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clang-p2996/llvm/lib/Transforms/Scalar/LoopFlatten.cpp
Sander de Smalen ae27274b2f NFC: Migrate LoopFlatten to work on InstructionCost. 
This patch migrates cost values and arithmetic to work on InstructionCost.
When the interfaces to TargetTransformInfo are changed, any InstructionCost
state will propagate naturally.

See this patch for the introduction of the type: https://reviews.llvm.org/D91174
See this thread for context: http://lists.llvm.org/pipermail/llvm-dev/2020-November/146408.html

Reviewed By: david-arm

Differential Revision: https://reviews.llvm.org/D96029
2021-02-06 11:47:04 +00:00

730 lines
28 KiB
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//===- 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.
//
//===----------------------------------------------------------------------===//
#include "llvm/Transforms/Scalar/LoopFlatten.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/LoopInfo.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"
#define DEBUG_TYPE "loop-flatten"
using namespace llvm;
using namespace llvm::PatternMatch;
static cl::opt<unsigned> 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<bool>
AssumeNoOverflow("loop-flatten-assume-no-overflow", cl::Hidden,
cl::init(false),
cl::desc("Assume that the product of the two iteration "
"limits will never overflow"));
static cl::opt<bool>
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"));
struct FlattenInfo {
Loop *OuterLoop = nullptr;
Loop *InnerLoop = nullptr;
PHINode *InnerInductionPHI = nullptr;
PHINode *OuterInductionPHI = nullptr;
Value *InnerLimit = nullptr;
Value *OuterLimit = nullptr;
BinaryOperator *InnerIncrement = nullptr;
BinaryOperator *OuterIncrement = nullptr;
BranchInst *InnerBranch = nullptr;
BranchInst *OuterBranch = nullptr;
SmallPtrSet<Value *, 4> LinearIVUses;
SmallPtrSet<PHINode *, 4> InnerPHIsToTransform;
// Whether this holds the flatten info before or after widening.
bool Widened = false;
FlattenInfo(Loop *OL, Loop *IL) : OuterLoop(OL), InnerLoop(IL) {};
};
// Finds the induction variable, increment and limit for a simple loop that we
// can flatten.
static bool findLoopComponents(
Loop *L, SmallPtrSetImpl<Instruction *> &IterationInstructions,
PHINode *&InductionPHI, Value *&Limit, BinaryOperator *&Increment,
BranchInst *&BackBranch, ScalarEvolution *SE) {
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;
}
// 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;
}
// Latch block must end in a conditional branch.
BackBranch = dyn_cast<BranchInst>(Latch->getTerminator());
if (!BackBranch || !BackBranch->isConditional()) {
LLVM_DEBUG(dbgs() << "Could not find back-branch\n");
return false;
}
IterationInstructions.insert(BackBranch);
LLVM_DEBUG(dbgs() << "Found back branch: "; BackBranch->dump());
bool ContinueOnTrue = L->contains(BackBranch->getSuccessor(0));
// 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 = nullptr;
for (PHINode &PHI : L->getHeader()->phis()) {
InductionDescriptor ID;
if (InductionDescriptor::isInductionPHI(&PHI, L, SE, ID)) {
InductionPHI = &PHI;
LLVM_DEBUG(dbgs() << "Found induction PHI: "; InductionPHI->dump());
break;
}
}
if (!InductionPHI) {
LLVM_DEBUG(dbgs() << "Could not find induction PHI\n");
return false;
}
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
ICmpInst *Compare = dyn_cast<ICmpInst>(BackBranch->getCondition());
if (!Compare || !IsValidPredicate(Compare->getUnsignedPredicate()) ||
Compare->hasNUsesOrMore(2)) {
LLVM_DEBUG(dbgs() << "Could not find valid comparison\n");
return false;
}
IterationInstructions.insert(Compare);
LLVM_DEBUG(dbgs() << "Found comparison: "; Compare->dump());
// Find increment and limit from the compare
Increment = nullptr;
if (match(Compare->getOperand(0),
m_c_Add(m_Specific(InductionPHI), m_ConstantInt<1>()))) {
Increment = dyn_cast<BinaryOperator>(Compare->getOperand(0));
Limit = Compare->getOperand(1);
} else if (Compare->getUnsignedPredicate() == CmpInst::ICMP_NE &&
match(Compare->getOperand(1),
m_c_Add(m_Specific(InductionPHI), m_ConstantInt<1>()))) {
Increment = dyn_cast<BinaryOperator>(Compare->getOperand(1));
Limit = Compare->getOperand(0);
}
if (!Increment || Increment->hasNUsesOrMore(3)) {
LLVM_DEBUG(dbgs() << "Cound not find valid increment\n");
return false;
}
IterationInstructions.insert(Increment);
LLVM_DEBUG(dbgs() << "Found increment: "; Increment->dump());
LLVM_DEBUG(dbgs() << "Found limit: "; Limit->dump());
assert(InductionPHI->getNumIncomingValues() == 2);
assert(InductionPHI->getIncomingValueForBlock(Latch) == Increment &&
"PHI value is not increment inst");
auto *CI = dyn_cast<ConstantInt>(
InductionPHI->getIncomingValueForBlock(L->getLoopPreheader()));
if (!CI || !CI->isZero()) {
LLVM_DEBUG(dbgs() << "PHI value is not zero: "; CI->dump());
return false;
}
LLVM_DEBUG(dbgs() << "Successfully found all loop components\n");
return true;
}
static bool checkPHIs(struct 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<PHINode *, 4> 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;
// 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<PHINode>(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<PHINode>(
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 (!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(struct FlattenInfo &FI,
SmallPtrSetImpl<Instruction *> &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<PHINode>(&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<BranchInst>(&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.InnerLimit))))
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;
}
static bool checkIVUsers(struct FlattenInfo &FI) {
// We require all uses of both induction variables to match this pattern:
//
// (OuterPHI * InnerLimit) + 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.
Value *InnerLimit = FI.InnerLimit;
if (FI.Widened &&
(isa<SExtInst>(InnerLimit) || isa<ZExtInst>(InnerLimit)))
InnerLimit = cast<Instruction>(InnerLimit)->getOperand(0);
// Check that all uses of the inner loop's induction variable match the
// expected pattern, recording the uses of the outer IV.
SmallPtrSet<Value *, 4> ValidOuterPHIUses;
for (User *U : FI.InnerInductionPHI->users()) {
if (U == FI.InnerIncrement)
continue;
// After widening the IVs, a trunc instruction might have been introduced, so
// look through truncs.
if (isa<TruncInst>(U)) {
if (!U->hasOneUse())
return false;
U = *U->user_begin();
}
LLVM_DEBUG(dbgs() << "Found use of inner induction variable: "; U->dump());
Value *MatchedMul;
Value *MatchedItCount;
bool IsAdd = match(U, m_c_Add(m_Specific(FI.InnerInductionPHI),
m_Value(MatchedMul))) &&
match(MatchedMul, m_c_Mul(m_Specific(FI.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(FI.InnerInductionPHI)),
m_Value(MatchedMul))) &&
match(MatchedMul,
m_c_Mul(m_Trunc(m_Specific(FI.OuterInductionPHI)),
m_Value(MatchedItCount)));
if ((IsAdd || IsAddTrunc) && MatchedItCount == InnerLimit) {
LLVM_DEBUG(dbgs() << "Use is optimisable\n");
ValidOuterPHIUses.insert(MatchedMul);
FI.LinearIVUses.insert(U);
} else {
LLVM_DEBUG(dbgs() << "Did not match expected pattern, bailing\n");
return false;
}
}
// Check that there are no uses of the outer IV other than the ones found
// as part of the pattern above.
for (User *U : FI.OuterInductionPHI->users()) {
if (U == FI.OuterIncrement)
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<TruncInst>(U)) {
for (auto *K : V->users()) {
if (!IsValidOuterPHIUses(K))
return false;
}
continue;
}
if (!IsValidOuterPHIUses(U))
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
// InnerLimit and OuterLimit can be assumed not to happen.
static OverflowResult checkOverflow(struct 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.InnerLimit, FI.OuterLimit, 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<GetElementPtrInst>(U)) {
// The IV is used as the operand of a GEP, 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(struct FlattenInfo &FI, DominatorTree *DT,
LoopInfo *LI, ScalarEvolution *SE,
AssumptionCache *AC, const TargetTransformInfo *TTI) {
SmallPtrSet<Instruction *, 8> IterationInstructions;
if (!findLoopComponents(FI.InnerLoop, IterationInstructions, FI.InnerInductionPHI,
FI.InnerLimit, FI.InnerIncrement, FI.InnerBranch, SE))
return false;
if (!findLoopComponents(FI.OuterLoop, IterationInstructions, FI.OuterInductionPHI,
FI.OuterLimit, FI.OuterIncrement, FI.OuterBranch, SE))
return false;
// Both of the loop limit values must be invariant in the outer loop
// (non-instructions are all inherently invariant).
if (!FI.OuterLoop->isLoopInvariant(FI.InnerLimit)) {
LLVM_DEBUG(dbgs() << "inner loop limit not invariant\n");
return false;
}
if (!FI.OuterLoop->isLoopInvariant(FI.OuterLimit)) {
LLVM_DEBUG(dbgs() << "outer loop limit 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(struct FlattenInfo &FI, DominatorTree *DT,
LoopInfo *LI, ScalarEvolution *SE,
AssumptionCache *AC,
const TargetTransformInfo *TTI) {
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.InnerLimit, FI.OuterLimit, "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<User>(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);
DT->deleteEdge(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);
LI->erase(FI.InnerLoop);
return true;
}
static bool CanWidenIV(struct 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
// (OuterLimit * InnerLimit) 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<WideIVInfo, 2> WideIVs;
SmallVector<WeakTrackingVH, 4> DeadInsts;
WideIVs.push_back( {FI.InnerInductionPHI, MaxLegalType, false });
WideIVs.push_back( {FI.OuterInductionPHI, MaxLegalType, false });
unsigned ElimExt;
unsigned Widened;
for (unsigned i = 0; i < WideIVs.size(); i++) {
PHINode *WidePhi = createWideIV(WideIVs[i], 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: "; WideIVs[i].NarrowIV->dump());
RecursivelyDeleteDeadPHINode(WideIVs[i].NarrowIV);
}
// After widening, rediscover all the loop components.
assert(Widened && "Widenend IV expected");
FI.Widened = true;
return CanFlattenLoopPair(FI, DT, LI, SE, AC, TTI);
}
static bool FlattenLoopPair(struct FlattenInfo &FI, DominatorTree *DT,
LoopInfo *LI, ScalarEvolution *SE,
AssumptionCache *AC,
const TargetTransformInfo *TTI) {
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.
if (CanWidenIV(FI, DT, LI, SE, AC, TTI))
return DoFlattenLoopPair(FI, DT, LI, SE, AC, TTI);
// 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);
}
bool Flatten(DominatorTree *DT, LoopInfo *LI, ScalarEvolution *SE,
AssumptionCache *AC, TargetTransformInfo *TTI) {
bool Changed = false;
for (auto *InnerLoop : LI->getLoopsInPreorder()) {
auto *OuterLoop = InnerLoop->getParentLoop();
if (!OuterLoop)
continue;
struct FlattenInfo FI(OuterLoop, InnerLoop);
Changed |= FlattenLoopPair(FI, DT, LI, SE, AC, TTI);
}
return Changed;
}
PreservedAnalyses LoopFlattenPass::run(Function &F,
FunctionAnalysisManager &AM) {
auto *DT = &AM.getResult<DominatorTreeAnalysis>(F);
auto *LI = &AM.getResult<LoopAnalysis>(F);
auto *SE = &AM.getResult<ScalarEvolutionAnalysis>(F);
auto *AC = &AM.getResult<AssumptionAnalysis>(F);
auto *TTI = &AM.getResult<TargetIRAnalysis>(F);
if (!Flatten(DT, LI, SE, AC, TTI))
return PreservedAnalyses::all();
PreservedAnalyses PA;
PA.preserveSet<CFGAnalyses>();
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<TargetTransformInfoWrapperPass>();
AU.addPreserved<TargetTransformInfoWrapperPass>();
AU.addRequired<AssumptionCacheTracker>();
AU.addPreserved<AssumptionCacheTracker>();
}
};
} // 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<ScalarEvolutionWrapperPass>().getSE();
LoopInfo *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
auto *DTWP = getAnalysisIfAvailable<DominatorTreeWrapperPass>();
DominatorTree *DT = DTWP ? &DTWP->getDomTree() : nullptr;
auto &TTIP = getAnalysis<TargetTransformInfoWrapperPass>();
auto *TTI = &TTIP.getTTI(F);
auto *AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
return Flatten(DT, LI, SE, AC, TTI);
}
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