ikawrakow/ik_llama.cpp
1
0
Fork 0
mirror of https://github.com/ikawrakow/ik_llama.cpp.git synced 2026-02-24 23:24:13 +00:00
Code Issues Packages Projects Releases Wiki Activity

iq4_0_r4: Use AVX2 version for matrix x vector

Browse Source
This commit is contained in:
Iwan Kawrakow
2024-12-23 18:30:47 +02:00
parent 167479e027
commit 1f785d2a3a
1 changed files with 53 additions and 44 deletions
Download Patch File Download Diff File Expand all files Collapse all files

97
ggml/src/iqk/iqk_mul_mat.cpp
View File

@@ -2481,9 +2481,61 @@ static void mul_mat_iq4_nl_r4_q8_1(int n, const void * vx, size_t bx, const Data
}
#endif
template <int nrc_y>
static void mul_mat_q4_0_r4_q8_1_avx2(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
GGML_ASSERT(nrc_x%4 == 0);
Q8<nrc_y, block_q8_1_x4> q8(info);
auto m4 = _mm256_set1_epi8(0xf);
auto m1 = _mm256_set1_epi16(1);
int nb = n / QK4_NL;
GGML_ASSERT(nb%4 == 0);
__m256 acc[nrc_y] = {};
float d8[8*nrc_y];
for (int ix = 0; ix < nrc_x; ix += 4) {
const block_iq4_nl_r4 * iq4 = (const block_iq4_nl_r4 *)((const char *)vx + ix*bx);
for (int ib4 = 0; ib4 < nb/4; ++ib4) {
for (int iy = 0; iy < nrc_y; ++iy) {
auto scales = _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)q8.y[iy][ib4].d));
_mm256_storeu_ps(d8 + 8*iy, scales);
}
for (int k = 0; k < 4; ++k) {
auto scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq4[4*ib4+k].d));
auto scales = _mm256_set_m128(scales128, scales128);
auto scales_m = _mm256_mul_ps(scales, _mm256_set1_ps(-4.f));
auto bits1 = _mm256_loadu_si256((const __m256i *)iq4[4*ib4+k].qs+0);
auto bits2 = _mm256_loadu_si256((const __m256i *)iq4[4*ib4+k].qs+1);
auto q1 = _mm256_and_si256(bits1, m4);
auto q2 = _mm256_and_si256(bits2, m4);
auto q3 = _mm256_and_si256(_mm256_srli_epi16(bits1, 4), m4);
auto q4 = _mm256_and_si256(_mm256_srli_epi16(bits2, 4), m4);
for (int iy = 0; iy < nrc_y; ++iy) {
auto y = _mm256_loadu_si256((const __m256i*)q8.y[iy][ib4].qs+k);
auto sumi1 = _mm256_add_epi16(_mm256_maddubs_epi16(q1, _mm256_shuffle_epi32(y, 0x00)),
_mm256_maddubs_epi16(q2, _mm256_shuffle_epi32(y, 0x55)));
auto sumi2 = _mm256_add_epi16(_mm256_maddubs_epi16(q3, _mm256_shuffle_epi32(y, 0xaa)),
_mm256_maddubs_epi16(q4, _mm256_shuffle_epi32(y, 0xff)));
auto sumi = _mm256_madd_epi16(m1, _mm256_add_epi16(sumi1, sumi2));
auto d4d8 = _mm256_mul_ps(scales, _mm256_set1_ps(d8[8*iy+k]));
acc[iy] = _mm256_fmadd_ps(d4d8, _mm256_cvtepi32_ps(sumi), acc[iy]);
acc[iy] = _mm256_fmadd_ps(scales_m, _mm256_set1_ps(d8[8*iy+4+k]), acc[iy]);
}
}
}
for (int iy = 0; iy < nrc_y; ++iy) {
auto sum = _mm_add_ps(_mm256_castps256_ps128(acc[iy]), _mm256_extractf128_ps(acc[iy], 1));
info.store(ix, iy, sum);
acc[iy] = _mm256_setzero_ps();
}
}
}
#ifdef HAVE_FANCY_SIMD
template <int nrc_y>
static void mul_mat_q4_0_r4_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
if constexpr (nrc_y == 1) {
mul_mat_q4_0_r4_q8_1_avx2<1>(n, vx, bx, info, nrc_x);
return;
}
GGML_ASSERT(nrc_x%8 == 0);
Q8<nrc_y, block_q8_1_x4> q8(info);
auto m4 = _mm512_set1_epi8(0xf);
@@ -2537,50 +2589,7 @@ static void mul_mat_q4_0_r4_q8_1(int n, const void * vx, size_t bx, const DataIn
#else
template <int nrc_y>
static void mul_mat_q4_0_r4_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
GGML_ASSERT(nrc_x%4 == 0);
Q8<nrc_y, block_q8_1_x4> q8(info);
auto m4 = _mm256_set1_epi8(0xf);
auto m1 = _mm256_set1_epi16(1);
int nb = n / QK4_NL;
GGML_ASSERT(nb%4 == 0);
__m256 acc[nrc_y] = {};
float d8[8*nrc_y];
for (int ix = 0; ix < nrc_x; ix += 4) {
const block_iq4_nl_r4 * iq4 = (const block_iq4_nl_r4 *)((const char *)vx + ix*bx);
for (int ib4 = 0; ib4 < nb/4; ++ib4) {
for (int iy = 0; iy < nrc_y; ++iy) {
auto scales = _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)q8.y[iy][ib4].d));
_mm256_storeu_ps(d8 + 8*iy, scales);
}
for (int k = 0; k < 4; ++k) {
auto scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq4[4*ib4+k].d));
auto scales = _mm256_set_m128(scales128, scales128);
auto scales_m = _mm256_mul_ps(scales, _mm256_set1_ps(-4.f));
auto bits1 = _mm256_loadu_si256((const __m256i *)iq4[4*ib4+k].qs+0);
auto bits2 = _mm256_loadu_si256((const __m256i *)iq4[4*ib4+k].qs+1);
auto q1 = _mm256_and_si256(bits1, m4);
auto q2 = _mm256_and_si256(bits2, m4);
auto q3 = _mm256_and_si256(_mm256_srli_epi16(bits1, 4), m4);
auto q4 = _mm256_and_si256(_mm256_srli_epi16(bits2, 4), m4);
for (int iy = 0; iy < nrc_y; ++iy) {
auto y = _mm256_loadu_si256((const __m256i*)q8.y[iy][ib4].qs+k);
auto sumi1 = _mm256_add_epi16(_mm256_maddubs_epi16(q1, _mm256_shuffle_epi32(y, 0x00)),
_mm256_maddubs_epi16(q2, _mm256_shuffle_epi32(y, 0x55)));
auto sumi2 = _mm256_add_epi16(_mm256_maddubs_epi16(q3, _mm256_shuffle_epi32(y, 0xaa)),
_mm256_maddubs_epi16(q4, _mm256_shuffle_epi32(y, 0xff)));
auto sumi = _mm256_madd_epi16(m1, _mm256_add_epi16(sumi1, sumi2));
auto d4d8 = _mm256_mul_ps(scales, _mm256_set1_ps(d8[8*iy+k]));
acc[iy] = _mm256_fmadd_ps(d4d8, _mm256_cvtepi32_ps(sumi), acc[iy]);
acc[iy] = _mm256_fmadd_ps(scales_m, _mm256_set1_ps(d8[8*iy+4+k]), acc[iy]);
}
}
}
for (int iy = 0; iy < nrc_y; ++iy) {
auto sum = _mm_add_ps(_mm256_castps256_ps128(acc[iy]), _mm256_extractf128_ps(acc[iy], 1));
info.store(ix, iy, sum);
acc[iy] = _mm256_setzero_ps();
}
}
mul_mat_q4_0_r4_q8_1_avx2<nrc_y>(n, vx, bx, info, nrc_x);
}
#endif