diff options
| author | Arnold Schwaighofer <aschwaighofer@apple.com> | 2013-03-02 04:02:52 +0000 |
|---|---|---|
| committer | Arnold Schwaighofer <aschwaighofer@apple.com> | 2013-03-02 04:02:52 +0000 |
| commit | 5f0d9dbdf48a9efe16bfadf88e5335f7b9a8ec3f (patch) | |
| tree | e39c3262177b95d29a2415f009cabade61fdd135 /test/Transforms/LoopVectorize | |
| parent | 1c01af8f26f1ddca69d332dd8456fdeab3d1936e (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
Diffstat (limited to 'test/Transforms/LoopVectorize')
| -rw-r--r-- | test/Transforms/LoopVectorize/X86/avx1.ll | 4 |
1 files changed, 2 insertions, 2 deletions
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 |