//===- LoopFlatten.cpp - Loop flattening pass------------------------------===// // // 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 flattens pairs nested loops into a single loop. // // The intention is to optimise loop nests like this, which together access an // array linearly: // // for (int i = 0; i < N; ++i) // for (int j = 0; j < M; ++j) // f(A[i*M+j]); // // into one loop: // // for (int i = 0; i < (N*M); ++i) // f(A[i]); // // It can also flatten loops where the induction variables are not used in the // loop. This is only worth doing if the induction variables are only used in an // expression like i*M+j. If they had any other uses, we would have to insert a // div/mod to reconstruct the original values, so this wouldn't be profitable. // // We also need to prove that N*M will not overflow. The preferred solution is // to widen the IV, which avoids overflow checks, so that is tried first. If // the IV cannot be widened, then we try to determine that this new tripcount // expression won't overflow. // // Q: Does LoopFlatten use SCEV? // Short answer: Yes and no. // // Long answer: // For this transformation to be valid, we require all uses of the induction // variables to be linear expressions of the form i*M+j. The different Loop // APIs are used to get some loop components like the induction variable, // compare statement, etc. In addition, we do some pattern matching to find the // linear expressions and other loop components like the loop increment. The // latter are examples of expressions that do use the induction variable, but // are safe to ignore when we check all uses to be of the form i*M+j. We keep // track of all of this in bookkeeping struct FlattenInfo. // We assume the loops to be canonical, i.e. starting at 0 and increment with // 1. This makes RHS of the compare the loop tripcount (with the right // predicate). We use SCEV to then sanity check that this tripcount matches // with the tripcount as computed by SCEV. // //===----------------------------------------------------------------------===// #include "llvm/Transforms/Scalar/LoopFlatten.h" #include "llvm/ADT/Statistic.h" #include "llvm/Analysis/AssumptionCache.h" #include "llvm/Analysis/LoopInfo.h" #include "llvm/Analysis/MemorySSAUpdater.h" #include "llvm/Analysis/OptimizationRemarkEmitter.h" #include "llvm/Analysis/ScalarEvolution.h" #include "llvm/Analysis/TargetTransformInfo.h" #include "llvm/Analysis/ValueTracking.h" #include "llvm/IR/Dominators.h" #include "llvm/IR/Function.h" #include "llvm/IR/IRBuilder.h" #include "llvm/IR/Module.h" #include "llvm/IR/PatternMatch.h" #include "llvm/IR/Verifier.h" #include "llvm/InitializePasses.h" #include "llvm/Pass.h" #include "llvm/Support/Debug.h" #include "llvm/Support/raw_ostream.h" #include "llvm/Transforms/Scalar.h" #include "llvm/Transforms/Utils/Local.h" #include "llvm/Transforms/Utils/LoopUtils.h" #include "llvm/Transforms/Utils/ScalarEvolutionExpander.h" #include "llvm/Transforms/Utils/SimplifyIndVar.h" using namespace llvm; using namespace llvm::PatternMatch; #define DEBUG_TYPE "loop-flatten" STATISTIC(NumFlattened, "Number of loops flattened"); static cl::opt RepeatedInstructionThreshold( "loop-flatten-cost-threshold", cl::Hidden, cl::init(2), cl::desc("Limit on the cost of instructions that can be repeated due to " "loop flattening")); static cl::opt AssumeNoOverflow("loop-flatten-assume-no-overflow", cl::Hidden, cl::init(false), cl::desc("Assume that the product of the two iteration " "trip counts will never overflow")); static cl::opt WidenIV("loop-flatten-widen-iv", cl::Hidden, cl::init(true), cl::desc("Widen the loop induction variables, if possible, so " "overflow checks won't reject flattening")); // We require all uses of both induction variables to match this pattern: // // (OuterPHI * InnerTripCount) + InnerPHI // // I.e., it needs to be a linear expression of the induction variables and the // inner loop trip count. We keep track of all different expressions on which // checks will be performed in this bookkeeping struct. // struct FlattenInfo { Loop *OuterLoop = nullptr; // The loop pair to be flattened. Loop *InnerLoop = nullptr; PHINode *InnerInductionPHI = nullptr; // These PHINodes correspond to loop PHINode *OuterInductionPHI = nullptr; // induction variables, which are // expected to start at zero and // increment by one on each loop. Value *InnerTripCount = nullptr; // The product of these two tripcounts Value *OuterTripCount = nullptr; // will be the new flattened loop // tripcount. Also used to recognise a // linear expression that will be replaced. SmallPtrSet LinearIVUses; // Contains the linear expressions // of the form i*M+j that will be // replaced. BinaryOperator *InnerIncrement = nullptr; // Uses of induction variables in BinaryOperator *OuterIncrement = nullptr; // loop control statements that BranchInst *InnerBranch = nullptr; // are safe to ignore. BranchInst *OuterBranch = nullptr; // The instruction that needs to be // updated with new tripcount. SmallPtrSet InnerPHIsToTransform; bool Widened = false; // Whether this holds the flatten info before or after // widening. PHINode *NarrowInnerInductionPHI = nullptr; // Holds the old/narrow induction PHINode *NarrowOuterInductionPHI = nullptr; // phis, i.e. the Phis before IV // has been apllied. Used to skip // checks on phi nodes. FlattenInfo(Loop *OL, Loop *IL) : OuterLoop(OL), InnerLoop(IL){}; bool isNarrowInductionPhi(PHINode *Phi) { // This can't be the narrow phi if we haven't widened the IV first. if (!Widened) return false; return NarrowInnerInductionPHI == Phi || NarrowOuterInductionPHI == Phi; } bool isInnerLoopIncrement(User *U) { return InnerIncrement == U; } bool isOuterLoopIncrement(User *U) { return OuterIncrement == U; } bool isInnerLoopTest(User *U) { return InnerBranch->getCondition() == U; } bool checkOuterInductionPhiUsers(SmallPtrSet &ValidOuterPHIUses) { for (User *U : OuterInductionPHI->users()) { if (isOuterLoopIncrement(U)) continue; auto IsValidOuterPHIUses = [&] (User *U) -> bool { LLVM_DEBUG(dbgs() << "Found use of outer induction variable: "; U->dump()); if (!ValidOuterPHIUses.count(U)) { LLVM_DEBUG(dbgs() << "Did not match expected pattern, bailing\n"); return false; } LLVM_DEBUG(dbgs() << "Use is optimisable\n"); return true; }; if (auto *V = dyn_cast(U)) { for (auto *K : V->users()) { if (!IsValidOuterPHIUses(K)) return false; } continue; } if (!IsValidOuterPHIUses(U)) return false; } return true; } bool matchLinearIVUser(User *U, Value *InnerTripCount, SmallPtrSet &ValidOuterPHIUses) { LLVM_DEBUG(dbgs() << "Found use of inner induction variable: "; U->dump()); Value *MatchedMul = nullptr; Value *MatchedItCount = nullptr; bool IsAdd = match(U, m_c_Add(m_Specific(InnerInductionPHI), m_Value(MatchedMul))) && match(MatchedMul, m_c_Mul(m_Specific(OuterInductionPHI), m_Value(MatchedItCount))); // Matches the same pattern as above, except it also looks for truncs // on the phi, which can be the result of widening the induction variables. bool IsAddTrunc = match(U, m_c_Add(m_Trunc(m_Specific(InnerInductionPHI)), m_Value(MatchedMul))) && match(MatchedMul, m_c_Mul(m_Trunc(m_Specific(OuterInductionPHI)), m_Value(MatchedItCount))); if (!MatchedItCount) return false; // Look through extends if the IV has been widened. if (Widened && (isa(MatchedItCount) || isa(MatchedItCount))) { assert(MatchedItCount->getType() == InnerInductionPHI->getType() && "Unexpected type mismatch in types after widening"); MatchedItCount = isa(MatchedItCount) ? dyn_cast(MatchedItCount)->getOperand(0) : dyn_cast(MatchedItCount)->getOperand(0); } if ((IsAdd || IsAddTrunc) && MatchedItCount == InnerTripCount) { LLVM_DEBUG(dbgs() << "Use is optimisable\n"); ValidOuterPHIUses.insert(MatchedMul); LinearIVUses.insert(U); return true; } LLVM_DEBUG(dbgs() << "Did not match expected pattern, bailing\n"); return false; } bool checkInnerInductionPhiUsers(SmallPtrSet &ValidOuterPHIUses) { Value *SExtInnerTripCount = InnerTripCount; if (Widened && (isa(InnerTripCount) || isa(InnerTripCount))) SExtInnerTripCount = cast(InnerTripCount)->getOperand(0); for (User *U : InnerInductionPHI->users()) { if (isInnerLoopIncrement(U)) continue; // After widening the IVs, a trunc instruction might have been introduced, // so look through truncs. if (isa(U)) { if (!U->hasOneUse()) return false; U = *U->user_begin(); } // If the use is in the compare (which is also the condition of the inner // branch) then the compare has been altered by another transformation e.g // icmp ult %inc, tripcount -> icmp ult %j, tripcount-1, where tripcount is // a constant. Ignore this use as the compare gets removed later anyway. if (isInnerLoopTest(U)) continue; if (!matchLinearIVUser(U, SExtInnerTripCount, ValidOuterPHIUses)) return false; } return true; } }; static bool setLoopComponents(Value *&TC, Value *&TripCount, BinaryOperator *&Increment, SmallPtrSetImpl &IterationInstructions) { TripCount = TC; IterationInstructions.insert(Increment); LLVM_DEBUG(dbgs() << "Found Increment: "; Increment->dump()); LLVM_DEBUG(dbgs() << "Found trip count: "; TripCount->dump()); LLVM_DEBUG(dbgs() << "Successfully found all loop components\n"); return true; } // Given the RHS of the loop latch compare instruction, verify with SCEV // that this is indeed the loop tripcount. // TODO: This used to be a straightforward check but has grown to be quite // complicated now. It is therefore worth revisiting what the additional // benefits are of this (compared to relying on canonical loops and pattern // matching). static bool verifyTripCount(Value *RHS, Loop *L, SmallPtrSetImpl &IterationInstructions, PHINode *&InductionPHI, Value *&TripCount, BinaryOperator *&Increment, BranchInst *&BackBranch, ScalarEvolution *SE, bool IsWidened) { const SCEV *BackedgeTakenCount = SE->getBackedgeTakenCount(L); if (isa(BackedgeTakenCount)) { LLVM_DEBUG(dbgs() << "Backedge-taken count is not predictable\n"); return false; } // The Extend=false flag is used for getTripCountFromExitCount as we want // to verify and match it with the pattern matched tripcount. Please note // that overflow checks are performed in checkOverflow, but are first tried // to avoid by widening the IV. const SCEV *SCEVTripCount = SE->getTripCountFromExitCount(BackedgeTakenCount, /*Extend=*/false); const SCEV *SCEVRHS = SE->getSCEV(RHS); if (SCEVRHS == SCEVTripCount) return setLoopComponents(RHS, TripCount, Increment, IterationInstructions); ConstantInt *ConstantRHS = dyn_cast(RHS); if (ConstantRHS) { const SCEV *BackedgeTCExt = nullptr; if (IsWidened) { const SCEV *SCEVTripCountExt; // Find the extended backedge taken count and extended trip count using // SCEV. One of these should now match the RHS of the compare. BackedgeTCExt = SE->getZeroExtendExpr(BackedgeTakenCount, RHS->getType()); SCEVTripCountExt = SE->getTripCountFromExitCount(BackedgeTCExt, false); if (SCEVRHS != BackedgeTCExt && SCEVRHS != SCEVTripCountExt) { LLVM_DEBUG(dbgs() << "Could not find valid trip count\n"); return false; } } // If the RHS of the compare is equal to the backedge taken count we need // to add one to get the trip count. if (SCEVRHS == BackedgeTCExt || SCEVRHS == BackedgeTakenCount) { ConstantInt *One = ConstantInt::get(ConstantRHS->getType(), 1); Value *NewRHS = ConstantInt::get( ConstantRHS->getContext(), ConstantRHS->getValue() + One->getValue()); return setLoopComponents(NewRHS, TripCount, Increment, IterationInstructions); } return setLoopComponents(RHS, TripCount, Increment, IterationInstructions); } // If the RHS isn't a constant then check that the reason it doesn't match // the SCEV trip count is because the RHS is a ZExt or SExt instruction // (and take the trip count to be the RHS). if (!IsWidened) { LLVM_DEBUG(dbgs() << "Could not find valid trip count\n"); return false; } auto *TripCountInst = dyn_cast(RHS); if (!TripCountInst) { LLVM_DEBUG(dbgs() << "Could not find valid trip count\n"); return false; } if ((!isa(TripCountInst) && !isa(TripCountInst)) || SE->getSCEV(TripCountInst->getOperand(0)) != SCEVTripCount) { LLVM_DEBUG(dbgs() << "Could not find valid extended trip count\n"); return false; } return setLoopComponents(RHS, TripCount, Increment, IterationInstructions); } // Finds the induction variable, increment and trip count for a simple loop that // we can flatten. static bool findLoopComponents( Loop *L, SmallPtrSetImpl &IterationInstructions, PHINode *&InductionPHI, Value *&TripCount, BinaryOperator *&Increment, BranchInst *&BackBranch, ScalarEvolution *SE, bool IsWidened) { LLVM_DEBUG(dbgs() << "Finding components of loop: " << L->getName() << "\n"); if (!L->isLoopSimplifyForm()) { LLVM_DEBUG(dbgs() << "Loop is not in normal form\n"); return false; } // Currently, to simplify the implementation, the Loop induction variable must // start at zero and increment with a step size of one. if (!L->isCanonical(*SE)) { LLVM_DEBUG(dbgs() << "Loop is not canonical\n"); return false; } // There must be exactly one exiting block, and it must be the same at the // latch. BasicBlock *Latch = L->getLoopLatch(); if (L->getExitingBlock() != Latch) { LLVM_DEBUG(dbgs() << "Exiting and latch block are different\n"); return false; } // Find the induction PHI. If there is no induction PHI, we can't do the // transformation. TODO: could other variables trigger this? Do we have to // search for the best one? InductionPHI = L->getInductionVariable(*SE); if (!InductionPHI) { LLVM_DEBUG(dbgs() << "Could not find induction PHI\n"); return false; } LLVM_DEBUG(dbgs() << "Found induction PHI: "; InductionPHI->dump()); bool ContinueOnTrue = L->contains(Latch->getTerminator()->getSuccessor(0)); auto IsValidPredicate = [&](ICmpInst::Predicate Pred) { if (ContinueOnTrue) return Pred == CmpInst::ICMP_NE || Pred == CmpInst::ICMP_ULT; else return Pred == CmpInst::ICMP_EQ; }; // Find Compare and make sure it is valid. getLatchCmpInst checks that the // back branch of the latch is conditional. ICmpInst *Compare = L->getLatchCmpInst(); if (!Compare || !IsValidPredicate(Compare->getUnsignedPredicate()) || Compare->hasNUsesOrMore(2)) { LLVM_DEBUG(dbgs() << "Could not find valid comparison\n"); return false; } BackBranch = cast(Latch->getTerminator()); IterationInstructions.insert(BackBranch); LLVM_DEBUG(dbgs() << "Found back branch: "; BackBranch->dump()); IterationInstructions.insert(Compare); LLVM_DEBUG(dbgs() << "Found comparison: "; Compare->dump()); // Find increment and trip count. // There are exactly 2 incoming values to the induction phi; one from the // pre-header and one from the latch. The incoming latch value is the // increment variable. Increment = dyn_cast(InductionPHI->getIncomingValueForBlock(Latch)); if (Increment->hasNUsesOrMore(3)) { LLVM_DEBUG(dbgs() << "Could not find valid increment\n"); return false; } // The trip count is the RHS of the compare. If this doesn't match the trip // count computed by SCEV then this is because the trip count variable // has been widened so the types don't match, or because it is a constant and // another transformation has changed the compare (e.g. icmp ult %inc, // tripcount -> icmp ult %j, tripcount-1), or both. Value *RHS = Compare->getOperand(1); return verifyTripCount(RHS, L, IterationInstructions, InductionPHI, TripCount, Increment, BackBranch, SE, IsWidened); } static bool checkPHIs(FlattenInfo &FI, const TargetTransformInfo *TTI) { // All PHIs in the inner and outer headers must either be: // - The induction PHI, which we are going to rewrite as one induction in // the new loop. This is already checked by findLoopComponents. // - An outer header PHI with all incoming values from outside the loop. // LoopSimplify guarantees we have a pre-header, so we don't need to // worry about that here. // - Pairs of PHIs in the inner and outer headers, which implement a // loop-carried dependency that will still be valid in the new loop. To // be valid, this variable must be modified only in the inner loop. // The set of PHI nodes in the outer loop header that we know will still be // valid after the transformation. These will not need to be modified (with // the exception of the induction variable), but we do need to check that // there are no unsafe PHI nodes. SmallPtrSet SafeOuterPHIs; SafeOuterPHIs.insert(FI.OuterInductionPHI); // Check that all PHI nodes in the inner loop header match one of the valid // patterns. for (PHINode &InnerPHI : FI.InnerLoop->getHeader()->phis()) { // The induction PHIs break these rules, and that's OK because we treat // them specially when doing the transformation. if (&InnerPHI == FI.InnerInductionPHI) continue; if (FI.isNarrowInductionPhi(&InnerPHI)) continue; // Each inner loop PHI node must have two incoming values/blocks - one // from the pre-header, and one from the latch. assert(InnerPHI.getNumIncomingValues() == 2); Value *PreHeaderValue = InnerPHI.getIncomingValueForBlock(FI.InnerLoop->getLoopPreheader()); Value *LatchValue = InnerPHI.getIncomingValueForBlock(FI.InnerLoop->getLoopLatch()); // The incoming value from the outer loop must be the PHI node in the // outer loop header, with no modifications made in the top of the outer // loop. PHINode *OuterPHI = dyn_cast(PreHeaderValue); if (!OuterPHI || OuterPHI->getParent() != FI.OuterLoop->getHeader()) { LLVM_DEBUG(dbgs() << "value modified in top of outer loop\n"); return false; } // The other incoming value must come from the inner loop, without any // modifications in the tail end of the outer loop. We are in LCSSA form, // so this will actually be a PHI in the inner loop's exit block, which // only uses values from inside the inner loop. PHINode *LCSSAPHI = dyn_cast( OuterPHI->getIncomingValueForBlock(FI.OuterLoop->getLoopLatch())); if (!LCSSAPHI) { LLVM_DEBUG(dbgs() << "could not find LCSSA PHI\n"); return false; } // The value used by the LCSSA PHI must be the same one that the inner // loop's PHI uses. if (LCSSAPHI->hasConstantValue() != LatchValue) { LLVM_DEBUG( dbgs() << "LCSSA PHI incoming value does not match latch value\n"); return false; } LLVM_DEBUG(dbgs() << "PHI pair is safe:\n"); LLVM_DEBUG(dbgs() << " Inner: "; InnerPHI.dump()); LLVM_DEBUG(dbgs() << " Outer: "; OuterPHI->dump()); SafeOuterPHIs.insert(OuterPHI); FI.InnerPHIsToTransform.insert(&InnerPHI); } for (PHINode &OuterPHI : FI.OuterLoop->getHeader()->phis()) { if (FI.isNarrowInductionPhi(&OuterPHI)) continue; if (!SafeOuterPHIs.count(&OuterPHI)) { LLVM_DEBUG(dbgs() << "found unsafe PHI in outer loop: "; OuterPHI.dump()); return false; } } LLVM_DEBUG(dbgs() << "checkPHIs: OK\n"); return true; } static bool checkOuterLoopInsts(FlattenInfo &FI, SmallPtrSetImpl &IterationInstructions, const TargetTransformInfo *TTI) { // Check for instructions in the outer but not inner loop. If any of these // have side-effects then this transformation is not legal, and if there is // a significant amount of code here which can't be optimised out that it's // not profitable (as these instructions would get executed for each // iteration of the inner loop). InstructionCost RepeatedInstrCost = 0; for (auto *B : FI.OuterLoop->getBlocks()) { if (FI.InnerLoop->contains(B)) continue; for (auto &I : *B) { if (!isa(&I) && !I.isTerminator() && !isSafeToSpeculativelyExecute(&I)) { LLVM_DEBUG(dbgs() << "Cannot flatten because instruction may have " "side effects: "; I.dump()); return false; } // The execution count of the outer loop's iteration instructions // (increment, compare and branch) will be increased, but the // equivalent instructions will be removed from the inner loop, so // they make a net difference of zero. if (IterationInstructions.count(&I)) continue; // The uncoditional branch to the inner loop's header will turn into // a fall-through, so adds no cost. BranchInst *Br = dyn_cast(&I); if (Br && Br->isUnconditional() && Br->getSuccessor(0) == FI.InnerLoop->getHeader()) continue; // Multiplies of the outer iteration variable and inner iteration // count will be optimised out. if (match(&I, m_c_Mul(m_Specific(FI.OuterInductionPHI), m_Specific(FI.InnerTripCount)))) continue; InstructionCost Cost = TTI->getUserCost(&I, TargetTransformInfo::TCK_SizeAndLatency); LLVM_DEBUG(dbgs() << "Cost " << Cost << ": "; I.dump()); RepeatedInstrCost += Cost; } } LLVM_DEBUG(dbgs() << "Cost of instructions that will be repeated: " << RepeatedInstrCost << "\n"); // Bail out if flattening the loops would cause instructions in the outer // loop but not in the inner loop to be executed extra times. if (RepeatedInstrCost > RepeatedInstructionThreshold) { LLVM_DEBUG(dbgs() << "checkOuterLoopInsts: not profitable, bailing.\n"); return false; } LLVM_DEBUG(dbgs() << "checkOuterLoopInsts: OK\n"); return true; } // We require all uses of both induction variables to match this pattern: // // (OuterPHI * InnerTripCount) + InnerPHI // // Any uses of the induction variables not matching that pattern would // require a div/mod to reconstruct in the flattened loop, so the // transformation wouldn't be profitable. static bool checkIVUsers(FlattenInfo &FI) { // Check that all uses of the inner loop's induction variable match the // expected pattern, recording the uses of the outer IV. SmallPtrSet ValidOuterPHIUses; if (!FI.checkInnerInductionPhiUsers(ValidOuterPHIUses)) return false; // Check that there are no uses of the outer IV other than the ones found // as part of the pattern above. if (!FI.checkOuterInductionPhiUsers(ValidOuterPHIUses)) return false; LLVM_DEBUG(dbgs() << "checkIVUsers: OK\n"; dbgs() << "Found " << FI.LinearIVUses.size() << " value(s) that can be replaced:\n"; for (Value *V : FI.LinearIVUses) { dbgs() << " "; V->dump(); }); return true; } // Return an OverflowResult dependant on if overflow of the multiplication of // InnerTripCount and OuterTripCount can be assumed not to happen. static OverflowResult checkOverflow(FlattenInfo &FI, DominatorTree *DT, AssumptionCache *AC) { Function *F = FI.OuterLoop->getHeader()->getParent(); const DataLayout &DL = F->getParent()->getDataLayout(); // For debugging/testing. if (AssumeNoOverflow) return OverflowResult::NeverOverflows; // Check if the multiply could not overflow due to known ranges of the // input values. OverflowResult OR = computeOverflowForUnsignedMul( FI.InnerTripCount, FI.OuterTripCount, DL, AC, FI.OuterLoop->getLoopPreheader()->getTerminator(), DT); if (OR != OverflowResult::MayOverflow) return OR; for (Value *V : FI.LinearIVUses) { for (Value *U : V->users()) { if (auto *GEP = dyn_cast(U)) { for (Value *GEPUser : U->users()) { auto *GEPUserInst = cast(GEPUser); if (!isa(GEPUserInst) && !(isa(GEPUserInst) && GEP == GEPUserInst->getOperand(1))) continue; if (!isGuaranteedToExecuteForEveryIteration(GEPUserInst, FI.InnerLoop)) continue; // The IV is used as the operand of a GEP which dominates the loop // latch, and the IV is at least as wide as the address space of the // GEP. In this case, the GEP would wrap around the address space // before the IV increment wraps, which would be UB. if (GEP->isInBounds() && V->getType()->getIntegerBitWidth() >= DL.getPointerTypeSizeInBits(GEP->getType())) { LLVM_DEBUG( dbgs() << "use of linear IV would be UB if overflow occurred: "; GEP->dump()); return OverflowResult::NeverOverflows; } } } } } return OverflowResult::MayOverflow; } static bool CanFlattenLoopPair(FlattenInfo &FI, DominatorTree *DT, LoopInfo *LI, ScalarEvolution *SE, AssumptionCache *AC, const TargetTransformInfo *TTI) { SmallPtrSet IterationInstructions; if (!findLoopComponents(FI.InnerLoop, IterationInstructions, FI.InnerInductionPHI, FI.InnerTripCount, FI.InnerIncrement, FI.InnerBranch, SE, FI.Widened)) return false; if (!findLoopComponents(FI.OuterLoop, IterationInstructions, FI.OuterInductionPHI, FI.OuterTripCount, FI.OuterIncrement, FI.OuterBranch, SE, FI.Widened)) return false; // Both of the loop trip count values must be invariant in the outer loop // (non-instructions are all inherently invariant). if (!FI.OuterLoop->isLoopInvariant(FI.InnerTripCount)) { LLVM_DEBUG(dbgs() << "inner loop trip count not invariant\n"); return false; } if (!FI.OuterLoop->isLoopInvariant(FI.OuterTripCount)) { LLVM_DEBUG(dbgs() << "outer loop trip count not invariant\n"); return false; } if (!checkPHIs(FI, TTI)) return false; // FIXME: it should be possible to handle different types correctly. if (FI.InnerInductionPHI->getType() != FI.OuterInductionPHI->getType()) return false; if (!checkOuterLoopInsts(FI, IterationInstructions, TTI)) return false; // Find the values in the loop that can be replaced with the linearized // induction variable, and check that there are no other uses of the inner // or outer induction variable. If there were, we could still do this // transformation, but we'd have to insert a div/mod to calculate the // original IVs, so it wouldn't be profitable. if (!checkIVUsers(FI)) return false; LLVM_DEBUG(dbgs() << "CanFlattenLoopPair: OK\n"); return true; } static bool DoFlattenLoopPair(FlattenInfo &FI, DominatorTree *DT, LoopInfo *LI, ScalarEvolution *SE, AssumptionCache *AC, const TargetTransformInfo *TTI, LPMUpdater *U, MemorySSAUpdater *MSSAU) { Function *F = FI.OuterLoop->getHeader()->getParent(); LLVM_DEBUG(dbgs() << "Checks all passed, doing the transformation\n"); { using namespace ore; OptimizationRemark Remark(DEBUG_TYPE, "Flattened", FI.InnerLoop->getStartLoc(), FI.InnerLoop->getHeader()); OptimizationRemarkEmitter ORE(F); Remark << "Flattened into outer loop"; ORE.emit(Remark); } Value *NewTripCount = BinaryOperator::CreateMul( FI.InnerTripCount, FI.OuterTripCount, "flatten.tripcount", FI.OuterLoop->getLoopPreheader()->getTerminator()); LLVM_DEBUG(dbgs() << "Created new trip count in preheader: "; NewTripCount->dump()); // Fix up PHI nodes that take values from the inner loop back-edge, which // we are about to remove. FI.InnerInductionPHI->removeIncomingValue(FI.InnerLoop->getLoopLatch()); // The old Phi will be optimised away later, but for now we can't leave // leave it in an invalid state, so are updating them too. for (PHINode *PHI : FI.InnerPHIsToTransform) PHI->removeIncomingValue(FI.InnerLoop->getLoopLatch()); // Modify the trip count of the outer loop to be the product of the two // trip counts. cast(FI.OuterBranch->getCondition())->setOperand(1, NewTripCount); // Replace the inner loop backedge with an unconditional branch to the exit. BasicBlock *InnerExitBlock = FI.InnerLoop->getExitBlock(); BasicBlock *InnerExitingBlock = FI.InnerLoop->getExitingBlock(); InnerExitingBlock->getTerminator()->eraseFromParent(); BranchInst::Create(InnerExitBlock, InnerExitingBlock); // Update the DomTree and MemorySSA. DT->deleteEdge(InnerExitingBlock, FI.InnerLoop->getHeader()); if (MSSAU) MSSAU->removeEdge(InnerExitingBlock, FI.InnerLoop->getHeader()); // Replace all uses of the polynomial calculated from the two induction // variables with the one new one. IRBuilder<> Builder(FI.OuterInductionPHI->getParent()->getTerminator()); for (Value *V : FI.LinearIVUses) { Value *OuterValue = FI.OuterInductionPHI; if (FI.Widened) OuterValue = Builder.CreateTrunc(FI.OuterInductionPHI, V->getType(), "flatten.trunciv"); LLVM_DEBUG(dbgs() << "Replacing: "; V->dump(); dbgs() << "with: "; OuterValue->dump()); V->replaceAllUsesWith(OuterValue); } // Tell LoopInfo, SCEV and the pass manager that the inner loop has been // deleted, and any information that have about the outer loop invalidated. SE->forgetLoop(FI.OuterLoop); SE->forgetLoop(FI.InnerLoop); if (U) U->markLoopAsDeleted(*FI.InnerLoop, FI.InnerLoop->getName()); LI->erase(FI.InnerLoop); // Increment statistic value. NumFlattened++; return true; } static bool CanWidenIV(FlattenInfo &FI, DominatorTree *DT, LoopInfo *LI, ScalarEvolution *SE, AssumptionCache *AC, const TargetTransformInfo *TTI) { if (!WidenIV) { LLVM_DEBUG(dbgs() << "Widening the IVs is disabled\n"); return false; } LLVM_DEBUG(dbgs() << "Try widening the IVs\n"); Module *M = FI.InnerLoop->getHeader()->getParent()->getParent(); auto &DL = M->getDataLayout(); auto *InnerType = FI.InnerInductionPHI->getType(); auto *OuterType = FI.OuterInductionPHI->getType(); unsigned MaxLegalSize = DL.getLargestLegalIntTypeSizeInBits(); auto *MaxLegalType = DL.getLargestLegalIntType(M->getContext()); // If both induction types are less than the maximum legal integer width, // promote both to the widest type available so we know calculating // (OuterTripCount * InnerTripCount) as the new trip count is safe. if (InnerType != OuterType || InnerType->getScalarSizeInBits() >= MaxLegalSize || MaxLegalType->getScalarSizeInBits() < InnerType->getScalarSizeInBits() * 2) { LLVM_DEBUG(dbgs() << "Can't widen the IV\n"); return false; } SCEVExpander Rewriter(*SE, DL, "loopflatten"); SmallVector DeadInsts; unsigned ElimExt = 0; unsigned Widened = 0; auto CreateWideIV = [&](WideIVInfo WideIV, bool &Deleted) -> bool { PHINode *WidePhi = createWideIV(WideIV, LI, SE, Rewriter, DT, DeadInsts, ElimExt, Widened, true /* HasGuards */, true /* UsePostIncrementRanges */); if (!WidePhi) return false; LLVM_DEBUG(dbgs() << "Created wide phi: "; WidePhi->dump()); LLVM_DEBUG(dbgs() << "Deleting old phi: "; WideIV.NarrowIV->dump()); Deleted = RecursivelyDeleteDeadPHINode(WideIV.NarrowIV); return true; }; bool Deleted; if (!CreateWideIV({FI.InnerInductionPHI, MaxLegalType, false}, Deleted)) return false; // Add the narrow phi to list, so that it will be adjusted later when the // the transformation is performed. if (!Deleted) FI.InnerPHIsToTransform.insert(FI.InnerInductionPHI); if (!CreateWideIV({FI.OuterInductionPHI, MaxLegalType, false}, Deleted)) return false; assert(Widened && "Widened IV expected"); FI.Widened = true; // Save the old/narrow induction phis, which we need to ignore in CheckPHIs. FI.NarrowInnerInductionPHI = FI.InnerInductionPHI; FI.NarrowOuterInductionPHI = FI.OuterInductionPHI; // After widening, rediscover all the loop components. return CanFlattenLoopPair(FI, DT, LI, SE, AC, TTI); } static bool FlattenLoopPair(FlattenInfo &FI, DominatorTree *DT, LoopInfo *LI, ScalarEvolution *SE, AssumptionCache *AC, const TargetTransformInfo *TTI, LPMUpdater *U, MemorySSAUpdater *MSSAU) { LLVM_DEBUG( dbgs() << "Loop flattening running on outer loop " << FI.OuterLoop->getHeader()->getName() << " and inner loop " << FI.InnerLoop->getHeader()->getName() << " in " << FI.OuterLoop->getHeader()->getParent()->getName() << "\n"); if (!CanFlattenLoopPair(FI, DT, LI, SE, AC, TTI)) return false; // Check if we can widen the induction variables to avoid overflow checks. bool CanFlatten = CanWidenIV(FI, DT, LI, SE, AC, TTI); // It can happen that after widening of the IV, flattening may not be // possible/happening, e.g. when it is deemed unprofitable. So bail here if // that is the case. // TODO: IV widening without performing the actual flattening transformation // is not ideal. While this codegen change should not matter much, it is an // unnecessary change which is better to avoid. It's unlikely this happens // often, because if it's unprofitibale after widening, it should be // unprofitabe before widening as checked in the first round of checks. But // 'RepeatedInstructionThreshold' is set to only 2, which can probably be // relaxed. Because this is making a code change (the IV widening, but not // the flattening), we return true here. if (FI.Widened && !CanFlatten) return true; // If we have widened and can perform the transformation, do that here. if (CanFlatten) return DoFlattenLoopPair(FI, DT, LI, SE, AC, TTI, U, MSSAU); // Otherwise, if we haven't widened the IV, check if the new iteration // variable might overflow. In this case, we need to version the loop, and // select the original version at runtime if the iteration space is too // large. // TODO: We currently don't version the loop. OverflowResult OR = checkOverflow(FI, DT, AC); if (OR == OverflowResult::AlwaysOverflowsHigh || OR == OverflowResult::AlwaysOverflowsLow) { LLVM_DEBUG(dbgs() << "Multiply would always overflow, so not profitable\n"); return false; } else if (OR == OverflowResult::MayOverflow) { LLVM_DEBUG(dbgs() << "Multiply might overflow, not flattening\n"); return false; } LLVM_DEBUG(dbgs() << "Multiply cannot overflow, modifying loop in-place\n"); return DoFlattenLoopPair(FI, DT, LI, SE, AC, TTI, U, MSSAU); } bool Flatten(LoopNest &LN, DominatorTree *DT, LoopInfo *LI, ScalarEvolution *SE, AssumptionCache *AC, TargetTransformInfo *TTI, LPMUpdater *U, MemorySSAUpdater *MSSAU) { bool Changed = false; for (Loop *InnerLoop : LN.getLoops()) { auto *OuterLoop = InnerLoop->getParentLoop(); if (!OuterLoop) continue; FlattenInfo FI(OuterLoop, InnerLoop); Changed |= FlattenLoopPair(FI, DT, LI, SE, AC, TTI, U, MSSAU); } return Changed; } PreservedAnalyses LoopFlattenPass::run(LoopNest &LN, LoopAnalysisManager &LAM, LoopStandardAnalysisResults &AR, LPMUpdater &U) { bool Changed = false; Optional MSSAU; if (AR.MSSA) { MSSAU = MemorySSAUpdater(AR.MSSA); if (VerifyMemorySSA) AR.MSSA->verifyMemorySSA(); } // The loop flattening pass requires loops to be // in simplified form, and also needs LCSSA. Running // this pass will simplify all loops that contain inner loops, // regardless of whether anything ends up being flattened. Changed |= Flatten(LN, &AR.DT, &AR.LI, &AR.SE, &AR.AC, &AR.TTI, &U, MSSAU.hasValue() ? MSSAU.getPointer() : nullptr); if (!Changed) return PreservedAnalyses::all(); if (AR.MSSA && VerifyMemorySSA) AR.MSSA->verifyMemorySSA(); auto PA = getLoopPassPreservedAnalyses(); if (AR.MSSA) PA.preserve(); return PA; } namespace { class LoopFlattenLegacyPass : public FunctionPass { public: static char ID; // Pass ID, replacement for typeid LoopFlattenLegacyPass() : FunctionPass(ID) { initializeLoopFlattenLegacyPassPass(*PassRegistry::getPassRegistry()); } // Possibly flatten loop L into its child. bool runOnFunction(Function &F) override; void getAnalysisUsage(AnalysisUsage &AU) const override { getLoopAnalysisUsage(AU); AU.addRequired(); AU.addPreserved(); AU.addRequired(); AU.addPreserved(); AU.addPreserved(); } }; } // namespace char LoopFlattenLegacyPass::ID = 0; INITIALIZE_PASS_BEGIN(LoopFlattenLegacyPass, "loop-flatten", "Flattens loops", false, false) INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass) INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker) INITIALIZE_PASS_END(LoopFlattenLegacyPass, "loop-flatten", "Flattens loops", false, false) FunctionPass *llvm::createLoopFlattenPass() { return new LoopFlattenLegacyPass(); } bool LoopFlattenLegacyPass::runOnFunction(Function &F) { ScalarEvolution *SE = &getAnalysis().getSE(); LoopInfo *LI = &getAnalysis().getLoopInfo(); auto *DTWP = getAnalysisIfAvailable(); DominatorTree *DT = DTWP ? &DTWP->getDomTree() : nullptr; auto &TTIP = getAnalysis(); auto *TTI = &TTIP.getTTI(F); auto *AC = &getAnalysis().getAssumptionCache(F); auto *MSSA = getAnalysisIfAvailable(); Optional MSSAU; if (MSSA) MSSAU = MemorySSAUpdater(&MSSA->getMSSA()); bool Changed = false; for (Loop *L : *LI) { auto LN = LoopNest::getLoopNest(*L, *SE); Changed |= Flatten(*LN, DT, LI, SE, AC, TTI, nullptr, MSSAU.hasValue() ? MSSAU.getPointer() : nullptr); } return Changed; }