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[LV] Refactor widenIntOrFpInduction. NFC.

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This untangles the logic in widenIntOrFpInduction in order to make more
explicit and visible how exactly the induction variable is lowered.

Differential Revision: https://reviews.llvm.org/D76686
This commit is contained in:
Sjoerd Meijer 2020-03-27 12:52:03 +00:00
parent 32f911d479
commit 5f6534c61b
1 changed files with 56 additions and 47 deletions
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103
lib/Transforms/Vectorize/LoopVectorize.cpp
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@ -1806,51 +1806,31 @@ void InnerLoopVectorizer::widenIntOrFpInduction(PHINode *IV, TruncInst *Trunc) {
auto ID = II->second;
assert(IV->getType() == ID.getStartValue()->getType() && "Types must match");
// The scalar value to broadcast. This will be derived from the canonical
// induction variable.
Value *ScalarIV = nullptr;
// The value from the original loop to which we are mapping the new induction
// variable.
Instruction *EntryVal = Trunc ? cast<Instruction>(Trunc) : IV;
// True if we have vectorized the induction variable.
auto VectorizedIV = false;
// Determine if we want a scalar version of the induction variable. This is
// true if the induction variable itself is not widened, or if it has at
// least one user in the loop that is not widened.
auto NeedsScalarIV = VF > 1 && needsScalarInduction(EntryVal);
auto &DL = OrigLoop->getHeader()->getModule()->getDataLayout();
// Generate code for the induction step. Note that induction steps are
// required to be loop-invariant
assert(PSE.getSE()->isLoopInvariant(ID.getStep(), OrigLoop) &&
"Induction step should be loop invariant");
auto &DL = OrigLoop->getHeader()->getModule()->getDataLayout();
Value *Step = nullptr;
if (PSE.getSE()->isSCEVable(IV->getType())) {
SCEVExpander Exp(*PSE.getSE(), DL, "induction");
Step = Exp.expandCodeFor(ID.getStep(), ID.getStep()->getType(),
LoopVectorPreHeader->getTerminator());
} else {
Step = cast<SCEVUnknown>(ID.getStep())->getValue();
}
auto CreateStepValue = [&](const SCEV *Step) -> Value * {
assert(PSE.getSE()->isLoopInvariant(Step, OrigLoop) &&
"Induction step should be loop invariant");
if (PSE.getSE()->isSCEVable(IV->getType())) {
SCEVExpander Exp(*PSE.getSE(), DL, "induction");
return Exp.expandCodeFor(Step, Step->getType(),
LoopVectorPreHeader->getTerminator());
}
return cast<SCEVUnknown>(Step)->getValue();
};
// Try to create a new independent vector induction variable. If we can't
// create the phi node, we will splat the scalar induction variable in each
// loop iteration.
if (VF > 1 && !shouldScalarizeInstruction(EntryVal)) {
createVectorIntOrFpInductionPHI(ID, Step, EntryVal);
VectorizedIV = true;
}
// If we haven't yet vectorized the induction variable, or if we will create
// a scalar one, we need to define the scalar induction variable and step
// values. If we were given a truncation type, truncate the canonical
// The scalar value to broadcast. This is derived from the canonical
// induction variable. If a truncation type is given, truncate the canonical
// induction variable and step. Otherwise, derive these values from the
// induction descriptor.
if (!VectorizedIV || NeedsScalarIV) {
ScalarIV = Induction;
auto CreateScalarIV = [&](Value *&Step) -> Value * {
Value *ScalarIV = Induction;
if (IV != OldInduction) {
ScalarIV = IV->getType()->isIntegerTy()
? Builder.CreateSExtOrTrunc(Induction, IV->getType())
@ -1866,12 +1846,12 @@ void InnerLoopVectorizer::widenIntOrFpInduction(PHINode *IV, TruncInst *Trunc) {
ScalarIV = Builder.CreateTrunc(ScalarIV, TruncType);
Step = Builder.CreateTrunc(Step, TruncType);
}
}
return ScalarIV;
};
// If we haven't yet vectorized the induction variable, splat the scalar
// induction variable, and build the necessary step vectors.
// TODO: Don't do it unless the vectorized IV is really required.
if (!VectorizedIV) {
// Create the vector values from the scalar IV, in the absence of creating a
// vector IV.
auto CreateSplatIV = [&](Value *ScalarIV, Value *Step) {
Value *Broadcasted = getBroadcastInstrs(ScalarIV);
for (unsigned Part = 0; Part < UF; ++Part) {
Value *EntryPart =
@ -1881,16 +1861,45 @@ void InnerLoopVectorizer::widenIntOrFpInduction(PHINode *IV, TruncInst *Trunc) {
addMetadata(EntryPart, Trunc);
recordVectorLoopValueForInductionCast(ID, EntryVal, EntryPart, Part);
}
};
// Now do the actual transformations, and start with creating the step value.
Value *Step = CreateStepValue(ID.getStep());
if (VF <= 1) {
Value *ScalarIV = CreateScalarIV(Step);
CreateSplatIV(ScalarIV, Step);
return;
}
// If an induction variable is only used for counting loop iterations or
// calculating addresses, it doesn't need to be widened. Create scalar steps
// that can be used by instructions we will later scalarize. Note that the
// addition of the scalar steps will not increase the number of instructions
// in the loop in the common case prior to InstCombine. We will be trading
// one vector extract for each scalar step.
if (NeedsScalarIV)
// Determine if we want a scalar version of the induction variable. This is
// true if the induction variable itself is not widened, or if it has at
// least one user in the loop that is not widened.
auto NeedsScalarIV = needsScalarInduction(EntryVal);
if (!NeedsScalarIV) {
createVectorIntOrFpInductionPHI(ID, Step, EntryVal);
return;
}
// Try to create a new independent vector induction variable. If we can't
// create the phi node, we will splat the scalar induction variable in each
// loop iteration.
if (!shouldScalarizeInstruction(EntryVal)) {
createVectorIntOrFpInductionPHI(ID, Step, EntryVal);
Value *ScalarIV = CreateScalarIV(Step);
// Create scalar steps that can be used by instructions we will later
// scalarize. Note that the addition of the scalar steps will not increase
// the number of instructions in the loop in the common case prior to
// InstCombine. We will be trading one vector extract for each scalar step.
buildScalarSteps(ScalarIV, Step, EntryVal, ID);
return;
}
// If we haven't yet vectorized the induction variable, splat the scalar
// induction variable, and build the necessary step vectors.
// TODO: Don't do it unless the vectorized IV is really required.
Value *ScalarIV = CreateScalarIV(Step);
CreateSplatIV(ScalarIV, Step);
buildScalarSteps(ScalarIV, Step, EntryVal, ID);
}
Value *InnerLoopVectorizer::getStepVector(Value *Val, int StartIdx, Value *Step,