This post is closely related to another one I posted some days ago. This time, I wrote a simple code that just adds a pair of arrays of elements, multiplies the result by the values in another array and stores it in a forth array, all variables floating point double precision typed.
I made two versions of that code: one with SSE instructions, using calls to and another one without them I then compiled them with gcc and -O0 optimization level. I write them below:
// SSE VERSION
#define N 10000
#define NTIMES 100000
#include <time.h>
#include <stdio.h>
#include <xmmintrin.h>
#include <pmmintrin.h>
double a[N] __attribute__((aligned(16)));
double b[N] __attribute__((aligned(16)));
double c[N] __attribute__((aligned(16)));
double r[N] __attribute__((aligned(16)));
int main(void){
int i, times;
for( times = 0; times < NTIMES; times++ ){
for( i = 0; i <N; i+= 2){
__m128d mm_a = _mm_load_pd( &a[i] );
_mm_prefetch( &a[i+4], _MM_HINT_T0 );
__m128d mm_b = _mm_load_pd( &b[i] );
_mm_prefetch( &b[i+4] , _MM_HINT_T0 );
__m128d mm_c = _mm_load_pd( &c[i] );
_mm_prefetch( &c[i+4] , _MM_HINT_T0 );
__m128d mm_r;
mm_r = _mm_add_pd( mm_a, mm_b );
mm_a = _mm_mul_pd( mm_r , mm_c );
_mm_store_pd( &r[i], mm_a );
}
}
}
//NO SSE VERSION
//same definitions as before
int main(void){
int i, times;
for( times = 0; times < NTIMES; times++ ){
for( i = 0; i < N; i++ ){
r[i] = (a[i]+b[i])*c[i];
}
}
}
When compiling them with -O0, gcc makes use of XMM/MMX registers and SSE intstructions, if not specifically given the -mno-sse (and others) options. I inspected the assembly code generated for the second code and I noticed that it makes use of movsd, addsd and mulsd instructions. So it makes use of SSE instructions but only of those that use the lowest part of the registers, if I am not wrong. The assembly code generated for the first C code made use, as expected, of the addp and mulpd instructions, though a pretty larger assembly code was generated.
Anyway, the first code should get better profit, as far as I know, of SIMD paradigm, since every iteration two result values are computed. Still that, the second code performs something such as a 25 per cent faster than the first one. I also made a test with single precision values and get similar results. What's the reason for that?
GCC has a range of optimization levels, plus individual options to enable or disable particular optimizations. The overall compiler optimization level is controlled by the command line option -On, where n is the required optimization level, as follows: -O0 . (default).
In short, SSE is short for Streaming SIMD Extensions, where SIMD = Single Instruction, Multiple Data. This is useful for performing a single mathematical or logical operation on many values at once, as is typically done for matrix or vector math operations.
The gcc option -O enables different levels of optimization. Use -O0 to disable them and use -S to output assembly.
The compiler optimizes to reduce the size of the binary instead of execution speed. If you do not specify an optimization option, gcc attempts to reduce the compilation time and to make debugging always yield the result expected from reading the source code.
Vectorization in GCC is enabled at -O3
. That's why at -O0
, you see only the ordinary scalar SSE2 instructions (movsd
, addsd
, etc). Using GCC 4.6.1 and your second example:
#define N 10000
#define NTIMES 100000
double a[N] __attribute__ ((aligned (16)));
double b[N] __attribute__ ((aligned (16)));
double c[N] __attribute__ ((aligned (16)));
double r[N] __attribute__ ((aligned (16)));
int
main (void)
{
int i, times;
for (times = 0; times < NTIMES; times++)
{
for (i = 0; i < N; ++i)
r[i] = (a[i] + b[i]) * c[i];
}
return 0;
}
and compiling with gcc -S -O3 -msse2 sse.c
produces for the inner loop the following instructions, which is pretty good:
.L3:
movapd a(%eax), %xmm0
addpd b(%eax), %xmm0
mulpd c(%eax), %xmm0
movapd %xmm0, r(%eax)
addl $16, %eax
cmpl $80000, %eax
jne .L3
As you can see, with the vectorization enabled GCC emits code to perform two loop iterations in parallel. It can be improved, though - this code uses the lower 128 bits of the SSE registers, but it can use the full the 256-bit YMM registers, by enabling the AVX encoding of SSE instructions (if available on the machine). So, compiling the same program with gcc -S -O3 -msse2 -mavx sse.c
gives for the inner loop:
.L3:
vmovapd a(%eax), %ymm0
vaddpd b(%eax), %ymm0, %ymm0
vmulpd c(%eax), %ymm0, %ymm0
vmovapd %ymm0, r(%eax)
addl $32, %eax
cmpl $80000, %eax
jne .L3
Note that v
in front of each instruction and that instructions use the 256-bit YMM registers, four iterations of the original loop are executed in parallel.
I would like to extend chill's answer and draw your attention on the fact that GCC seems not to be able to do the same smart use of the AVX instructions when iterating backwards.
Just replace the inner loop in chill's sample code with:
for (i = N-1; i >= 0; --i)
r[i] = (a[i] + b[i]) * c[i];
GCC (4.8.4) with options -S -O3 -mavx
produces:
.L5:
vmovsd a+79992(%rax), %xmm0
subq $8, %rax
vaddsd b+80000(%rax), %xmm0, %xmm0
vmulsd c+80000(%rax), %xmm0, %xmm0
vmovsd %xmm0, r+80000(%rax)
cmpq $-80000, %rax
jne .L5
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