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[LV] Add helper function for predicated block probability (NFC)

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The cost model has to estimate the probability of executing predicated blocks.
However, we currently always assume predicated blocks have a 50% chance of
executing (this value is hardcoded in several places throughout the code).
Since we always use the same value, this patch adds a helper function for
getting this uniform probability. The function simplifies some comments and
makes our assumptions more clear. In the future, we may want to extend this
with actual block probability information if it's available.

llvm-svn: 283354
This commit is contained in:
Matthew Simpson 2016-10-05 18:30:36 +00:00
parent fdd6126933
commit 2384e6e79c
1 changed files with 25 additions and 13 deletions
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38
lib/Transforms/Vectorize/LoopVectorize.cpp
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@ -342,6 +342,14 @@ static bool hasIrregularType(Type *Ty, const DataLayout &DL, unsigned VF) {
return DL.getTypeAllocSizeInBits(Ty) != DL.getTypeSizeInBits(Ty);
}
/// A helper function that returns the reciprocal of the block probability of
/// predicated blocks. If we return X, we are assuming the predicated block
/// will execute once for for every X iterations of the loop header.
///
/// TODO: We should use actual block probability here, if available. Currently,
/// we always assume predicated blocks have a 50% chance of executing.
static unsigned getReciprocalPredBlockProb() { return 2; }
/// InnerLoopVectorizer vectorizes loops which contain only one basic
/// block to a specified vectorization factor (VF).
/// This class performs the widening of scalars into vectors, or multiple
@ -3554,12 +3562,11 @@ static unsigned getScalarizationOverhead(Type *Ty, bool Insert, bool Extract,
}
}
// We assume that if-converted blocks have a 50% chance of being executed.
// Predicated scalarized instructions are avoided due to the CF that bypasses
// turned off lanes. The extracts and inserts will be sinked/hoisted to the
// predicated basic-block and are subjected to the same assumption.
// If we have a predicated instruction, it may not be executed for each
// vector lane. Scale the cost by the probability of executing the
// predicated block.
if (Predicated)
Cost /= 2;
Cost /= getReciprocalPredBlockProb();
return Cost;
}
@ -6397,11 +6404,14 @@ LoopVectorizationCostModel::expectedCost(unsigned VF) {
<< VF << " For instruction: " << I << '\n');
}
// We assume that if-converted blocks have a 50% chance of being executed.
// When the code is scalar then some of the blocks are avoided due to CF.
// When the code is vectorized we execute all code paths.
// If we are vectorizing a predicated block, it will have been
// if-converted. This means that the block's instructions (aside from
// stores and instructions that may divide by zero) will now be
// unconditionally executed. For the scalar case, we may not always execute
// the predicated block. Thus, scale the block's cost by the probability of
// executing it.
if (VF == 1 && Legal->blockNeedsPredication(BB))
BlockCost.first /= 2;
BlockCost.first /= getReciprocalPredBlockProb();
Cost.first += BlockCost.first;
Cost.second |= BlockCost.second;
@ -6518,11 +6528,13 @@ unsigned LoopVectorizationCostModel::getInstructionCost(Instruction *I,
case Instruction::SDiv:
case Instruction::URem:
case Instruction::SRem:
// We assume that if-converted blocks have a 50% chance of being executed.
// Predicated scalarized instructions are avoided due to the CF that
// bypasses turned off lanes. If we are not predicating, fallthrough.
// If we have a predicated instruction, it may not be executed for each
// vector lane. Get the scalarization cost and scale this amount by the
// probability of executing the predicated block. If the instruction is not
// predicated, we fall through to the next case.
if (VF > 1 && Legal->isScalarWithPredication(I))
return VF * TTI.getArithmeticInstrCost(I->getOpcode(), RetTy) / 2 +
return VF * TTI.getArithmeticInstrCost(I->getOpcode(), RetTy) /
getReciprocalPredBlockProb() +
getScalarizationOverhead(I, VF, true, TTI);
case Instruction::Add:
case Instruction::FAdd: