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authorArnold Schwaighofer <aschwaighofer@apple.com>2013-03-02 04:02:52 +0000
committerArnold Schwaighofer <aschwaighofer@apple.com>2013-03-02 04:02:52 +0000
commit5f0d9dbdf48a9efe16bfadf88e5335f7b9a8ec3f (patch)
treee39c3262177b95d29a2415f009cabade61fdd135
parent1c01af8f26f1ddca69d332dd8456fdeab3d1936e (diff)
X86 cost model: Adjust cost for custom lowered vector multiplies
This matters for example in following matrix multiply: int **mmult(int rows, int cols, int **m1, int **m2, int **m3) { int i, j, k, val; for (i=0; i<rows; i++) { for (j=0; j<cols; j++) { val = 0; for (k=0; k<cols; k++) { val += m1[i][k] * m2[k][j]; } m3[i][j] = val; } } return(m3); } Taken from the test-suite benchmark Shootout. We estimate the cost of the multiply to be 2 while we generate 9 instructions for it and end up being quite a bit slower than the scalar version (48% on my machine). Also, properly differentiate between avx1 and avx2. On avx-1 we still split the vector into 2 128bits and handle the subvector muls like above with 9 instructions. Only on avx-2 will we have a cost of 9 for v4i64. I changed the test case in test/Transforms/LoopVectorize/X86/avx1.ll to use an add instead of a mul because with a mul we now no longer vectorize. I did verify that the mul would be indeed more expensive when vectorized with 3 kernels: for (i ...) r += a[i] * 3; for (i ...) m1[i] = m1[i] * 3; // This matches the test case in avx1.ll and a matrix multiply. In each case the vectorized version was considerably slower. radar://13304919 git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@176403 91177308-0d34-0410-b5e6-96231b3b80d8
-rw-r--r--lib/Target/X86/X86TargetTransformInfo.cpp34
-rw-r--r--test/Analysis/CostModel/X86/arith.ll32
-rw-r--r--test/Transforms/LoopVectorize/X86/avx1.ll4
3 files changed, 63 insertions, 7 deletions
diff --git a/lib/Target/X86/X86TargetTransformInfo.cpp b/lib/Target/X86/X86TargetTransformInfo.cpp
index fefb479da9..be2a997b8e 100644
--- a/lib/Target/X86/X86TargetTransformInfo.cpp
+++ b/lib/Target/X86/X86TargetTransformInfo.cpp
@@ -176,18 +176,42 @@ unsigned X86TTI::getArithmeticInstrCost(unsigned Opcode, Type *Ty) const {
{ ISD::MUL, MVT::v8i32, 4 },
{ ISD::SUB, MVT::v8i32, 4 },
{ ISD::ADD, MVT::v8i32, 4 },
- { ISD::MUL, MVT::v4i64, 4 },
{ ISD::SUB, MVT::v4i64, 4 },
{ ISD::ADD, MVT::v4i64, 4 },
- };
+ // A v4i64 multiply is custom lowered as two split v2i64 vectors that then
+ // are lowered as a series of long multiplies(3), shifts(4) and adds(2)
+ // Because we believe v4i64 to be a legal type, we must also include the
+ // split factor of two in the cost table. Therefore, the cost here is 18
+ // instead of 9.
+ { ISD::MUL, MVT::v4i64, 18 },
+ };
// Look for AVX1 lowering tricks.
- if (ST->hasAVX()) {
- int Idx = CostTableLookup<MVT>(AVX1CostTable, array_lengthof(AVX1CostTable), ISD,
- LT.second);
+ if (ST->hasAVX() && !ST->hasAVX2()) {
+ int Idx = CostTableLookup<MVT>(AVX1CostTable, array_lengthof(AVX1CostTable),
+ ISD, LT.second);
if (Idx != -1)
return LT.first * AVX1CostTable[Idx].Cost;
}
+
+ // Custom lowering of vectors.
+ static const CostTblEntry<MVT> CustomLowered[] = {
+ // A v2i64/v4i64 and multiply is custom lowered as a series of long
+ // multiplies(3), shifts(4) and adds(2).
+ { ISD::MUL, MVT::v2i64, 9 },
+ { ISD::MUL, MVT::v4i64, 9 },
+ };
+ int Idx = CostTableLookup<MVT>(CustomLowered, array_lengthof(CustomLowered),
+ ISD, LT.second);
+ if (Idx != -1)
+ return LT.first * CustomLowered[Idx].Cost;
+
+ // Special lowering of v4i32 mul on sse2, sse3: Lower v4i32 mul as 2x shuffle,
+ // 2x pmuludq, 2x shuffle.
+ if (ISD == ISD::MUL && LT.second == MVT::v4i32 && ST->hasSSE2() &&
+ !ST->hasSSE41())
+ return 6;
+
// Fallback to the default implementation.
return TargetTransformInfo::getArithmeticInstrCost(Opcode, Ty);
}
diff --git a/test/Analysis/CostModel/X86/arith.ll b/test/Analysis/CostModel/X86/arith.ll
index ae78d44aeb..f0521bae48 100644
--- a/test/Analysis/CostModel/X86/arith.ll
+++ b/test/Analysis/CostModel/X86/arith.ll
@@ -1,4 +1,6 @@
; RUN: opt < %s -cost-model -analyze -mtriple=x86_64-apple-macosx10.8.0 -mcpu=corei7-avx | FileCheck %s
+; RUN: opt < %s -cost-model -analyze -mtriple=x86_64-apple-macosx10.8.0 -mcpu=core2 | FileCheck %s --check-prefix=SSE3
+; RUN: opt < %s -cost-model -analyze -mtriple=x86_64-apple-macosx10.8.0 -mcpu=core-avx2 | FileCheck %s --check-prefix=AVX2
target datalayout = "e-p:64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:64-f32:32:32-f64:64:64-v64:64:64-v128:128:128-a0:0:64-s0:64:64-f80:128:128-n8:16:32:64-S128"
target triple = "x86_64-apple-macosx10.8.0"
@@ -32,7 +34,37 @@ define i32 @xor(i32 %arg) {
ret i32 undef
}
+; CHECK: mul
+define void @mul() {
+ ; A <2 x i32> gets expanded to a <2 x i64> vector.
+ ; A <2 x i64> vector multiply is implemented using
+ ; 3 PMULUDQ and 2 PADDS and 4 shifts.
+ ;CHECK: cost of 9 {{.*}} mul
+ %A0 = mul <2 x i32> undef, undef
+ ;CHECK: cost of 9 {{.*}} mul
+ %A1 = mul <2 x i64> undef, undef
+ ;CHECK: cost of 18 {{.*}} mul
+ %A2 = mul <4 x i64> undef, undef
+ ret void
+}
+
+; SSE3: sse3mull
+define void @sse3mull() {
+ ; SSE3: cost of 6 {{.*}} mul
+ %A0 = mul <4 x i32> undef, undef
+ ret void
+ ; SSE3: avx2mull
+}
+
+; AVX2: avx2mull
+define void @avx2mull() {
+ ; AVX2: cost of 9 {{.*}} mul
+ %A0 = mul <4 x i64> undef, undef
+ ret void
+ ; AVX2: fmul
+}
+; CHECK: fmul
define i32 @fmul(i32 %arg) {
;CHECK: cost of 1 {{.*}} fmul
%A = fmul <4 x float> undef, undef
diff --git a/test/Transforms/LoopVectorize/X86/avx1.ll b/test/Transforms/LoopVectorize/X86/avx1.ll
index a85c6fe0d5..6c0366eae9 100644
--- a/test/Transforms/LoopVectorize/X86/avx1.ll
+++ b/test/Transforms/LoopVectorize/X86/avx1.ll
@@ -27,7 +27,7 @@ define i32 @read_mod_write_single_ptr(float* nocapture %a, i32 %n) nounwind uwta
;CHECK: @read_mod_i64
-;CHECK: load <4 x i64>
+;CHECK: load <2 x i64>
;CHECK: ret i32
define i32 @read_mod_i64(i64* nocapture %a, i32 %n) nounwind uwtable ssp {
%1 = icmp sgt i32 %n, 0
@@ -37,7 +37,7 @@ define i32 @read_mod_i64(i64* nocapture %a, i32 %n) nounwind uwtable ssp {
%indvars.iv = phi i64 [ %indvars.iv.next, %.lr.ph ], [ 0, %0 ]
%2 = getelementptr inbounds i64* %a, i64 %indvars.iv
%3 = load i64* %2, align 4
- %4 = mul i64 %3, 3
+ %4 = add i64 %3, 3
store i64 %4, i64* %2, align 4
%indvars.iv.next = add i64 %indvars.iv, 1
%lftr.wideiv = trunc i64 %indvars.iv.next to i32