Convert array of eight bytes to eight integers
I am working with the Xeon Phi Knights Landing. I need to do a gather operation from an array of doubles. The list of indices comes from an array of chars. The gather operations are either _mm512_i32gather_pd
or _mm512_i64gather_pd
. As I understand it, I either need to convert eight chars to to eight 32-bit integers or eight chars to 64-bit integers. I have gone with the first choice for _mm512_i32gather_pd
.
I have created two functions get_index
and get_index2
to convert eight chars to a __m256i
. The assembly for get_index
is simpler than for get_index2
see https://godbolt.org/z/lhg9fX. However, in my code get_index2
is significantly faster. Why is this? I am using ICC 18. Maybe there is a better solution than either of these two functions?
#include <x86intrin.h>
#include <inttypes.h>
__m256i get_index(char *index) {
int64_t x = *(int64_t *)&index[0];
const __m256i t3 = _mm256_setr_epi8(
0,0x80,0x80,0x80,
1,0x80,0x80,0x80,
2,0x80,0x80,0x80,
3,0x80,0x80,0x80,
4,0x80,0x80,0x80,
5,0x80,0x80,0x80,
6,0x80,0x80,0x80,
7,0x80,0x80,0x80);
__m256i t2 = _mm256_set1_epi64x(x);
__m256i t4 = _mm256_shuffle_epi8(t2, t3);
return t4;
}
__m256i get_index2(char *index) {
const __m256i t3 = _mm256_setr_epi8(
0,0x80,0x80,0x80,
1,0x80,0x80,0x80,
2,0x80,0x80,0x80,
3,0x80,0x80,0x80,
4,0x80,0x80,0x80,
5,0x80,0x80,0x80,
6,0x80,0x80,0x80,
7,0x80,0x80,0x80);
__m128i t1 = _mm_loadl_epi64((__m128i*)index);
__m256i t2 = _mm256_inserti128_si256(_mm256_castsi128_si256(t1), t1, 1);
__m256i t4 = _mm256_shuffle_epi8(t2, t3);
return t4;
}
x86 avx2 xeon-phi avx512 knights-landing
add a comment |
I am working with the Xeon Phi Knights Landing. I need to do a gather operation from an array of doubles. The list of indices comes from an array of chars. The gather operations are either _mm512_i32gather_pd
or _mm512_i64gather_pd
. As I understand it, I either need to convert eight chars to to eight 32-bit integers or eight chars to 64-bit integers. I have gone with the first choice for _mm512_i32gather_pd
.
I have created two functions get_index
and get_index2
to convert eight chars to a __m256i
. The assembly for get_index
is simpler than for get_index2
see https://godbolt.org/z/lhg9fX. However, in my code get_index2
is significantly faster. Why is this? I am using ICC 18. Maybe there is a better solution than either of these two functions?
#include <x86intrin.h>
#include <inttypes.h>
__m256i get_index(char *index) {
int64_t x = *(int64_t *)&index[0];
const __m256i t3 = _mm256_setr_epi8(
0,0x80,0x80,0x80,
1,0x80,0x80,0x80,
2,0x80,0x80,0x80,
3,0x80,0x80,0x80,
4,0x80,0x80,0x80,
5,0x80,0x80,0x80,
6,0x80,0x80,0x80,
7,0x80,0x80,0x80);
__m256i t2 = _mm256_set1_epi64x(x);
__m256i t4 = _mm256_shuffle_epi8(t2, t3);
return t4;
}
__m256i get_index2(char *index) {
const __m256i t3 = _mm256_setr_epi8(
0,0x80,0x80,0x80,
1,0x80,0x80,0x80,
2,0x80,0x80,0x80,
3,0x80,0x80,0x80,
4,0x80,0x80,0x80,
5,0x80,0x80,0x80,
6,0x80,0x80,0x80,
7,0x80,0x80,0x80);
__m128i t1 = _mm_loadl_epi64((__m128i*)index);
__m256i t2 = _mm256_inserti128_si256(_mm256_castsi128_si256(t1), t1, 1);
__m256i t4 = _mm256_shuffle_epi8(t2, t3);
return t4;
}
x86 avx2 xeon-phi avx512 knights-landing
2
KNL has very slow 256-bitvpshufb ymm
(12 uops, 23c latency, 12c throughput), and 128-bit XMM is slow, too. (MMX is fast :P). See Agner Fog's tables. Why can't you usevpmovzxbd
orbq
like a normal person?__m512i _mm512_cvtepu8_epi32(__m128i a)
or_mm256_cvtepu8_epi32
. Those are all single-uop with 2c throughput.
– Peter Cordes
Nov 24 '18 at 18:28
That doesn't explain your results, though. What loop did these functions inline into? Are you sure they didn't optimize differently somehow given different surrounding code? Otherwise IDK why a load + insert would be faster than a qword broadcast-load. Maybe some kind of front-end effect? Again we'd need to see the whole loop to guess about the front-end.
– Peter Cordes
Nov 24 '18 at 18:34
1
@PeterCordes, thank you for pointing out_mm256_cvtepu8_epi32
, that's exactly what I want, the result is no faster thanget_index2
though in my code. Maybe ICC convertsget_index2
to vpmovzxbd in my code anyway. I did not think of this because I'm a bit rusty with vectorization. But now I get about a 4x improvement with manual vectorization compare to ICC auto-vectorization (with#pragma ivdep
). I'm vectorizing stencil code.
– Z boson
Nov 26 '18 at 12:10
add a comment |
I am working with the Xeon Phi Knights Landing. I need to do a gather operation from an array of doubles. The list of indices comes from an array of chars. The gather operations are either _mm512_i32gather_pd
or _mm512_i64gather_pd
. As I understand it, I either need to convert eight chars to to eight 32-bit integers or eight chars to 64-bit integers. I have gone with the first choice for _mm512_i32gather_pd
.
I have created two functions get_index
and get_index2
to convert eight chars to a __m256i
. The assembly for get_index
is simpler than for get_index2
see https://godbolt.org/z/lhg9fX. However, in my code get_index2
is significantly faster. Why is this? I am using ICC 18. Maybe there is a better solution than either of these two functions?
#include <x86intrin.h>
#include <inttypes.h>
__m256i get_index(char *index) {
int64_t x = *(int64_t *)&index[0];
const __m256i t3 = _mm256_setr_epi8(
0,0x80,0x80,0x80,
1,0x80,0x80,0x80,
2,0x80,0x80,0x80,
3,0x80,0x80,0x80,
4,0x80,0x80,0x80,
5,0x80,0x80,0x80,
6,0x80,0x80,0x80,
7,0x80,0x80,0x80);
__m256i t2 = _mm256_set1_epi64x(x);
__m256i t4 = _mm256_shuffle_epi8(t2, t3);
return t4;
}
__m256i get_index2(char *index) {
const __m256i t3 = _mm256_setr_epi8(
0,0x80,0x80,0x80,
1,0x80,0x80,0x80,
2,0x80,0x80,0x80,
3,0x80,0x80,0x80,
4,0x80,0x80,0x80,
5,0x80,0x80,0x80,
6,0x80,0x80,0x80,
7,0x80,0x80,0x80);
__m128i t1 = _mm_loadl_epi64((__m128i*)index);
__m256i t2 = _mm256_inserti128_si256(_mm256_castsi128_si256(t1), t1, 1);
__m256i t4 = _mm256_shuffle_epi8(t2, t3);
return t4;
}
x86 avx2 xeon-phi avx512 knights-landing
I am working with the Xeon Phi Knights Landing. I need to do a gather operation from an array of doubles. The list of indices comes from an array of chars. The gather operations are either _mm512_i32gather_pd
or _mm512_i64gather_pd
. As I understand it, I either need to convert eight chars to to eight 32-bit integers or eight chars to 64-bit integers. I have gone with the first choice for _mm512_i32gather_pd
.
I have created two functions get_index
and get_index2
to convert eight chars to a __m256i
. The assembly for get_index
is simpler than for get_index2
see https://godbolt.org/z/lhg9fX. However, in my code get_index2
is significantly faster. Why is this? I am using ICC 18. Maybe there is a better solution than either of these two functions?
#include <x86intrin.h>
#include <inttypes.h>
__m256i get_index(char *index) {
int64_t x = *(int64_t *)&index[0];
const __m256i t3 = _mm256_setr_epi8(
0,0x80,0x80,0x80,
1,0x80,0x80,0x80,
2,0x80,0x80,0x80,
3,0x80,0x80,0x80,
4,0x80,0x80,0x80,
5,0x80,0x80,0x80,
6,0x80,0x80,0x80,
7,0x80,0x80,0x80);
__m256i t2 = _mm256_set1_epi64x(x);
__m256i t4 = _mm256_shuffle_epi8(t2, t3);
return t4;
}
__m256i get_index2(char *index) {
const __m256i t3 = _mm256_setr_epi8(
0,0x80,0x80,0x80,
1,0x80,0x80,0x80,
2,0x80,0x80,0x80,
3,0x80,0x80,0x80,
4,0x80,0x80,0x80,
5,0x80,0x80,0x80,
6,0x80,0x80,0x80,
7,0x80,0x80,0x80);
__m128i t1 = _mm_loadl_epi64((__m128i*)index);
__m256i t2 = _mm256_inserti128_si256(_mm256_castsi128_si256(t1), t1, 1);
__m256i t4 = _mm256_shuffle_epi8(t2, t3);
return t4;
}
x86 avx2 xeon-phi avx512 knights-landing
x86 avx2 xeon-phi avx512 knights-landing
asked Nov 24 '18 at 14:25
Z bosonZ boson
20.9k781153
20.9k781153
2
KNL has very slow 256-bitvpshufb ymm
(12 uops, 23c latency, 12c throughput), and 128-bit XMM is slow, too. (MMX is fast :P). See Agner Fog's tables. Why can't you usevpmovzxbd
orbq
like a normal person?__m512i _mm512_cvtepu8_epi32(__m128i a)
or_mm256_cvtepu8_epi32
. Those are all single-uop with 2c throughput.
– Peter Cordes
Nov 24 '18 at 18:28
That doesn't explain your results, though. What loop did these functions inline into? Are you sure they didn't optimize differently somehow given different surrounding code? Otherwise IDK why a load + insert would be faster than a qword broadcast-load. Maybe some kind of front-end effect? Again we'd need to see the whole loop to guess about the front-end.
– Peter Cordes
Nov 24 '18 at 18:34
1
@PeterCordes, thank you for pointing out_mm256_cvtepu8_epi32
, that's exactly what I want, the result is no faster thanget_index2
though in my code. Maybe ICC convertsget_index2
to vpmovzxbd in my code anyway. I did not think of this because I'm a bit rusty with vectorization. But now I get about a 4x improvement with manual vectorization compare to ICC auto-vectorization (with#pragma ivdep
). I'm vectorizing stencil code.
– Z boson
Nov 26 '18 at 12:10
add a comment |
2
KNL has very slow 256-bitvpshufb ymm
(12 uops, 23c latency, 12c throughput), and 128-bit XMM is slow, too. (MMX is fast :P). See Agner Fog's tables. Why can't you usevpmovzxbd
orbq
like a normal person?__m512i _mm512_cvtepu8_epi32(__m128i a)
or_mm256_cvtepu8_epi32
. Those are all single-uop with 2c throughput.
– Peter Cordes
Nov 24 '18 at 18:28
That doesn't explain your results, though. What loop did these functions inline into? Are you sure they didn't optimize differently somehow given different surrounding code? Otherwise IDK why a load + insert would be faster than a qword broadcast-load. Maybe some kind of front-end effect? Again we'd need to see the whole loop to guess about the front-end.
– Peter Cordes
Nov 24 '18 at 18:34
1
@PeterCordes, thank you for pointing out_mm256_cvtepu8_epi32
, that's exactly what I want, the result is no faster thanget_index2
though in my code. Maybe ICC convertsget_index2
to vpmovzxbd in my code anyway. I did not think of this because I'm a bit rusty with vectorization. But now I get about a 4x improvement with manual vectorization compare to ICC auto-vectorization (with#pragma ivdep
). I'm vectorizing stencil code.
– Z boson
Nov 26 '18 at 12:10
2
2
KNL has very slow 256-bit
vpshufb ymm
(12 uops, 23c latency, 12c throughput), and 128-bit XMM is slow, too. (MMX is fast :P). See Agner Fog's tables. Why can't you use vpmovzxbd
or bq
like a normal person? __m512i _mm512_cvtepu8_epi32(__m128i a)
or _mm256_cvtepu8_epi32
. Those are all single-uop with 2c throughput.– Peter Cordes
Nov 24 '18 at 18:28
KNL has very slow 256-bit
vpshufb ymm
(12 uops, 23c latency, 12c throughput), and 128-bit XMM is slow, too. (MMX is fast :P). See Agner Fog's tables. Why can't you use vpmovzxbd
or bq
like a normal person? __m512i _mm512_cvtepu8_epi32(__m128i a)
or _mm256_cvtepu8_epi32
. Those are all single-uop with 2c throughput.– Peter Cordes
Nov 24 '18 at 18:28
That doesn't explain your results, though. What loop did these functions inline into? Are you sure they didn't optimize differently somehow given different surrounding code? Otherwise IDK why a load + insert would be faster than a qword broadcast-load. Maybe some kind of front-end effect? Again we'd need to see the whole loop to guess about the front-end.
– Peter Cordes
Nov 24 '18 at 18:34
That doesn't explain your results, though. What loop did these functions inline into? Are you sure they didn't optimize differently somehow given different surrounding code? Otherwise IDK why a load + insert would be faster than a qword broadcast-load. Maybe some kind of front-end effect? Again we'd need to see the whole loop to guess about the front-end.
– Peter Cordes
Nov 24 '18 at 18:34
1
1
@PeterCordes, thank you for pointing out
_mm256_cvtepu8_epi32
, that's exactly what I want, the result is no faster than get_index2
though in my code. Maybe ICC converts get_index2
to vpmovzxbd in my code anyway. I did not think of this because I'm a bit rusty with vectorization. But now I get about a 4x improvement with manual vectorization compare to ICC auto-vectorization (with #pragma ivdep
). I'm vectorizing stencil code.– Z boson
Nov 26 '18 at 12:10
@PeterCordes, thank you for pointing out
_mm256_cvtepu8_epi32
, that's exactly what I want, the result is no faster than get_index2
though in my code. Maybe ICC converts get_index2
to vpmovzxbd in my code anyway. I did not think of this because I'm a bit rusty with vectorization. But now I get about a 4x improvement with manual vectorization compare to ICC auto-vectorization (with #pragma ivdep
). I'm vectorizing stencil code.– Z boson
Nov 26 '18 at 12:10
add a comment |
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2
KNL has very slow 256-bit
vpshufb ymm
(12 uops, 23c latency, 12c throughput), and 128-bit XMM is slow, too. (MMX is fast :P). See Agner Fog's tables. Why can't you usevpmovzxbd
orbq
like a normal person?__m512i _mm512_cvtepu8_epi32(__m128i a)
or_mm256_cvtepu8_epi32
. Those are all single-uop with 2c throughput.– Peter Cordes
Nov 24 '18 at 18:28
That doesn't explain your results, though. What loop did these functions inline into? Are you sure they didn't optimize differently somehow given different surrounding code? Otherwise IDK why a load + insert would be faster than a qword broadcast-load. Maybe some kind of front-end effect? Again we'd need to see the whole loop to guess about the front-end.
– Peter Cordes
Nov 24 '18 at 18:34
1
@PeterCordes, thank you for pointing out
_mm256_cvtepu8_epi32
, that's exactly what I want, the result is no faster thanget_index2
though in my code. Maybe ICC convertsget_index2
to vpmovzxbd in my code anyway. I did not think of this because I'm a bit rusty with vectorization. But now I get about a 4x improvement with manual vectorization compare to ICC auto-vectorization (with#pragma ivdep
). I'm vectorizing stencil code.– Z boson
Nov 26 '18 at 12:10