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authorSanjay Patel <spatel@rotateright.com>2019-10-05 18:03:58 +0000
committerSanjay Patel <spatel@rotateright.com>2019-10-05 18:03:58 +0000
commite2321bb4488a81b87742f3343e3bdf8e161aa35b (patch)
tree48e6260a743b8adf2a2866d6250955e09c2ce8a6 /llvm/lib/Transforms/Vectorize
parent9ecacb0d54fb89dc7e6da66d9ecae934ca5c01d4 (diff)
downloadbcm5719-llvm-e2321bb4488a81b87742f3343e3bdf8e161aa35b.tar.gz
bcm5719-llvm-e2321bb4488a81b87742f3343e3bdf8e161aa35b.zip
[SLP] avoid reduction transform on patterns that the backend can load-combine
I don't see an ideal solution to these 2 related, potentially large, perf regressions: https://bugs.llvm.org/show_bug.cgi?id=42708 https://bugs.llvm.org/show_bug.cgi?id=43146 We decided that load combining was unsuitable for IR because it could obscure other optimizations in IR. So we removed the LoadCombiner pass and deferred to the backend. Therefore, preventing SLP from destroying load combine opportunities requires that it recognizes patterns that could be combined later, but not do the optimization itself ( it's not a vector combine anyway, so it's probably out-of-scope for SLP). Here, we add a scalar cost model adjustment with a conservative pattern match and cost summation for a multi-instruction sequence that can probably be reduced later. This should prevent SLP from creating a vector reduction unless that sequence is extremely cheap. In the x86 tests shown (and discussed in more detail in the bug reports), SDAG combining will produce a single instruction on these tests like: movbe rax, qword ptr [rdi] or: mov rax, qword ptr [rdi] Not some (half) vector monstrosity as we currently do using SLP: vpmovzxbq ymm0, dword ptr [rdi + 1] # ymm0 = mem[0],zero,zero,.. vpsllvq ymm0, ymm0, ymmword ptr [rip + .LCPI0_0] movzx eax, byte ptr [rdi] movzx ecx, byte ptr [rdi + 5] shl rcx, 40 movzx edx, byte ptr [rdi + 6] shl rdx, 48 or rdx, rcx movzx ecx, byte ptr [rdi + 7] shl rcx, 56 or rcx, rdx or rcx, rax vextracti128 xmm1, ymm0, 1 vpor xmm0, xmm0, xmm1 vpshufd xmm1, xmm0, 78 # xmm1 = xmm0[2,3,0,1] vpor xmm0, xmm0, xmm1 vmovq rax, xmm0 or rax, rcx vzeroupper ret Differential Revision: https://reviews.llvm.org/D67841 llvm-svn: 373833
Diffstat (limited to 'llvm/lib/Transforms/Vectorize')
-rw-r--r--llvm/lib/Transforms/Vectorize/SLPVectorizer.cpp15
1 files changed, 12 insertions, 3 deletions
diff --git a/llvm/lib/Transforms/Vectorize/SLPVectorizer.cpp b/llvm/lib/Transforms/Vectorize/SLPVectorizer.cpp
index 99428c6c5de..ad12646bdee 100644
--- a/llvm/lib/Transforms/Vectorize/SLPVectorizer.cpp
+++ b/llvm/lib/Transforms/Vectorize/SLPVectorizer.cpp
@@ -6499,10 +6499,19 @@ private:
int ScalarReduxCost = 0;
switch (ReductionData.getKind()) {
- case RK_Arithmetic:
- ScalarReduxCost =
- TTI->getArithmeticInstrCost(ReductionData.getOpcode(), ScalarTy);
+ case RK_Arithmetic: {
+ // Note: Passing in the reduction operands allows the cost model to match
+ // load combining patterns for this reduction.
+ auto *ReduxInst = cast<Instruction>(ReductionRoot);
+ SmallVector<const Value *, 2> OperandList;
+ for (Value *Operand : ReduxInst->operands())
+ OperandList.push_back(Operand);
+ ScalarReduxCost = TTI->getArithmeticInstrCost(ReductionData.getOpcode(),
+ ScalarTy, TargetTransformInfo::OK_AnyValue,
+ TargetTransformInfo::OK_AnyValue, TargetTransformInfo::OP_None,
+ TargetTransformInfo::OP_None, OperandList);
break;
+ }
case RK_Min:
case RK_Max:
case RK_UMin:
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