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Revert "[LoopVectorize] Simplify scalar cost calculation in getInstructionCost" 

This reverts commit 4afeda9157.
This commit is contained in:
David Sherwood 2021-04-27 15:46:03 +01:00
parent 4abba775a3
commit 6968520c3b
3 changed files with 27 additions and 74 deletions
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62
llvm/lib/Transforms/Vectorize/LoopVectorize.cpp
View File

@ -7316,37 +7316,10 @@ LoopVectorizationCostModel::getInstructionCost(Instruction *I, ElementCount VF,
Type *RetTy = I->getType();
if (canTruncateToMinimalBitwidth(I, VF))
RetTy = IntegerType::get(RetTy->getContext(), MinBWs[I]);
VectorTy = isScalarAfterVectorization(I, VF) ? RetTy : ToVectorTy(RetTy, VF);
auto SE = PSE.getSE();
TTI::TargetCostKind CostKind = TTI::TCK_RecipThroughput;
auto hasSingleCopyAfterVectorization = [this](Instruction *I,
ElementCount VF) -> bool {
if (VF.isScalar())
return true;
auto Scalarized = InstsToScalarize.find(VF);
assert(Scalarized != InstsToScalarize.end() &&
"VF not yet analyzed for scalarization profitability");
return !Scalarized->second.count(I) &&
llvm::all_of(I->users(), [&](User *U) {
auto *UI = cast<Instruction>(U);
return !Scalarized->second.count(UI);
});
};
if (isScalarAfterVectorization(I, VF)) {
// With the exception of GEPs and PHIs, after scalarization there should
// only be one copy of the instruction generated in the loop. This is
// because the VF is either 1, or any instructions that need scalarizing
// have already been dealt with by the the time we get here. As a result,
// it means we don't have to multiply the instruction cost by VF.
assert(I->getOpcode() == Instruction::GetElementPtr ||
I->getOpcode() == Instruction::PHI ||
hasSingleCopyAfterVectorization(I, VF));
VectorTy = RetTy;
} else
VectorTy = ToVectorTy(RetTy, VF);
// TODO: We need to estimate the cost of intrinsic calls.
switch (I->getOpcode()) {
case Instruction::GetElementPtr:
@ -7474,16 +7447,21 @@ LoopVectorizationCostModel::getInstructionCost(Instruction *I, ElementCount VF,
Op2VK = TargetTransformInfo::OK_UniformValue;
SmallVector<const Value *, 4> Operands(I->operand_values());
return TTI.getArithmeticInstrCost(
I->getOpcode(), VectorTy, CostKind, TargetTransformInfo::OK_AnyValue,
unsigned N = isScalarAfterVectorization(I, VF) ? VF.getKnownMinValue() : 1;
return N * TTI.getArithmeticInstrCost(
I->getOpcode(), VectorTy, CostKind,
TargetTransformInfo::OK_AnyValue,
Op2VK, TargetTransformInfo::OP_None, Op2VP, Operands, I);
}
case Instruction::FNeg: {
assert(!VF.isScalable() && "VF is assumed to be non scalable.");
return TTI.getArithmeticInstrCost(
I->getOpcode(), VectorTy, CostKind, TargetTransformInfo::OK_AnyValue,
TargetTransformInfo::OK_AnyValue, TargetTransformInfo::OP_None,
TargetTransformInfo::OP_None, I->getOperand(0), I);
unsigned N = isScalarAfterVectorization(I, VF) ? VF.getKnownMinValue() : 1;
return N * TTI.getArithmeticInstrCost(
I->getOpcode(), VectorTy, CostKind,
TargetTransformInfo::OK_AnyValue,
TargetTransformInfo::OK_AnyValue,
TargetTransformInfo::OP_None, TargetTransformInfo::OP_None,
I->getOperand(0), I);
}
case Instruction::Select: {
SelectInst *SI = cast<SelectInst>(I);
@ -7627,7 +7605,14 @@ LoopVectorizationCostModel::getInstructionCost(Instruction *I, ElementCount VF,
}
}
return TTI.getCastInstrCost(Opcode, VectorTy, SrcVecTy, CCH, CostKind, I);
unsigned N;
if (isScalarAfterVectorization(I, VF)) {
assert(!VF.isScalable() && "VF is assumed to be non scalable");
N = VF.getKnownMinValue();
} else
N = 1;
return N *
TTI.getCastInstrCost(Opcode, VectorTy, SrcVecTy, CCH, CostKind, I);
}
case Instruction::Call: {
bool NeedToScalarize;
@ -7642,8 +7627,11 @@ LoopVectorizationCostModel::getInstructionCost(Instruction *I, ElementCount VF,
case Instruction::ExtractValue:
return TTI.getInstructionCost(I, TTI::TCK_RecipThroughput);
default:
// This opcode is unknown. Assume that it is the same as 'mul'.
return TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy, CostKind);
// The cost of executing VF copies of the scalar instruction. This opcode
// is unknown. Assume that it is the same as 'mul'.
return VF.getKnownMinValue() * TTI.getArithmeticInstrCost(
Instruction::Mul, VectorTy, CostKind) +
getScalarizationOverhead(I, VF);
} // end of switch.
}

2
llvm/test/Transforms/LoopVectorize/AArch64/no_vector_instructions.ll
View File

@ -6,7 +6,7 @@ target triple = "aarch64--linux-gnu"
; CHECK-LABEL: all_scalar
; CHECK: LV: Found scalar instruction: %i.next = add nuw nsw i64 %i, 2
; CHECK: LV: Found an estimated cost of 1 for VF 2 For instruction: %i.next = add nuw nsw i64 %i, 2
; CHECK: LV: Found an estimated cost of 2 for VF 2 For instruction: %i.next = add nuw nsw i64 %i, 2
; CHECK: LV: Not considering vector loop of width 2 because it will not generate any vector instructions
;
define void @all_scalar(i64* %a, i64 %n) {

35
llvm/test/Transforms/LoopVectorize/AArch64/predication_costs.ll
View File

@ -86,41 +86,6 @@ for.end:
ret void
}
; CHECK-LABEL: predicated_store_phi
;
; Same as predicate_store except we use a pointer PHI to maintain the address
;
; CHECK: Found new scalar instruction: %addr = phi i32* [ %a, %entry ], [ %addr.next, %for.inc ]
; CHECK: Found new scalar instruction: %addr.next = getelementptr inbounds i32, i32* %addr, i64 1
; CHECK: Scalarizing and predicating: store i32 %tmp2, i32* %addr, align 4
; CHECK: Found an estimated cost of 0 for VF 2 For instruction: %addr = phi i32* [ %a, %entry ], [ %addr.next, %for.inc ]
; CHECK: Found an estimated cost of 3 for VF 2 For instruction: store i32 %tmp2, i32* %addr, align 4
;
define void @predicated_store_phi(i32* %a, i1 %c, i32 %x, i64 %n) {
entry:
br label %for.body
for.body:
%i = phi i64 [ 0, %entry ], [ %i.next, %for.inc ]
%addr = phi i32 * [ %a, %entry ], [ %addr.next, %for.inc ]
%tmp1 = load i32, i32* %addr, align 4
%tmp2 = add nsw i32 %tmp1, %x
br i1 %c, label %if.then, label %for.inc
if.then:
store i32 %tmp2, i32* %addr, align 4
br label %for.inc
for.inc:
%i.next = add nuw nsw i64 %i, 1
%cond = icmp slt i64 %i.next, %n
%addr.next = getelementptr inbounds i32, i32* %addr, i64 1
br i1 %cond, label %for.body, label %for.end
for.end:
ret void
}
; CHECK-LABEL: predicated_udiv_scalarized_operand
;
; This test checks that we correctly compute the cost of the predicated udiv