask = DB->getDemandedBits(Exit);
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MaxBitWidth = Mask.getBitWidth() - Mask.countLeadingZeros();
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}
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if (MaxBitWidth == DL.getTypeSizeInBits(Exit->getType()) && AC && DT) {
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// If demanded bits wasn't able to limit the bit width, we can try to use
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// value tracking instead. This can be the case, for example, if the value
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// may be negative.
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auto NumSignBits = ComputeNumSignBits(Exit, DL, 0, AC, nullptr, DT);
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auto NumTypeBits = DL.getTypeSizeInBits(Exit->getType());
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MaxBitWidth = NumTypeBits - NumSignBits;
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KnownBits Bits = computeKnownBits(Exit, DL);
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if (!Bits.isNonNegative()) {
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// If the value is not known to be non-negative, we set IsSigned to true,
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// meaning that we will use sext instructions instead of zext
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// instructions to restore the original type.
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IsSigned = true;
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if (!Bits.isNegative())
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// If the value is not known to be negative, we don't known what the
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// upper bit is, and therefore, we don't know what kind of extend we
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// will need. In this case, just increase the bit width by one bit and
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// use sext.
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++MaxBitWidth;
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}
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}
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if (!isPowerOf2_64(MaxBitWidth))
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MaxBitWidth = NextPowerOf2(MaxBitWidth);
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return std::make_pair(Type::getIntNTy(Exit->getContext(), MaxBitWidth),
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IsSigned);
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}
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/// Collect cast instructions that can be ignored in the vectorizer's cost
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/// model, given a reduction exit value and the minimal type in which the
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/// reduction can be represented.
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static void collectCastsToIgnore(Loop *TheLoop, Instruction *Exit,
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Type *RecurrenceType,
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SmallPtrSetImpl<Instruction *> &Casts) {
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SmallVector<Instruction *, 8> Worklist;
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SmallPtrSet<Instruction *, 8> Visited;
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Worklist.push_back(Exit);
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while (!Worklist.empty()) {
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Instruction *Val = Worklist.pop_back_val();
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Visited.insert(Val);
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if (auto *Cast = dyn_cast<CastInst>(Val))
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if (Cast->getSrcTy() == RecurrenceType) {
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// If the source type of a cast instruction is equal to the recurrence
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// type, it will be eliminated, and should be ignored in the vectorizer
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// cost model.
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Casts.insert(Cast);
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continue;
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}
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// Add all operands to the work list if they are loop-varying values that
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// we haven't yet visited.
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for (Value *O : cast<User>(Val)->operands())
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if (auto *I = dyn_cast<Instruction>(O))
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if (TheLoop->contains(I) && !Visited.count(I))
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Worklist.push_back(I);
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}
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}
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bool RecurrenceDescriptor::AddReductionVar(PHINode *Phi, RecurrenceKind Kind,
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Loop *TheLoop, bool HasFunNoNaNAttr,
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RecurrenceDescriptor &RedDes,
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DemandedBits *DB,
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AssumptionCache *AC,
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DominatorTree *DT) {
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if (Phi->getNumIncomingValues() != 2)
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return false;
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// Reduction variables are only found in the loop header block.
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if (Phi->getParent() != TheLoop->getHeader())
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return false;
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// Obtain the reduction start value from the value that comes from the loop
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// preheader.
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Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader());
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// ExitInstruction is the single value which is used outside the loop.
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// We only allow for a single reduction value to be used outside the loop.
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// This includes users of the reduction, variables (which form a cycle
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// which ends in the phi node).
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Instruction *ExitInstruction = nullptr;
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// Indicates that we found a reduction operation in our scan.
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bool FoundReduxOp = false;
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// We start with the PHI node and scan for all of the users of this
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// instruction. All users must be instructions that can be used as reduction
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// variables (such as ADD). We must have a single out-of-block user. The cycle
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// must include the original PHI.
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bool FoundStartPHI = false;
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// To recognize min/max patterns formed by a icmp select sequence, we store
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// the number of instruction we saw from the recognized min/max pattern,
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// to make sure we only see exactly the two instructions.
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unsigned NumCmpSelectPatternInst = 0;
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InstDesc ReduxDesc(false, nullptr);
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// Data used for determining if the recurrence has been type-promoted.
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Type *RecurrenceType = Phi->getType();
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SmallPtrSet<Instruction *, 4> CastInsts;
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Instruction *Start = Phi;
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bool IsSigned = false;
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SmallPtrSet<Instruction *, 8> VisitedInsts;
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SmallVector<Instruction *, 8> Worklist;
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// Return early if the recurrence kind does not match the type of Phi. If the
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// recurrence kind is arithmetic, we attempt to look through AND operations
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// resulting from the type promotion performed by InstCombine. Vector
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// operations are not limited to the legal integer widths, so we may be able
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// to evaluate the reduction in the narrower width.
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if (RecurrenceType->isFloatingPointTy()) {
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if (!isFloatingPointRecurrenceKind(Kind))
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return false;
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} else {
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if (!isIntegerRecurrenceKind(Kind))
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return false;
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if (isArithmeticRecurrenceKind(Kind))
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Start = lookThroughAnd(Phi, RecurrenceType, VisitedInsts, CastInsts);
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}
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Worklist.push_back(Start);
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VisitedInsts.insert(Start);
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// Start with all flags set because we will intersect this with the reduction
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// flags from all the reduction operations.
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FastMathFlags FMF = FastMathFlags::getFast();
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// A value in the reduction can be used:
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// - By the reduction:
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// - Reduction operation:
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// - One use of reduction value (safe).
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// - Multiple use of reduction value (not safe).
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// - PHI:
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// - All uses of the PHI must be the reduction (safe).
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// - Otherwise, not safe.
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// - By instructions outside of the loop (safe).
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// * One value may have several outside users, but all outside
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// uses must be of the same value.
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// - By an instruction that is not part of the reduction (not safe).
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// This is either:
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// * An instruction type other than PHI or the reduction operation.
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// * A PHI in the header other than the initial PHI.
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while (!Worklist.empty()) {
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Instruction *Cur = Worklist.back();
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Worklist.pop_back();
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// No Users.
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// If the instruction has no users then this is a broken chain and can't be
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// a reduction variable.
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if (Cur->use_empty())
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return false;
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bool IsAPhi = isa<PHINode>(Cur);
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// A header PHI use other than the original PHI.
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if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent())
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return false;
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// Reductions of instructions such as Div, and Sub is only possible if the
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// LHS is the reduction variable.
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if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) &&
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!isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) &&
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!VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0))))
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return false;
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// Any reduction instruction must be of one of the allowed kinds. We ignore
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// the starting value (the Phi or an AND instruction if the Phi has been
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// type-promoted).
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if (Cur != Start) {
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ReduxDesc = isRecurrenceInstr(Cur, Kind, ReduxDesc, HasFunNoNaNAttr);
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if (!ReduxDesc.isRecurrence())
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return false;
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// FIXME: FMF is allowed on phi, but propagation is not handled correctly.
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if (isa<FPMathOperator>(ReduxDesc.getPatternInst()) && !IsAPhi)
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FMF &= ReduxDesc.getPatternInst()->getFastMathFlags();
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}
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bool IsASelect = isa<SelectInst>(Cur);
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// A conditional reduction operation must only have 2 or less uses in
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// VisitedInsts.
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if (IsASelect && (Kind == RK_FloatAdd || Kind == RK_FloatMult) &&
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hasMultipleUsesOf(Cur, VisitedInsts, 2))
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return false;
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// A reduction operation must only have one use of the reduction value.
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if (!IsAPhi && !IsASelect && Kind != RK_IntegerMinMax &&
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Kind != RK_FloatMinMax && hasMultipleUsesOf(Cur, VisitedInsts, 1))
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return false;
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// All inputs to a PHI node must be a reduction value.
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if (IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts))
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return false;
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if (Kind == RK_IntegerMinMax &&
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(isa<ICmpInst>(Cur) || isa<SelectInst>(Cur)))
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++NumCmpSelectPatternInst;
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if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) || isa<SelectInst>(Cur)))
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++NumCmpSelectPatternInst;
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// Check whether we found a reduction operator.
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FoundReduxOp |= !IsAPhi && Cur != Start;
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// Process users of current instruction. Push non-PHI nodes after PHI nodes
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// onto the stack. This way we are going to have seen all inputs to PHI
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// nodes once we get to them.
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SmallVector<Instruction *, 8> NonPHIs;
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SmallVector<Instruction *, 8> PHIs;
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for (User *U : Cur->users()) {
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Instruction *UI = cast<Instruction>(U);
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// Check if we found the exit user.
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BasicBlock *Parent = UI->getParent();
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if (!TheLoop->contains(Parent)) {
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// If we already know this instruction is used externally, move on to
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// the next user.
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if (ExitInstruction == Cur)
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continue;
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// Exit if you find multiple values used outside or if the header phi
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// node is being used. In this case the user uses the value of the
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// previous iteration, in which case we would loose "VF-1" iterations of
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// the reduction operation if we vectorize.
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if (ExitInstruction != nullptr || Cur == Phi)
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return false;
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// The instruction used by an outside user must be the last instruction
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// before we feed back to the reduction phi. Otherwise, we loose VF-1
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// operations on the value.
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if (!is_contained(Phi->operands(), Cur))
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return false;
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ExitInstruction = Cur;
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continue;
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}
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// Process instructions only once (termination). Each reduction cycle
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// value must only be used once, except by phi nodes and min/max
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// reductions which are represented as a cmp followed by a select.
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InstDesc IgnoredVal(false, nullptr);
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if (VisitedInsts.insert(UI).second) {
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if (isa<PHINode>(UI))
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PHIs.push_back(UI);
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else
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NonPHIs.push_back(UI);
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} else if (!isa<PHINode>(UI) &&
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((!isa<FCmpInst>(UI) && !isa<ICmpInst>(UI) &&
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!isa<SelectInst>(UI)) ||
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(!isConditionalRdxPattern(Kind, UI).isRecurrence() &&
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!isMinMaxSelectCmpPattern(UI, IgnoredVal).isRecurrence())))
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return false;
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// Remember that we completed the cycle.
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if (UI == Phi)
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FoundStartPHI = true;
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}
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Worklist.append(PHIs.begin(), PHIs.end());
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Worklist.append(NonPHIs.begin(), NonPHIs.end());
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}
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// This means we have seen one but not the other instruction of the
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// pattern or more than just a select and cmp.
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if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) &&
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NumCmpSelectPatternInst != 2)
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return false;
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if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction)
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return false;
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if (Start != Phi) {
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// If the starting value is not the same as the phi node, we speculatively
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// looked through an 'and' instruction when evaluating a potential
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// arithmetic reduction to determine if it may have been type-promoted.
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//
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// We now compute the minimal bit width that is required to represent the
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// reduction. If this is the same width that was indicated by the 'and', we
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// can represent the reduction in the smaller type. The 'and' instruction
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// will be eliminated since it will essentially be a cast instruction that
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// can be ignore in the cost model. If we compute a different type than we
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// did when evaluating the 'and', the 'and' will not be eliminated, and we
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// will end up with different kinds of operations in the recurrence
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// expression (e.g., RK_IntegerAND, RK_IntegerADD). We give up if this is
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// the case.
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//
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// The vectorizer relies on InstCombine to perform the actual
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// type-shrinking. It does this by inserting instructions to truncate the
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// exit value of the reduction to the width indicated by RecurrenceType and
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// then extend this value back to the original width. If IsSigned is false,
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// a 'zext' instruction will be generated; otherwise, a 'sext' will be
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// used.
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//
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// TODO: We should not rely on InstCombine to rewrite the reduction in the
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// smaller type. We should just generate a correctly typed expression
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// to begin with.
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Type *ComputedType;
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std::tie(ComputedType, IsSigned) =
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computeRecurrenceType(ExitInstruction, DB, AC, DT);
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if (ComputedType != RecurrenceType)
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return false;
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// The recurrence expression will be represented in a narrower type. If
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// there are any cast instructions that will be unnecessary, collect them
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// in CastInsts. Note that the 'and' instruction was already included in
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// this list.
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//
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// TODO: A better way to represent this may be to tag in some way all the
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// instructions that are a part of the reduction. The vectorizer cost
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// model could then apply the recurrence type to these instructions,
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// without needing a white list of instructions to ignore.
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// This may also be useful for the inloop reductions, if it can be
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// kept simple enough.
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collectCastsToIgnore(TheLoop, ExitInstruction, RecurrenceType, CastInsts);
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}
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|
|
// We found a reduction var if we have reached the original phi node and we
|
|
// only have a single instruction with out-of-loop users.
|
|
|
|
// The ExitInstruction(Instruction which is allowed to have out-of-loop users)
|
|
// is saved as part of the RecurrenceDescriptor.
|
|
|
|
// Save the description of this reduction variable.
|
|
RecurrenceDescriptor RD(
|
|
RdxStart, ExitInstruction, Kind, FMF, ReduxDesc.getMinMaxKind(),
|
|
ReduxDesc.getUnsafeAlgebraInst(), RecurrenceType, IsSigned, CastInsts);
|
|
RedDes = RD;
|
|
|
|
return true;
|
|
}
|
|
|
|
/// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
|
|
/// pattern corresponding to a min(X, Y) or max(X, Y).
|
|
RecurrenceDescriptor::InstDesc
|
|
RecurrenceDescriptor::isMinMaxSelectCmpPattern(Instruction *I, InstDesc &Prev) {
|
|
|
|
assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) &&
|
|
"Expect a select instruction");
|
|
Instruction *Cmp = nullptr;
|
|
SelectInst *Select = nullptr;
|
|
|
|
// We must handle the select(cmp()) as a single instruction. Advance to the
|
|
// select.
|
|
if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) {
|
|
if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->user_begin())))
|
|
return InstDesc(false, I);
|
|
return InstDesc(Select, Prev.getMinMaxKind());
|
|
}
|
|
|
|
// Only handle single use cases for now.
|
|
if (!(Select = dyn_cast<SelectInst>(I)))
|
|
return InstDesc(false, I);
|
|
if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) &&
|
|
!(Cmp = dyn_cast<FCmpInst>(I->getOperand(0))))
|
|
return InstDesc(false, I);
|
|
if (!Cmp->hasOneUse())
|
|
return InstDesc(false, I);
|
|
|
|
Value *CmpLeft;
|
|
Value *CmpRight;
|
|
|
|
// Look for a min/max pattern.
|
|
if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return InstDesc(Select, MRK_UIntMin);
|
|
else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return InstDesc(Select, MRK_UIntMax);
|
|
else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return InstDesc(Select, MRK_SIntMax);
|
|
else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return InstDesc(Select, MRK_SIntMin);
|
|
else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return InstDesc(Select, MRK_FloatMin);
|
|
else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return InstDesc(Select, MRK_FloatMax);
|
|
else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return InstDesc(Select, MRK_FloatMin);
|
|
else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return InstDesc(Select, MRK_FloatMax);
|
|
|
|
return InstDesc(false, I);
|
|
}
|
|
|
|
/// Returns true if the select instruction has users in the compare-and-add
|
|
/// reduction pattern below. The select instruction argument is the last one
|
|
/// in the sequence.
|
|
///
|
|
/// %sum.1 = phi ...
|
|
/// ...
|
|
/// %cmp = fcmp pred %0, %CFP
|
|
/// %add = fadd %0, %sum.1
|
|
/// %sum.2 = select %cmp, %add, %sum.1
|
|
RecurrenceDescriptor::InstDesc
|
|
RecurrenceDescriptor::isConditionalRdxPattern(
|
|
RecurrenceKind Kind, Instruction *I) {
|
|
SelectInst *SI = dyn_cast<SelectInst>(I);
|
|
if (!SI)
|
|
return InstDesc(false, I);
|
|
|
|
CmpInst *CI = dyn_cast<CmpInst>(SI->getCondition());
|
|
// Only handle single use cases for now.
|
|
if (!CI || !CI->hasOneUse())
|
|
return InstDesc(false, I);
|
|
|
|
Value *TrueVal = SI->getTrueValue();
|
|
Value *FalseVal = SI->getFalseValue();
|
|
// Handle only when either of operands of select instruction is a PHI
|
|
// node for now.
|
|
if ((isa<PHINode>(*TrueVal) && isa<PHINode>(*FalseVal)) ||
|
|
(!isa<PHINode>(*TrueVal) && !isa<PHINode>(*FalseVal)))
|
|
return InstDesc(false, I);
|
|
|
|
Instruction *I1 =
|
|
isa<PHINode>(*TrueVal) ? dyn_cast<Instruction>(FalseVal)
|
|
: dyn_cast<Instruction>(TrueVal);
|
|
if (!I1 || !I1->isBinaryOp())
|
|
return InstDesc(false, I);
|
|
|
|
Value *Op1, *Op2;
|
|
if ((m_FAdd(m_Value(Op1), m_Value(Op2)).match(I1) ||
|
|
m_FSub(m_Value(Op1), m_Value(Op2)).match(I1)) &&
|
|
I1->isFast())
|
|
return InstDesc(Kind == RK_FloatAdd, SI);
|
|
|
|
if (m_FMul(m_Value(Op1), m_Value(Op2)).match(I1) && (I1->isFast()))
|
|
return InstDesc(Kind == RK_FloatMult, SI);
|
|
|
|
return InstDesc(false, I);
|
|
}
|
|
|
|
RecurrenceDescriptor::InstDesc
|
|
RecurrenceDescriptor::isRecurrenceInstr(Instruction *I, RecurrenceKind Kind,
|
|
InstDesc &Prev, bool HasFunNoNaNAttr) {
|
|
Instruction *UAI = Prev.getUnsafeAlgebraInst();
|
|
if (!UAI && isa<FPMathOperator>(I) && !I->hasAllowReassoc())
|
|
UAI = I; // Found an unsafe (unvectorizable) algebra instruction.
|
|
|
|
switch (I->getOpcode()) {
|
|
default:
|
|
return InstDesc(false, I);
|
|
case Instruction::PHI:
|
|
return InstDesc(I, Prev.getMinMaxKind(), Prev.getUnsafeAlgebraInst());
|
|
case Instruction::Sub:
|
|
case Instruction::Add:
|
|
return InstDesc(Kind == RK_IntegerAdd, I);
|
|
case Instruction::Mul:
|
|
return InstDesc(Kind == RK_IntegerMult, I);
|
|
case Instruction::And:
|
|
return InstDesc(Kind == RK_IntegerAnd, I);
|
|
case Instruction::Or:
|
|
return InstDesc(Kind == RK_IntegerOr, I);
|
|
case Instruction::Xor:
|
|
return InstDesc(Kind == RK_IntegerXor, I);
|
|
case Instruction::FMul:
|
|
return InstDesc(Kind == RK_FloatMult, I, UAI);
|
|
case Instruction::FSub:
|
|
case Instruction::FAdd:
|
|
return InstDesc(Kind == RK_FloatAdd, I, UAI);
|
|
case Instruction::Select:
|
|
if (Kind == RK_FloatAdd || Kind == RK_FloatMult)
|
|
return isConditionalRdxPattern(Kind, I);
|
|
LLVM_FALLTHROUGH;
|
|
case Instruction::FCmp:
|
|
case Instruction::ICmp:
|
|
if (Kind != RK_IntegerMinMax &&
|
|
(!HasFunNoNaNAttr || Kind != RK_FloatMinMax))
|
|
return InstDesc(false, I);
|
|
return isMinMaxSelectCmpPattern(I, Prev);
|
|
}
|
|
}
|
|
|
|
bool RecurrenceDescriptor::hasMultipleUsesOf(
|
|
Instruction *I, SmallPtrSetImpl<Instruction *> &Insts,
|
|
unsigned MaxNumUses) {
|
|
unsigned NumUses = 0;
|
|
for (User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E;
|
|
++Use) {
|
|
if (Insts.count(dyn_cast<Instruction>(*Use)))
|
|
++NumUses;
|
|
if (NumUses > MaxNumUses)
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
bool RecurrenceDescriptor::isReductionPHI(PHINode *Phi, Loop *TheLoop,
|
|
RecurrenceDescriptor &RedDes,
|
|
DemandedBits *DB, AssumptionCache *AC,
|
|
DominatorTree *DT) {
|
|
|
|
BasicBlock *Header = TheLoop->getHeader();
|
|
Function &F = *Header->getParent();
|
|
bool HasFunNoNaNAttr =
|
|
F.getFnAttribute("no-nans-fp-math").getValueAsString() == "true";
|
|
|
|
if (AddReductionVar(Phi, RK_IntegerAdd, TheLoop, HasFunNoNaNAttr, RedDes, DB,
|
|
AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found an ADD reduction PHI." << *Phi << "\n");
|
|
return true;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerMult, TheLoop, HasFunNoNaNAttr, RedDes, DB,
|
|
AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found a MUL reduction PHI." << *Phi << "\n");
|
|
return true;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerOr, TheLoop, HasFunNoNaNAttr, RedDes, DB,
|
|
AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found an OR reduction PHI." << *Phi << "\n");
|
|
return true;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerAnd, TheLoop, HasFunNoNaNAttr, RedDes, DB,
|
|
AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found an AND reduction PHI." << *Phi << "\n");
|
|
return true;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerXor, TheLoop, HasFunNoNaNAttr, RedDes, DB,
|
|
AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found a XOR reduction PHI." << *Phi << "\n");
|
|
return true;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerMinMax, TheLoop, HasFunNoNaNAttr, RedDes,
|
|
DB, AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found a MINMAX reduction PHI." << *Phi << "\n");
|
|
return true;
|
|
}
|
|
if (AddReductionVar(Phi, RK_FloatMult, TheLoop, HasFunNoNaNAttr, RedDes, DB,
|
|
AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found an FMult reduction PHI." << *Phi << "\n");
|
|
return true;
|
|
}
|
|
if (AddReductionVar(Phi, RK_FloatAdd, TheLoop, HasFunNoNaNAttr, RedDes, DB,
|
|
AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found an FAdd reduction PHI." << *Phi << "\n");
|
|
return true;
|
|
}
|
|
if (AddReductionVar(Phi, RK_FloatMinMax, TheLoop, HasFunNoNaNAttr, RedDes, DB,
|
|
AC, DT)) {
|
|
LLVM_DEBUG(dbgs() << "Found an float MINMAX reduction PHI." << *Phi
|
|
<< "\n");
|
|
return true;
|
|
}
|
|
// Not a reduction of known type.
|
|
return false;
|
|
}
|
|
|
|
bool RecurrenceDescriptor::isFirstOrderRecurrence(
|
|
PHINode *Phi, Loop *TheLoop,
|
|
DenseMap<Instruction *, Instruction *> &SinkAfter, DominatorTree *DT) {
|
|
|
|
// Ensure the phi node is in the loop header and has two incoming values.
|
|
if (Phi->getParent() != TheLoop->getHeader() ||
|
|
Phi->getNumIncomingValues() != 2)
|
|
return false;
|
|
|
|
// Ensure the loop has a preheader and a single latch block. The loop
|
|
// vectorizer will need the latch to set up the next iteration of the loop.
|
|
auto *Preheader = TheLoop->getLoopPreheader();
|
|
auto *Latch = TheLoop->getLoopLatch();
|
|
if (!Preheader || !Latch)
|
|
return false;
|
|
|
|
// Ensure the phi node's incoming blocks are the loop preheader and latch.
|
|
if (Phi->getBasicBlockIndex(Preheader) < 0 ||
|
|
Phi->getBasicBlockIndex(Latch) < 0)
|
|
return false;
|
|
|
|
// Get the previous value. The previous value comes from the latch edge while
|
|
// the initial value comes form the preheader edge.
|
|
auto *Previous = dyn_cast<Instruction>(Phi->getIncomingValueForBlock(Latch));
|
|
if (!Previous || !TheLoop->contains(Previous) || isa<PHINode>(Previous) ||
|
|
SinkAfter.count(Previous)) // Cannot rely on dominance due to motion.
|
|
return false;
|
|
|
|
// Ensure every user of the phi node is dominated by the previous value.
|
|
// The dominance requirement ensures the loop vectorizer will not need to
|
|
// vectorize the initial value prior to the first iteration of the loop.
|
|
// TODO: Consider extending this sinking to handle memory instructions and
|
|
// phis with multiple users.
|
|
|
|
// Returns true, if all users of I are dominated by DominatedBy.
|
|
auto allUsesDominatedBy = [DT](Instruction *I, Instruction *DominatedBy) {
|
|
return all_of(I->uses(), [DT, DominatedBy](Use &U) {
|
|
return DT->dominates(DominatedBy, U);
|
|
});
|
|
};
|
|
|
|
if (Phi->hasOneUse()) {
|
|
Instruction *I = Phi->user_back();
|
|
|
|
// If the user of the PHI is also the incoming value, we potentially have a
|
|
// reduction and which cannot be handled by sinking.
|
|
if (Previous == I)
|
|
return false;
|
|
|
|
// We cannot sink terminator instructions.
|
|
if (I->getParent()->getTerminator() == I)
|
|
return false;
|
|
|
|
// Do not try to sink an instruction multiple times (if multiple operands
|
|
// are first order recurrences).
|
|
// TODO: We can support this case, by sinking the instruction after the
|
|
// 'deepest' previous instruction.
|
|
if (SinkAfter.find(I) != SinkAfter.end())
|
|
return false;
|
|
|
|
if (DT->dominates(Previous, I)) // We already are good w/o sinking.
|
|
return true;
|
|
|
|
// We can sink any instruction without side effects, as long as all users
|
|
// are dominated by the instruction we are sinking after.
|
|
if (I->getParent() == Phi->getParent() && !I->mayHaveSideEffects() &&
|
|
allUsesDominatedBy(I, Previous)) {
|
|
SinkAfter[I] = Previous;
|
|
return true;
|
|
}
|
|
}
|
|
|
|
return allUsesDominatedBy(Phi, Previous);
|
|
}
|
|
|
|
/// This function returns the identity element (or neutral element) for
|
|
/// the operation K.
|
|
Constant *RecurrenceDescriptor::getRecurrenceIdentity(RecurrenceKind K,
|
|
Type *Tp) {
|
|
switch (K) {
|
|
case RK_IntegerXor:
|
|
case RK_IntegerAdd:
|
|
case RK_IntegerOr:
|
|
// Adding, Xoring, Oring zero to a number does not change it.
|
|
return ConstantInt::get(Tp, 0);
|
|
case RK_IntegerMult:
|
|
// Multiplying a number by 1 does not change it.
|
|
return ConstantInt::get(Tp, 1);
|
|
case RK_IntegerAnd:
|
|
// AND-ing a number with an all-1 value does not change it.
|
|
return ConstantInt::get(Tp, -1, true);
|
|
case RK_FloatMult:
|
|
// Multiplying a number by 1 does not change it.
|
|
return ConstantFP::get(Tp, 1.0L);
|
|
case RK_FloatAdd:
|
|
// Adding zero to a number does not change it.
|
|
return ConstantFP::get(Tp, 0.0L);
|
|
default:
|
|
llvm_unreachable("Unknown recurrence kind");
|
|
}
|
|
}
|
|
|
|
/// This function translates the recurrence kind to an LLVM binary operator.
|
|
unsigned RecurrenceDescriptor::getRecurrenceBinOp(RecurrenceKind Kind) {
|
|
switch (Kind) {
|
|
case RK_IntegerAdd:
|
|
return Instruction::Add;
|
|
case RK_IntegerMult:
|
|
return Instruction::Mul;
|
|
case RK_IntegerOr:
|
|
return Instruction::Or;
|
|
case RK_IntegerAnd:
|
|
return Instruction::And;
|
|
case RK_IntegerXor:
|
|
return Instruction::Xor;
|
|
case RK_FloatMult:
|
|
return Instruction::FMul;
|
|
case RK_FloatAdd:
|
|
return Instruction::FAdd;
|
|
case RK_IntegerMinMax:
|
|
return Instruction::ICmp;
|
|
case RK_FloatMinMax:
|
|
return Instruction::FCmp;
|
|
default:
|
|
llvm_unreachable("Unknown recurrence operation");
|
|
}
|
|
}
|
|
|
|
SmallVector<Instruction *, 4>
|
|
RecurrenceDescriptor::getReductionOpChain(PHINode *Phi, Loop *L) const {
|
|
SmallVector<Instruction *, 4> ReductionOperations;
|
|
unsigned RedOp = getRecurrenceBinOp(Kind);
|
|
|
|
// Search down from the Phi to the LoopExitInstr, looking for instructions
|
|
// with a single user of the correct type for the reduction.
|
|
|
|
// Note that we check that the type of the operand is correct for each item in
|
|
// the chain, including the last (the loop exit value). This can come up from
|
|
// sub, which would otherwise be treated as an add reduction. MinMax also need
|
|
// to check for a pair of icmp/select, for which we use getNextInstruction and
|
|
// isCorrectOpcode functions to step the right number of instruction, and
|
|
// check the icmp/select pair.
|
|
// FIXME: We also do not attempt to look through Phi/Select's yet, which might
|
|
// be part of the reduction chain, or attempt to looks through And's to find a
|
|
// smaller bitwidth. Subs are also currently not allowed (which are usually
|
|
// treated as part of a add reduction) as they are expected to generally be
|
|
// more expensive than out-of-loop reductions, and need to be costed more
|
|
// carefully.
|
|
unsigned ExpectedUses = 1;
|
|
if (RedOp == Instruction::ICmp || RedOp == Instruction::FCmp)
|
|
ExpectedUses = 2;
|
|
|
|
auto getNextInstruction = [&](Instruction *Cur) {
|
|
if (RedOp == Instruction::ICmp || RedOp == Instruction::FCmp) {
|
|
// We are expecting a icmp/select pair, which we go to the next select
|
|
// instruction if we can. We already know that Cur has 2 uses.
|
|
if (isa<SelectInst>(*Cur->user_begin()))
|
|
return cast<Instruction>(*Cur->user_begin());
|
|
else
|
|
return cast<Instruction>(*std::next(Cur->user_begin()));
|
|
}
|
|
return cast<Instruction>(*Cur->user_begin());
|
|
};
|
|
auto isCorrectOpcode = [&](Instruction *Cur) {
|
|
if (RedOp == Instruction::ICmp || RedOp == Instruction::FCmp) {
|
|
Value *LHS, *RHS;
|
|
return SelectPatternResult::isMinOrMax(
|
|
matchSelectPattern(Cur, LHS, RHS).Flavor);
|
|
}
|
|
return Cur->getOpcode() == RedOp;
|
|
};
|
|
|
|
// The loop exit instruction we check first (as a quick test) but add last. We
|
|
// check the opcode is correct (and dont allow them to be Subs) and that they
|
|
// have expected to have the expected number of uses. They will have one use
|
|
// from the phi and one from a LCSSA value, no matter the type.
|
|
if (!isCorrectOpcode(LoopExitInstr) || !LoopExitInstr->hasNUses(2))
|
|
return {};
|
|
|
|
// Check that the Phi has one (or two for min/max) uses.
|
|
if (!Phi->hasNUses(ExpectedUses))
|
|
return {};
|
|
Instruction *Cur = getNextInstruction(Phi);
|
|
|
|
// Each other instruction in the chain should have the expected number of uses
|
|
// and be the correct opcode.
|
|
while (Cur != LoopExitInstr) {
|
|
if (!isCorrectOpcode(Cur) || !Cur->hasNUses(ExpectedUses))
|
|
return {};
|
|
|
|
ReductionOperations.push_back(Cur);
|
|
Cur = getNextInstruction(Cur);
|
|
}
|
|
|
|
ReductionOperations.push_back(Cur);
|
|
return ReductionOperations;
|
|
}
|
|
|
|
InductionDescriptor::InductionDescriptor(Value *Start, InductionKind K,
|
|
const SCEV *Step, BinaryOperator *BOp,
|
|
SmallVectorImpl<Instruction *> *Casts)
|
|
: StartValue(Start), IK(K), Step(Step), InductionBinOp(BOp) {
|
|
assert(IK != IK_NoInduction && "Not an induction");
|
|
|
|
// Start value type should match the induction kind and the value
|
|
// itself should not be null.
|
|
assert(StartValue && "StartValue is null");
|
|
assert((IK != IK_PtrInduction || StartValue->getType()->isPointerTy()) &&
|
|
"StartValue is not a pointer for pointer induction");
|
|
assert((IK != IK_IntInduction || StartValue->getType()->isIntegerTy()) &&
|
|
"StartValue is not an integer for integer induction");
|
|
|
|
// Check the Step Value. It should be non-zero integer value.
|
|
assert((!getConstIntStepValue() || !getConstIntStepValue()->isZero()) &&
|
|
"Step value is zero");
|
|
|
|
assert((IK != IK_PtrInduction || getConstIntStepValue()) &&
|
|
"Step value should be constant for pointer induction");
|
|
assert((IK == IK_FpInduction || Step->getType()->isIntegerTy()) &&
|
|
"StepValue is not an integer");
|
|
|
|
assert((IK != IK_FpInduction || Step->getType()->isFloatingPointTy()) &&
|
|
"StepValue is not FP for FpInduction");
|
|
assert((IK != IK_FpInduction ||
|
|
(InductionBinOp &&
|
|
(InductionBinOp->getOpcode() == Instruction::FAdd ||
|
|
InductionBinOp->getOpcode() == Instruction::FSub))) &&
|
|
"Binary opcode should be specified for FP induction");
|
|
|
|
if (Casts) {
|
|
for (auto &Inst : *Casts) {
|
|
RedundantCasts.push_back(Inst);
|
|
}
|
|
}
|
|
}
|
|
|
|
int InductionDescriptor::getConsecutiveDirection() const {
|
|
ConstantInt *ConstStep = getConstIntStepValue();
|
|
if (ConstStep && (ConstStep->isOne() || ConstStep->isMinusOne()))
|
|
return ConstStep->getSExtValue();
|
|
return 0;
|
|
}
|
|
|
|
ConstantInt *InductionDescriptor::getConstIntStepValue() const {
|
|
if (isa<SCEVConstant>(Step))
|
|
return dyn_cast<ConstantInt>(cast<SCEVConstant>(Step)->getValue());
|
|
return nullptr;
|
|
}
|
|
|
|
bool InductionDescriptor::isFPInductionPHI(PHINode *Phi, const Loop *TheLoop,
|
|
ScalarEvolution *SE,
|
|
InductionDescriptor &D) {
|
|
|
|
// Here we only handle FP induction variables.
|
|
assert(Phi->getType()->isFloatingPointTy() && "Unexpected Phi type");
|
|
|
|
if (TheLoop->getHeader() != Phi->getParent())
|
|
return false;
|
|
|
|
// The loop may have multiple entrances or multiple exits; we can analyze
|
|
// this phi if it has a unique entry value and a unique backedge value.
|
|
if (Phi->getNumIncomingValues() != 2)
|
|
return false;
|
|
Value *BEValue = nullptr, *StartValue = nullptr;
|
|
if (TheLoop->contains(Phi->getIncomingBlock(0))) {
|
|
BEValue = Phi->getIncomingValue(0);
|
|
StartValue = Phi->getIncomingValue(1);
|
|
} else {
|
|
assert(TheLoop->contains(Phi->getIncomingBlock(1)) &&
|
|
"Unexpected Phi node in the loop");
|
|
BEValue = Phi->getIncomingValue(1);
|
|
StartValue = Phi->getIncomingValue(0);
|
|
}
|
|
|
|
BinaryOperator *BOp = dyn_cast<BinaryOperator>(BEValue);
|
|
if (!BOp)
|
|
return false;
|
|
|
|
Value *Addend = nullptr;
|
|
if (BOp->getOpcode() == Instruction::FAdd) {
|
|
if (BOp->getOperand(0) == Phi)
|
|
Addend = BOp->getOperand(1);
|
|
else if (BOp->getOperand(1) == Phi)
|
|
Addend = BOp->getOperand(0);
|
|
} else if (BOp->getOpcode() == Instruction::FSub)
|
|
if (BOp->getOperand(0) == Phi)
|
|
Addend = BOp->getOperand(1);
|
|
|
|
if (!Addend)
|
|
return false;
|
|
|
|
// The addend should be loop invariant
|
|
if (auto *I = dyn_cast<Instruction>(Addend))
|
|
if (TheLoop->contains(I))
|
|
return false;
|
|
|
|
// FP Step has unknown SCEV
|
|
const SCEV *Step = SE->getUnknown(Addend);
|
|
D = InductionDescriptor(StartValue, IK_FpInduction, Step, BOp);
|
|
return true;
|
|
}
|
|
|
|
/// This function is called when we suspect that the update-chain of a phi node
|
|
/// (whose symbolic SCEV expression sin \p PhiScev) contains redundant casts,
|
|
/// that can be ignored. (This can happen when the PSCEV rewriter adds a runtime
|
|
/// predicate P under which the SCEV expression for the phi can be the
|
|
/// AddRecurrence \p AR; See createAddRecFromPHIWithCast). We want to find the
|
|
/// cast instructions that are involved in the update-chain of this induction.
|
|
/// A caller that adds the required runtime predicate can be free to drop these
|
|
/// cast instructions, and compute the phi using \p AR (instead of some scev
|
|
/// expression with casts).
|
|
///
|
|
/// For example, without a predicate the scev expression can take the following
|
|
/// form:
|
|
/// (Ext ix (Trunc iy ( Start + i*Step ) to ix) to iy)
|
|
///
|
|
/// It corresponds to the following IR sequence:
|
|
/// %for.body:
|
|
/// %x = phi i64 [ 0, %ph ], [ %add, %for.body ]
|
|
/// %casted_phi = "ExtTrunc i64 %x"
|
|
/// %add = add i64 %casted_phi, %step
|
|
///
|
|
/// where %x is given in \p PN,
|
|
/// PSE.getSCEV(%x) is equal to PSE.getSCEV(%casted_phi) under a predicate,
|
|
/// and the IR sequence that "ExtTrunc i64 %x" represents can take one of
|
|
/// several forms, for example, such as:
|
|
/// ExtTrunc1: %casted_phi = and %x, 2^n-1
|
|
/// or:
|
|
/// ExtTrunc2: %t = shl %x, m
|
|
/// %casted_phi = ashr %t, m
|
|
///
|
|
/// If we are able to find such sequence, we return the instructions
|
|
/// we found, namely %casted_phi and the instructions on its use-def chain up
|
|
/// to the phi (not including the phi).
|
|
static bool getCastsForInductionPHI(PredicatedScalarEvolution &PSE,
|
|
const SCEVUnknown *PhiScev,
|
|
const SCEVAddRecExpr *AR,
|
|
SmallVectorImpl<Instruction *> &CastInsts) {
|
|
|
|
assert(CastInsts.empty() && "CastInsts is expected to be empty.");
|
|
auto *PN = cast<PHINode>(PhiScev->getValue());
|
|
assert(PSE.getSCEV(PN) == AR && "Unexpected phi node SCEV expression");
|
|
const Loop *L = AR->getLoop();
|
|
|
|
// Find any cast instructions that participate in the def-use chain of
|
|
// PhiScev in the loop.
|
|
// FORNOW/TODO: We currently expect the def-use chain to include only
|
|
// two-operand instructions, where one of the operands is an invariant.
|
|
// createAddRecFromPHIWithCasts() currently does not support anything more
|
|
// involved than that, so we keep the search simple. This can be
|
|
// extended/generalized as needed.
|
|
|
|
auto getDef = [&](const Value *Val) -> Value * {
|
|
const BinaryOperator *BinOp = dyn_cast<BinaryOperator>(Val);
|
|
if (!BinOp)
|
|
return nullptr;
|
|
Value *Op0 = BinOp->getOperand(0);
|
|
Value *Op1 = BinOp->getOperand(1);
|
|
Value *Def = nullptr;
|
|
if (L->isLoopInvariant(Op0))
|
|
Def = Op1;
|
|
else if (L->isLoopInvariant(Op1))
|
|
Def = Op0;
|
|
return Def;
|
|
};
|
|
|
|
// Look for the instruction that defines the induction via the
|
|
// loop backedge.
|
|
BasicBlock *Latch = L->getLoopLatch();
|
|
if (!Latch)
|
|
return false;
|
|
Value *Val = PN->getIncomingValueForBlock(Latch);
|
|
if (!Val)
|
|
return false;
|
|
|
|
// Follow the def-use chain until the induction phi is reached.
|
|
// If on the way we encounter a Value that has the same SCEV Expr as the
|
|
// phi node, we can consider the instructions we visit from that point
|
|
// as part of the cast-sequence that can be ignored.
|
|
bool InCastSequence = false;
|
|
auto *Inst = dyn_cast<Instruction>(Val);
|
|
while (Val != PN) {
|
|
// If we encountered a phi node other than PN, or if we left the loop,
|
|
// we bail out.
|
|
if (!Inst || !L->contains(Inst)) {
|
|
return false;
|
|
}
|
|
auto *AddRec = dyn_cast<SCEVAddRecExpr>(PSE.getSCEV(Val));
|
|
if (AddRec && PSE.areAddRecsEqualWithPreds(AddRec, AR))
|
|
InCastSequence = true;
|
|
if (InCastSequence) {
|
|
// Only the last instruction in the cast sequence is expected to have
|
|
// uses outside the induction def-use chain.
|
|
if (!CastInsts.empty())
|
|
if (!Inst->hasOneUse())
|
|
return false;
|
|
CastInsts.push_back(Inst);
|
|
}
|
|
Val = getDef(Val);
|
|
if (!Val)
|
|
return false;
|
|
Inst = dyn_cast<Instruction>(Val);
|
|
}
|
|
|
|
return InCastSequence;
|
|
}
|
|
|
|
bool InductionDescriptor::isInductionPHI(PHINode *Phi, const Loop *TheLoop,
|
|
PredicatedScalarEvolution &PSE,
|
|
InductionDescriptor &D, bool Assume) {
|
|
Type *PhiTy = Phi->getType();
|
|
|
|
// Handle integer and pointer inductions variables.
|
|
// Now we handle also FP induction but not trying to make a
|
|
// recurrent expression from the PHI node in-place.
|
|
|
|
if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy() && !PhiTy->isFloatTy() &&
|
|
!PhiTy->isDoubleTy() && !PhiTy->isHalfTy())
|
|
return false;
|
|
|
|
if (PhiTy->isFloatingPointTy())
|
|
return isFPInductionPHI(Phi, TheLoop, PSE.getSE(), D);
|
|
|
|
const SCEV *PhiScev = PSE.getSCEV(Phi);
|
|
const auto *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
|
|
|
|
// We need this expression to be an AddRecExpr.
|
|
if (Assume && !AR)
|
|
AR = PSE.getAsAddRec(Phi);
|
|
|
|
if (!AR) {
|
|
LLVM_DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
|
|
return false;
|
|
}
|
|
|
|
// Record any Cast instructions that participate in the induction update
|
|
const auto *SymbolicPhi = dyn_cast<SCEVUnknown>(PhiScev);
|
|
// If we started from an UnknownSCEV, and managed to build an addRecurrence
|
|
// only after enabling Assume with PSCEV, this means we may have encountered
|
|
// cast instructions that required adding a runtime check in order to
|
|
// guarantee the correctness of the AddRecurrence respresentation of the
|
|
// induction.
|
|
if (PhiScev != AR && SymbolicPhi) {
|
|
SmallVector<Instruction *, 2> Casts;
|
|
if (getCastsForInductionPHI(PSE, SymbolicPhi, AR, Casts))
|
|
return isInductionPHI(Phi, TheLoop, PSE.getSE(), D, AR, &Casts);
|
|
}
|
|
|
|
return isInductionPHI(Phi, TheLoop, PSE.getSE(), D, AR);
|
|
}
|
|
|
|
bool InductionDescriptor::isInductionPHI(
|
|
PHINode *Phi, const Loop *TheLoop, ScalarEvolution *SE,
|
|
InductionDescriptor &D, const SCEV *Expr,
|
|
SmallVectorImpl<Instruction *> *CastsToIgnore) {
|
|
Type *PhiTy = Phi->getType();
|
|
// We only handle integer and pointer inductions variables.
|
|
if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy())
|
|
return false;
|
|
|
|
// Check that the PHI is consecutive.
|
|
const SCEV *PhiScev = Expr ? Expr : SE->getSCEV(Phi);
|
|
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
|
|
|
|
if (!AR) {
|
|
LLVM_DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
|
|
return false;
|
|
}
|
|
|
|
if (AR->getLoop() != TheLoop) {
|
|
// FIXME: We should treat this as a uniform. Unfortunately, we
|
|
// don't currently know how to handled uniform PHIs.
|
|
LLVM_DEBUG(
|
|
dbgs() << "LV: PHI is a recurrence with respect to an outer loop.\n");
|
|
return false;
|
|
}
|
|
|
|
Value *StartValue =
|
|
Phi->getIncomingValueForBlock(AR->getLoop()->getLoopPreheader());
|
|
|
|
BasicBlock *Latch = AR->getLoop()->getLoopLatch();
|
|
if (!Latch)
|
|
return false;
|
|
BinaryOperator *BOp =
|
|
dyn_cast<BinaryOperator>(Phi->getIncomingValueForBlock(Latch));
|
|
|
|
const SCEV *Step = AR->getStepRecurrence(*SE);
|
|
// Calculate the pointer stride and check if it is consecutive.
|
|
// The stride may be a constant or a loop invariant integer value.
|
|
const SCEVConstant *ConstStep = dyn_cast<SCEVConstant>(Step);
|
|
if (!ConstStep && !SE->isLoopInvariant(Step, TheLoop))
|
|
return false;
|
|
|
|
if (PhiTy->isIntegerTy()) {
|
|
D = InductionDescriptor(StartValue, IK_IntInduction, Step, BOp,
|
|
CastsToIgnore);
|
|
return true;
|
|
}
|
|
|
|
assert(PhiTy->isPointerTy() && "The PHI must be a pointer");
|
|
// Pointer induction should be a constant.
|
|
if (!ConstStep)
|
|
return false;
|
|
|
|
ConstantInt *CV = ConstStep->getValue();
|
|
Type *PointerElementType = PhiTy->getPointerElementType();
|
|
// The pointer stride cannot be determined if the pointer element type is not
|
|
// sized.
|
|
if (!PointerElementType->isSized())
|
|
return false;
|
|
|
|
const DataLayout &DL = Phi->getModule()->getDataLayout();
|
|
int64_t Size = static_cast<int64_t>(DL.getTypeAllocSize(PointerElementType));
|
|
if (!Size)
|
|
return false;
|
|
|
|
int64_t CVSize = CV->getSExtValue();
|
|
if (CVSize % Size)
|
|
return false;
|
|
auto *StepValue =
|
|
SE->getConstant(CV->getType(), CVSize / Size, true /* signed */);
|
|
D = InductionDescriptor(StartValue, IK_PtrInduction, StepValue, BOp);
|
|
return true;
|
|
}
|