以下循环将一个整数矩阵转置为另一个整数矩阵。当我有趣地编译时,它会生成 movaps 指令以将结果存储到输出矩阵中。为什么gcc
这样做?
数据:
int __attribute__(( aligned(16))) t[N][M]
, __attribute__(( aligned(16))) c_tra[N][M];
循环:
for( i=0; i<N; i+=4){
for(j=0; j<M; j+=4){
row0 = _mm_load_si128((__m128i *)&t[i][j]);
row1 = _mm_load_si128((__m128i *)&t[i+1][j]);
row2 = _mm_load_si128((__m128i *)&t[i+2][j]);
row3 = _mm_load_si128((__m128i *)&t[i+3][j]);
__t0 = _mm_unpacklo_epi32(row0, row1);
__t1 = _mm_unpacklo_epi32(row2, row3);
__t2 = _mm_unpackhi_epi32(row0, row1);
__t3 = _mm_unpackhi_epi32(row2, row3);
/* values back into I[0-3] */
row0 = _mm_unpacklo_epi64(__t0, __t1);
row1 = _mm_unpackhi_epi64(__t0, __t1);
row2 = _mm_unpacklo_epi64(__t2, __t3);
row3 = _mm_unpackhi_epi64(__t2, __t3);
_mm_store_si128((__m128i *)&c_tra[j][i], row0);
_mm_store_si128((__m128i *)&c_tra[j+1][i], row1);
_mm_store_si128((__m128i *)&c_tra[j+2][i], row2);
_mm_store_si128((__m128i *)&c_tra[j+3][i], row3);
}
}
汇编生成的代码:
.L39:
lea rcx, [rsi+rdx]
movdqa xmm1, XMMWORD PTR [rdx]
add rdx, 16
add rax, 2048
movdqa xmm6, XMMWORD PTR [rcx+rdi]
movdqa xmm3, xmm1
movdqa xmm2, XMMWORD PTR [rcx+r9]
punpckldq xmm3, xmm6
movdqa xmm5, XMMWORD PTR [rcx+r10]
movdqa xmm4, xmm2
punpckhdq xmm1, xmm6
punpckldq xmm4, xmm5
punpckhdq xmm2, xmm5
movdqa xmm5, xmm3
punpckhqdq xmm3, xmm4
punpcklqdq xmm5, xmm4
movdqa xmm4, xmm1
punpckhqdq xmm1, xmm2
punpcklqdq xmm4, xmm2
movaps XMMWORD PTR [rax-2048], xmm5
movaps XMMWORD PTR [rax-1536], xmm3
movaps XMMWORD PTR [rax-1024], xmm4
movaps XMMWORD PTR [rax-512], xmm1
cmp r11, rdx
jne .L39
gcc -Wall -msse4.2 -masm="intel"-O2 -c -S
天湖
linuxmint
-mavx2
或 -march=naticve
生成 VEX 编码:vmovaps
。
最佳答案
从功能上讲,这些指令是相同的。 我不喜欢复制+粘贴其他人的陈述作为我的陈述,所以解释它的链接很少:
Difference between MOVDQA and MOVAPS x86 instructions?
https://software.intel.com/en-us/forums/intel-isa-extensions/topic/279587
http://masm32.com/board/index.php?topic=1138.0
https://www.gamedev.net/blog/615/entry-2250281-demystifying-sse-move-instructions/
简短版本:
So for the most part, you should try to use the move instruction that corresponds with the operations you are going to use on those registers. However, there is an additional complication. Loads and stores to and from memory execute on a separate port from the integer and floating point units; thus instructions that load from memory into a register or store from a register into memory will experience the same delay regardless of the data type you attach to the move. Thus in this case, movaps, movapd, and movdqa will have the same delay no matter what data you use. Since movaps (and movups) is encoded in binary form with one less byte than the other two, it makes sense to use it for all reg-mem moves, regardless of the data type.
所以这是GCC优化。
关于gcc - 为什么这个SSE2程序(整数)生成movaps(浮点)?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/42250184/