I have a number of tight loops I'm trying to optimize with GCC and intrinsics. Consider for example the following function.
void triad(float *x, float *y, float *z, const int n) {
float k = 3.14159f;
int i;
__m256 k4 = _mm256_set1_ps(k);
for(i=0; i<n; i+=8) {
_mm256_store_ps(&z[i], _mm256_add_ps(_mm256_load_ps(&x[i]), _mm256_mul_ps(k4, _mm256_load_ps(&y[i]))));
}
}
This produces a main loop like this
20: vmulps ymm0,ymm1,[rsi+rax*1]
25: vaddps ymm0,ymm0,[rdi+rax*1]
2a: vmovaps [rdx+rax*1],ymm0
2f: add rax,0x20
33: cmp rax,rcx
36: jne 20
But the cmp
instruction is unnecessary. Instead of having rax
start at zero and finish at sizeof(float)*n
we can set the base pointers (rsi
, rdi
, and rdx
) to the end of the array and set rax
to -sizeof(float)*n
and then test for zero. I am able to do this with my own assembly code like this
.L2 vmulps ymm1, ymm2, [rdi+rax]
vaddps ymm0, ymm1, [rsi+rax]
vmovaps [rdx+rax], ymm0
add rax, 32
jne .L2
but I can't manage to get GCC to do this. I have several tests now where this makes a significant difference. Until recently GCC and intrinsics have severed me well so I'm wondering if there is a compiler switch or a way to reorder/change my code so the cmp
instruction is not produced with GCC.
I tried the following but it still produces cmp
. All variations I have tried still produce cmp
.
void triad2(float *x, float *y, float *z, const int n) {
float k = 3.14159f;
float *x2 = x+n;
float *y2 = y+n;
float *z2 = z+n;
int i;
__m256 k4 = _mm256_set1_ps(k);
for(i=-n; i<0; i+=8) {
_mm256_store_ps(&z2[i], _mm256_add_ps(_mm256_load_ps(&x2[i]), _mm256_mul_ps(k4, _mm256_load_ps(&y2[i]))));
}
}
Edit:
I'm interested in maximizing instruction level parallelism (ILP) for these functions for arrays which fit in the L1 cache (actually for n=2048
). Although unrolling can be used to improve the bandwidth it can decrease the ILP (assuming the full bandwidth can be attained without unrolling).
Edit:
Here is a table of results for a Core2 (pre Nehalem), a IvyBridge, and a Haswell system. Intrinsics is the results of using intrinsics, unroll1 is my assembly code not using cmp
, and unroll16 is my assembly code unrolling 16 times. The percentages are the percentage of the peak performance (frequency*num_bytes_cycle where num_bytes_cycle is 24 for SSE, 48 for AVX and 96 for FMA).
SSE AVX FMA
intrinsic 71.3% 90.9% 53.6%
unroll1 97.0% 96.1% 63.5%
unroll16 98.6% 90.4% 93.6%
ScottD 96.5%
32B code align 95.5%
For SSE I get almost as good a result without unrolling as with unroll but only if I don't use cmp
. On AVX I get the best result without unrolling and without using cmp
. It's interesting that on IB unrolling actually is worse. On Haswell I get by far the best result by unrolling. Which is why I asked this question. The source code to test this can be found in that question.
Edit:
Based on ScottD's answer I now get almost 97% with intrinsics for my Core2 system (pre Nehalem 64-bit mode). I'm not sure why the cmp
matters actually since it should take 2 clock cycles per iteration anyway. For Sandy Bridge it turns out the efficiency loss is due to code alignment not to the extra cmp
. On Haswell only unrolling works anyway.