summaryrefslogtreecommitdiff
diff options
context:
space:
mode:
-rw-r--r--CMakeLists.txt13
-rw-r--r--Makefile4
-rw-r--r--ggml-common.h12
-rw-r--r--ggml-quants.c54
-rw-r--r--ggml.c49
-rw-r--r--iqk_mul_mat.cpp2468
-rw-r--r--sgemm.cpp17
7 files changed, 2586 insertions, 31 deletions
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 9cfe08d7..5b7ff8e6 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -154,11 +154,12 @@ include(${CMAKE_CURRENT_SOURCE_DIR}/scripts/build-info.cmake)
# Compile flags
#
-if (LLAMA_SYCL)
- set(CMAKE_CXX_STANDARD 17)
-else()
- set(CMAKE_CXX_STANDARD 11)
-endif()
+set(CMAKE_CXX_STANDARD 17)
+#if (LLAMA_SYCL)
+# set(CMAKE_CXX_STANDARD 17)
+#else()
+# set(CMAKE_CXX_STANDARD 11)
+#endif()
set(CMAKE_CXX_STANDARD_REQUIRED true)
set(CMAKE_C_STANDARD 11)
@@ -402,7 +403,7 @@ if (LLAMA_LLAMAFILE)
add_compile_definitions(GGML_USE_LLAMAFILE)
set(GGML_HEADERS_LLAMAFILE sgemm.h)
- set(GGML_SOURCES_LLAMAFILE sgemm.cpp)
+ set(GGML_SOURCES_LLAMAFILE sgemm.cpp iqk_mul_mat.cpp)
endif()
if (LLAMA_CUBLAS)
diff --git a/Makefile b/Makefile
index 4ea59c0b..02f6362f 100644
--- a/Makefile
+++ b/Makefile
@@ -170,8 +170,8 @@ endif
# keep standard at C11 and C++11
MK_CPPFLAGS = -I. -Icommon
-MK_CFLAGS = -std=c11 -fPIC
-MK_CXXFLAGS = -std=c++11 -fPIC
+MK_CFLAGS = -std=c11 -fPIC -v
+MK_CXXFLAGS = -std=c++11 -fPIC -v
MK_NVCCFLAGS = -std=c++11
# -Ofast tends to produce faster code, but may not be available for some compilers.
diff --git a/ggml-common.h b/ggml-common.h
index e8efceb7..d1ae722a 100644
--- a/ggml-common.h
+++ b/ggml-common.h
@@ -199,6 +199,18 @@ typedef struct {
} block_q8_1;
static_assert(sizeof(block_q8_1) == 2*sizeof(ggml_half) + QK8_1, "wrong q8_1 block size/padding");
+typedef struct {
+ ggml_half d[8];
+ int8_t qs[4*QK8_1];
+} block_q8_1_x4;
+static_assert(sizeof(block_q8_1_x4) == 4*sizeof(block_q8_1), "wrong q8_1_x4 block size/padding");
+typedef struct {
+ ggml_half d[4];
+ int8_t qs[4*QK8_0];
+} block_q8_0_x4;
+static_assert(sizeof(block_q8_0_x4) == 4*sizeof(block_q8_0), "wrong q8_0_x4 block size/padding");
+
+
//
// Super-block quantization structures
//
diff --git a/ggml-quants.c b/ggml-quants.c
index 0eb52e48..e540fe4d 100644
--- a/ggml-quants.c
+++ b/ggml-quants.c
@@ -871,7 +871,10 @@ void quantize_row_q8_0(const float * restrict x, void * restrict vy, int64_t k)
block_q8_0 * restrict y = vy;
#if defined(__ARM_NEON)
+ block_q8_0_x4 * y4 = (block_q8_0_x4 *)vy;
+ int nb4 = 4*(nb/4);
for (int i = 0; i < nb; i++) {
+ int i4 = i/4, ir = i%4;
float32x4_t srcv [8];
float32x4_t asrcv[8];
float32x4_t amaxv[8];
@@ -888,16 +891,27 @@ void quantize_row_q8_0(const float * restrict x, void * restrict vy, int64_t k)
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
- y[i].d = GGML_FP32_TO_FP16(d);
+ if (i < nb4) {
+ y4[i4].d[ir] = GGML_FP32_TO_FP16(d);
+ } else {
+ y[i].d = GGML_FP32_TO_FP16(d);
+ }
for (int j = 0; j < 8; j++) {
const float32x4_t v = vmulq_n_f32(srcv[j], id);
const int32x4_t vi = vcvtnq_s32_f32(v);
- y[i].qs[4*j + 0] = vgetq_lane_s32(vi, 0);
- y[i].qs[4*j + 1] = vgetq_lane_s32(vi, 1);
- y[i].qs[4*j + 2] = vgetq_lane_s32(vi, 2);
- y[i].qs[4*j + 3] = vgetq_lane_s32(vi, 3);
+ if (i < nb4) {
+ y4[i4].qs[32*ir + 4*j + 0] = vgetq_lane_s32(vi, 0);
+ y4[i4].qs[32*ir + 4*j + 1] = vgetq_lane_s32(vi, 1);
+ y4[i4].qs[32*ir + 4*j + 2] = vgetq_lane_s32(vi, 2);
+ y4[i4].qs[32*ir + 4*j + 3] = vgetq_lane_s32(vi, 3);
+ } else {
+ y[i].qs[4*j + 0] = vgetq_lane_s32(vi, 0);
+ y[i].qs[4*j + 1] = vgetq_lane_s32(vi, 1);
+ y[i].qs[4*j + 2] = vgetq_lane_s32(vi, 2);
+ y[i].qs[4*j + 3] = vgetq_lane_s32(vi, 3);
+ }
}
}
#elif defined(__wasm_simd128__)
@@ -1191,7 +1205,10 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k)
block_q8_1 * restrict y = vy;
#if defined(__ARM_NEON)
+ block_q8_1_x4 * restrict y4 = vy;
+ int nb4 = 4*(nb/4);
for (int i = 0; i < nb; i++) {
+ int i4 = i/4, ir = i%4;
float32x4_t srcv [8];
float32x4_t asrcv[8];
float32x4_t amaxv[8];
@@ -1208,7 +1225,11 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k)
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
- y[i].d = GGML_FP32_TO_FP16(d);
+ if (i < nb4) {
+ y4[i4].d[ir] = GGML_FP32_TO_FP16(d);
+ } else {
+ y[i].d = GGML_FP32_TO_FP16(d);
+ }
int32x4_t accv = vdupq_n_s32(0);
@@ -1216,15 +1237,26 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k)
const float32x4_t v = vmulq_n_f32(srcv[j], id);
const int32x4_t vi = vcvtnq_s32_f32(v);
- y[i].qs[4*j + 0] = vgetq_lane_s32(vi, 0);
- y[i].qs[4*j + 1] = vgetq_lane_s32(vi, 1);
- y[i].qs[4*j + 2] = vgetq_lane_s32(vi, 2);
- y[i].qs[4*j + 3] = vgetq_lane_s32(vi, 3);
+ if (i < nb4) {
+ y4[i4].qs[QK8_1*ir + 4*j + 0] = vgetq_lane_s32(vi, 0);
+ y4[i4].qs[QK8_1*ir + 4*j + 1] = vgetq_lane_s32(vi, 1);
+ y4[i4].qs[QK8_1*ir + 4*j + 2] = vgetq_lane_s32(vi, 2);
+ y4[i4].qs[QK8_1*ir + 4*j + 3] = vgetq_lane_s32(vi, 3);
+ } else {
+ y[i].qs[4*j + 0] = vgetq_lane_s32(vi, 0);
+ y[i].qs[4*j + 1] = vgetq_lane_s32(vi, 1);
+ y[i].qs[4*j + 2] = vgetq_lane_s32(vi, 2);
+ y[i].qs[4*j + 3] = vgetq_lane_s32(vi, 3);
+ }
accv = vaddq_s32(accv, vi);
}
- y[i].s = GGML_FP32_TO_FP16(d * vaddvq_s32(accv));
+ if (i < nb4) {
+ y4[i4].d[ir+4] = GGML_FP32_TO_FP16(d * vaddvq_s32(accv));
+ } else {
+ y[i].s = GGML_FP32_TO_FP16(d * vaddvq_s32(accv));
+ }
}
#elif defined(__wasm_simd128__)
for (int i = 0; i < nb; i++) {
diff --git a/ggml.c b/ggml.c
index 778ca3fd..55daa330 100644
--- a/ggml.c
+++ b/ggml.c
@@ -12334,11 +12334,7 @@ UseGgmlGemm1:;
#endif
if (params->type == GGML_TASK_TYPE_INIT) {
- if (ith != 0) {
- return;
- }
- // Every thread starts at ith, so the first unprocessed chunk is nth. This save a bit of coordination right at the start.
- atomic_store(&state->shared->current_chunk, nth);
+
if (src1->type != vec_dot_type) {
char * wdata = params->wdata;
const size_t row_size = ggml_row_size(vec_dot_type, ne10);
@@ -12346,16 +12342,45 @@ UseGgmlGemm1:;
assert(params->wsize >= ne11*ne12*ne13*row_size);
GGML_ASSERT(src1->type == GGML_TYPE_F32);
- for (int64_t i13 = 0; i13 < ne13; ++i13) {
- for (int64_t i12 = 0; i12 < ne12; ++i12) {
- for (int64_t i11 = 0; i11 < ne11; ++i11) {
- from_float_to_vec_dot((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11), (void *) wdata, ne10);
- wdata += row_size;
- }
- }
+ int64_t work_size = ne13*ne12*ne11;
+ int64_t work_per_thread = (work_size + nth - 1)/nth;
+ int64_t work_start = work_per_thread * ith;
+ if (work_start >= work_size) {
+ return;
+ }
+ int64_t work_end = MIN(work_size, work_start + work_per_thread);
+ for (int64_t i_work = work_start; i_work < work_end; ++i_work) {
+ int64_t i13 = i_work / (ne11*ne12);
+ int64_t i12 = (i_work - i13*ne11*ne12)/ne11;
+ int64_t i11 = i_work - i13*ne11*ne12 - i12*ne11;
+ from_float_to_vec_dot((const float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11),
+ (void *)(wdata + i_work*row_size), ne10);
}
}
+ if (ith == 0) {
+ atomic_store(&state->shared->current_chunk, nth);
+ }
+
+ //// Every thread starts at ith, so the first unprocessed chunk is nth. This save a bit of coordination right at the start.
+ //atomic_store(&state->shared->current_chunk, nth);
+ //if (src1->type != vec_dot_type) {
+ // char * wdata = params->wdata;
+ // const size_t row_size = ggml_row_size(vec_dot_type, ne10);
+
+ // assert(params->wsize >= ne11*ne12*ne13*row_size);
+ // GGML_ASSERT(src1->type == GGML_TYPE_F32);
+
+ // for (int64_t i13 = 0; i13 < ne13; ++i13) {
+ // for (int64_t i12 = 0; i12 < ne12; ++i12) {
+ // for (int64_t i11 = 0; i11 < ne11; ++i11) {
+ // from_float_to_vec_dot((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11), (void *) wdata, ne10);
+ // wdata += row_size;
+ // }
+ // }
+ // }
+ //}
+
return;
}
diff --git a/iqk_mul_mat.cpp b/iqk_mul_mat.cpp
new file mode 100644
index 00000000..7c1afa39
--- /dev/null
+++ b/iqk_mul_mat.cpp
@@ -0,0 +1,2468 @@
+// -*- mode:c++;indent-tabs-mode:nil;c-basic-offset:4;coding:utf-8 -*-
+// vi: set et ft=cpp fenc=utf-8 :vi
+//
+// Copyright 2024 Iwan Kawrakow
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <type_traits>
+#if defined __x86_64__ || defined __aarch64__
+
+#include "ggml-impl.h"
+#include "ggml-quants.h"
+#include "sgemm.h"
+
+// clang-format off
+
+// This matrix - vector and matrix - matrix multiplication implementation
+// for k-quants and IQ4_XS makes prompt processing 150-200% faster
+// compared to mainline llama.cpp (and llamafile).
+// It is AVX2 only for now.
+//
+// Main idea is that unpacking the quants and the block scales to
+// be ready for dot products with the corresponding Q8_K quants
+// takes time. Hence, if we are performing a QX x Q8_K matrix matrix
+// multiplication (as needed for prompt processing), we can get
+// a significant speedup by reusing the unpacked QX quants and scales
+// for multiplication with several Q8_K columns.
+
+#include <utility>
+#include <array>
+
+#endif
+
+namespace {
+
+typedef struct {
+ int32_t i1;
+ int32_t i2;
+} mmid_row_mapping;
+
+struct DataInfo {
+ float * s;
+ const char * cy;
+ size_t bs;
+ size_t by;
+ int cur_y = 0;
+ int ne11;
+ const mmid_row_mapping * row_mapping = nullptr;
+ size_t bs2 = 0;
+
+ inline const char * src1_row(int iy) const {
+ if (!row_mapping) return cy + (cur_y + iy)*by;
+ int i11 = row_mapping[cur_y + iy].i1 % ne11;
+ int i12 = row_mapping[cur_y + iy].i2;
+ return cy + (i11 + i12*ne11)*by;
+ }
+
+ inline void store(int ix, int iy, float result) const {
+ *(dst_row(iy) + ix) = result;
+ //dst_row(iy)[ix] = result;
+ }
+ inline float * dst_row(int iy) const {
+ if (!row_mapping) return s + (cur_y + iy)*bs;
+ int i12 = row_mapping[cur_y + iy].i2;
+ int i1 = row_mapping[cur_y + iy].i1;
+ int i2 = i12;
+ return s + i1*bs + i2*bs2;
+ }
+};
+
+typedef void (*mul_mat_t)(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x);
+
+struct MulMat {
+ std::array<mul_mat_t, 8> funcs = {};
+ //std::array<mul_mat_t, 4> funcs = {};
+ inline void mul_mat_NxM(int n, const void * vx, size_t bx, DataInfo& info, int nrc_x, int nrc_y) {
+#ifdef __aarch64__
+ constexpr int k_x_step = 64; //8192; // Tiling does not seem to help on my M2 Max (but difference to tiling is small)
+#else
+ constexpr int k_x_step = 64; // This works best on my Ryzen-7950X (but differences to other tile size are small)
+#endif
+ int n_step = (nrc_y - info.cur_y)/funcs.size();
+ if (n_step > 0) {
+ for (int ix = 0; ix < nrc_x; ix += k_x_step) {
+ auto this_info = info;
+ this_info.s += ix;
+ int this_nrc_x = ix + k_x_step <= nrc_x ? k_x_step : nrc_x - ix;
+ for (int iy = 0; iy < n_step; ++iy) {
+ funcs.back()(n, (const void *)((const char *)vx + ix*bx), bx, this_info, this_nrc_x);
+ this_info.cur_y += funcs.size();
+ }
+ }
+ info.cur_y += funcs.size() * n_step;
+ }
+ int n_left = nrc_y - info.cur_y;
+ if (n_left > 0) {
+ funcs[n_left-1](n, vx, bx, info, nrc_x);
+ }
+ }
+ static bool set_mul_mat(int typeA, int ne00, MulMat& mm, int& row_size_q8, int Ny);
+private:
+ template <typename Dequantizer> static void set_functions(MulMat& m);
+};
+
+inline void make_q4_scales(const uint8_t * scales8, uint32_t * aux32) {
+ const uint16_t * scales = (const uint16_t *)scales8;
+ const uint32_t a0 = scales[0] | (scales[1] << 16);
+ const uint32_t a1 = scales[2] | (scales[3] << 16);
+ const uint32_t a2 = scales[4] | (scales[5] << 16);
+ aux32[3] = ((a2 >> 4) & 0x0f0f0f0f) | ((a1 >> 2) & 0x30303030);
+ aux32[1] = ((a2 >> 0) & 0x0f0f0f0f) | ((a0 >> 2) & 0x30303030);
+ aux32[2] = a1 & 0x3f3f3f3f;
+ aux32[0] = a0 & 0x3f3f3f3f;
+}
+
+}
+
+bool iqk_mul_mat(long Nx, long Ny, long ne00, int typeA, const void * A, const void * B,
+ float * C, long stride_C, int ith, int nth) {
+
+ MulMat mm;
+ int row_size_q8;
+ if (!MulMat::set_mul_mat(typeA, ne00, mm, row_size_q8, Ny)) {
+ return false;
+ }
+
+ auto row_size_qx = ggml_row_size((ggml_type)typeA, ne00);
+
+ auto nrc_x = (Nx + nth - 1)/nth;
+ auto first_x = ith*nrc_x;
+ if (first_x + nrc_x > Nx) nrc_x = Nx - first_x;
+
+ DataInfo info{C + first_x, (const char *)B, (size_t)stride_C, (size_t)row_size_q8, 0, 1, nullptr, 0};
+
+ mm.mul_mat_NxM(ne00, (const char *)A + row_size_qx*first_x, row_size_qx, info, nrc_x, Ny);
+
+ return true;
+}
+
+bool iqk_mul_mat_moe(long Nx, long Ny, long ne00, int ne11, int typeA, const void * A, const void * B,
+ float * C, long nb1, long nb2, const void * vrow_mapping, int ith, int nth) {
+ const mmid_row_mapping * row_mapping = (const mmid_row_mapping *)vrow_mapping;
+ assert(row_mapping != nullptr);
+
+ MulMat mm;
+ int row_size_q8;
+ if (!MulMat::set_mul_mat(typeA, ne00, mm, row_size_q8, Ny)) {
+ return false;
+ }
+ int row_size_qx = ggml_row_size((ggml_type)typeA, ne00);
+ int nrc_x = (Nx + nth - 1)/nth;
+ int first_x = ith*nrc_x;
+ if (first_x + nrc_x > Nx) nrc_x = Nx - first_x;
+ DataInfo info{C + first_x, (const char *)B, nb1/sizeof(float), (size_t)row_size_q8, 0, ne11, row_mapping, nb2/sizeof(float)};
+ mm.mul_mat_NxM(ne00, (const char *)A + row_size_qx*first_x, row_size_qx, info, nrc_x, Ny);
+ return true;
+}
+
+#if defined __x86_64__
+
+#if defined HAVE_FANCY_SIMD
+ #undef HAVE_FANCY_SIMD
+#endif
+#if defined(__AVX512F__) && defined(__AVX512VNNI__) && defined(__AVX512VL__) && defined(__AVX512BW__) && defined(__AVX512DQ__)
+ #define HAVE_FANCY_SIMD
+#endif
+
+namespace {
+
+inline float hsum_float_4(__m128 x) {
+ x = _mm_add_ps(x, _mm_movehl_ps(x, x));
+ x = _mm_add_ss(x, _mm_movehdup_ps(x));
+ return _mm_cvtss_f32(x);
+}
+inline float hsum_float_8(__m256 x) {
+ return hsum_float_4(_mm_add_ps(_mm256_castps256_ps128(x), _mm256_extractf128_ps(x, 1)));
+}
+
+#define MM256_SET_M128I(a, b) _mm256_insertf128_si256(_mm256_castsi128_si256(b), (a), 1)
+
+
+template <int nrc, typename block_q8 = block_q8_K> struct Q8 {
+
+ constexpr static int nrc_y = nrc;
+
+ Q8(const DataInfo& info) {
+ for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8 *)info.src1_row(iy);
+ }
+
+#ifdef HAVE_FANCY_SIMD
+ inline __m512i load_quants(int iy, int i, int j) const { return _mm512_loadu_si512((const __m512i*)y[iy][i].qs + j); }
+#else
+ inline __m256i load_quants(int iy, int i, int j) const { return _mm256_loadu_si256((const __m256i*)y[iy][i].qs + j); }
+#endif
+ inline __m256i load_bsums(int iy, int i) const { return _mm256_loadu_si256((const __m256i*)y[iy][i].bsums); }
+ inline float scale(int iy, int i) const { return y[iy][i].d; }
+
+ const block_q8 * y[nrc_y];
+};
+
+// Handles q4_K and q5_K scales/mins
+struct Scales8K {
+ template <typename Q8>
+ inline __m256i process_mins_and_scales(const uint8_t * data, float c, int i, const Q8& q8, __m256 * accd) {
+ make_q4_scales(data, utmp);
+ const __m256i mins_and_scales = _mm256_cvtepu8_epi16(_mm_set_epi32(utmp[3], utmp[2], utmp[1], utmp[0]));
+ const __m128i mins128 = _mm256_extracti128_si256(mins_and_scales, 1);
+ accum_mins(mins128, q8, i, c, accd);
+ const __m128i sc128 = _mm256_extracti128_si256(mins_and_scales, 0);
+ return MM256_SET_M128I(sc128, sc128);
+ }
+#ifdef HAVE_FANCY_SIMD
+ template <typename Q8>
+ inline __m512i process_mins_and_scales_64(const uint8_t * data, float c, int i, const Q8& q8, __m256 * accd) {
+ auto scales = process_mins_and_scales(data, c, i, q8, accd);
+ return _mm512_inserti32x8(_mm512_castsi256_si512(scales), scales, 1);
+ }
+#endif
+ template <typename Q8>
+ inline void accum_mins(const __m128i& mins128, const Q8& q8, int i, float c, __m256 * accd) const {
+ const __m256i mins = MM256_SET_M128I(_mm_shuffle_epi8(mins128, shuffles[1]), _mm_shuffle_epi8(mins128, shuffles[0]));
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ const __m256i q8s = q8.load_bsums(iy, i);
+ const __m256i prod = _mm256_madd_epi16(mins, q8s);
+ accd[iy] = _mm256_fmadd_ps(_mm256_set1_ps(c*q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accd[iy]);
+ }
+ }
+#ifdef HAVE_FANCY_SIMD
+ const __m512i shuffles512[2] = {
+ _mm512_set_epi64(0x0706070607060706, 0x0302030203020302, 0x0706070607060706, 0x0302030203020302,
+ 0x0504050405040504, 0x0100010001000100, 0x0504050405040504, 0x0100010001000100),
+ _mm512_set_epi64(0x0f0e0f0e0f0e0f0e, 0x0b0a0b0a0b0a0b0a, 0x0f0e0f0e0f0e0f0e, 0x0b0a0b0a0b0a0b0a,
+ 0x0d0c0d0c0d0c0d0c, 0x0908090809080908, 0x0d0c0d0c0d0c0d0c, 0x0908090809080908)
+ };
+#endif
+ const __m128i shuffles[2] = {_mm_set_epi32(0x07060706, 0x05040504, 0x03020302, 0x01000100),
+ _mm_set_epi32(0x0f0e0f0e, 0x0d0c0d0c, 0x0b0a0b0a, 0x09080908)};
+
+ uint32_t utmp[4];
+};
+
+template <typename Q8>
+inline void process_mins_16(const __m256i& all_scales, const Q8& q8, int i, float d, __m256 * accm) {
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ const __m256i prod = _mm256_madd_epi16(all_scales, q8.load_bsums(iy, i));
+ accm[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d * q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accm[iy]);
+ }
+}
+inline void prepare_scales_16(const __m256i& all_scales, __m256i * scales) {
+ const __m128i l_scales = _mm256_extracti128_si256(all_scales, 0);
+ const __m128i h_scales = _mm256_extracti128_si256(all_scales, 1);
+ scales[0] = MM256_SET_M128I(l_scales, l_scales);
+ scales[1] = MM256_SET_M128I(h_scales, h_scales);
+}
+
+struct ScaleQ3 {
+ inline __m128i make_scales(const uint16_t * s8) const {
+ const uint16_t * scales16 = (const uint16_t *)s8;
+ uint32_t aux0 = scales16[0] | (scales16[1] << 16);
+ uint32_t aux1 = scales16[2] | (scales16[3] << 16);
+ uint32_t aux2 = scales16[4] | (scales16[5] << 16);
+ __m128i scales128 = _mm_set_epi32(
+ ((aux1 >> 4) & 0x0f0f0f0f) | ((aux2 >> 2) & 0x30303030),
+ ((aux0 >> 4) & 0x0f0f0f0f) | ((aux2 >> 0) & 0x30303030),
+ (aux1 & 0x0f0f0f0f) | ((aux2 << 2) & 0x30303030),
+ (aux0 & 0x0f0f0f0f) | ((aux2 << 4) & 0x30303030));
+ return _mm_add_epi8(scales128, m32);
+ }
+ const __m128i m32 = _mm_set1_epi8(-32);
+};
+
+struct ScaleIQ4XS {
+ inline __m128i make_scales(const uint32_t scales_l, const uint16_t scales_h) {
+ uint32_t tmp32 = scales_h | (scales_h << 14);
+ const __m128i sh = _mm_slli_epi16(_mm_and_si128(_mm_srlv_epi32(_mm_set1_epi32(tmp32), hshift), hmask), 4);
+ const __m128i sl = _mm_and_si128(_mm_srlv_epi32(_mm_set1_epi32(scales_l), lshift), lmask);
+ return _mm_add_epi16(_mm_or_si128(sh, _mm_cvtepi8_epi16(_mm_shuffle_epi8(sl, lshuffle))), m32);
+ }
+ const __m128i hshift = _mm_set_epi32(12, 8, 4, 0);
+ const __m128i lshift = _mm_set_epi32(4, 0, 4, 0);
+ const __m128i hmask = _mm_set1_epi16(0x03);
+ const __m128i lmask = _mm_set1_epi8(0xf);
+ const __m128i lshuffle = _mm_set_epi32(0x07030602, 0x05010400, 0x07030602, 0x05010400);
+ const __m128i m32 = _mm_set1_epi16(-32);
+};
+
+template <typename Block>
+struct BaseDequantizer {
+ BaseDequantizer(const void * vx, size_t bx) : vx(vx), bx(bx) {}
+ inline void new_row(int ix) {
+ x = (const Block *)((const char *)vx + bx*ix);
+ }
+
+ const void * vx;
+ size_t bx;
+ const Block * x;
+
+ float d;
+};
+
+#ifdef HAVE_FANCY_SIMD
+//====================================== Zen4 ==================================================
+
+struct BlockPermuter {
+ const __m512i permute1 = _mm512_set_epi64(11, 10, 9, 8, 3, 2, 1, 0);
+ const __m512i permute2 = _mm512_set_epi64(15, 14, 13, 12, 7, 6, 5, 4);
+};
+
+struct Q4Bits {
+ inline void prepare(const uint8_t * q4) {
+ auto q4bits = _mm512_loadu_si512((const __m512i*)q4 + 0);
+ auto tmp1 = _mm512_and_si512(q4bits, ml);
+ auto tmp2 = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml);
+ values[0] = _mm512_permutex2var_epi64(tmp1, perm.permute1, tmp2);
+ values[1] = _mm512_permutex2var_epi64(tmp1, perm.permute2, tmp2);
+ q4bits = _mm512_loadu_si512((const __m512i*)q4 + 1);
+ tmp1 = _mm512_and_si512(q4bits, ml);
+ tmp2 = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml);
+ values[2] = _mm512_permutex2var_epi64(tmp1, perm.permute1, tmp2);
+ values[3] = _mm512_permutex2var_epi64(tmp1, perm.permute2, tmp2);
+ }
+ inline void prepare64(const uint8_t * q4) {
+ auto q4bits = _mm512_loadu_si512((const __m512i*)q4 + 0);
+ values[0] = _mm512_and_si512(q4bits, ml);
+ values[1] = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml);
+ q4bits = _mm512_loadu_si512((const __m512i*)q4 + 1);
+ values[2] = _mm512_and_si512(q4bits, ml);
+ values[3] = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml);
+ }
+ __m512i values[4];
+ const __m512i ml = _mm512_set1_epi8(0xf);
+ BlockPermuter perm;
+};
+
+struct Q2Bits {
+ inline void prepare(const uint8_t * q2) {
+
+ auto q2bits = _mm512_loadu_si512((const __m512i*)q2);
+ auto tmp = _mm512_srli_epi16(q2bits, 2);
+
+ values[0] = _mm512_permutex2var_epi64(q2bits, perm.permute1, tmp);
+ values[2] = _mm512_permutex2var_epi64(q2bits, perm.permute2, tmp);
+ values[1] = _mm512_and_si512(_mm512_srli_epi16(values[0], 4), ml);
+ values[3] = _mm512_and_si512(_mm512_srli_epi16(values[2], 4), ml);
+ values[0] = _mm512_and_si512(values[0], ml);
+ values[2] = _mm512_and_si512(values[2], ml);
+ }
+ __m512i values[4];
+ const __m512i ml = _mm512_set1_epi8(0x03);
+ BlockPermuter perm;
+};
+
+struct DequantizerQ4K final : public BaseDequantizer<block_q4_K> {
+ DequantizerQ4K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ bits.prepare(x[i].qs);
+ auto all_scales = s8k.process_mins_and_scales_64(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd);
+ scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]);
+ scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]);
+ }
+
+ Q4Bits bits;
+ Scales8K s8k;
+};
+
+struct DequantizerIQ4XS final : public BaseDequantizer<block_iq4_xs> {
+ DequantizerIQ4XS(const void * vx, size_t bx) : BaseDequantizer(vx, bx), values(load_values()) {}
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ prepare(x[i].qs);
+ auto scales128 = siq4.make_scales(*(const uint32_t *)x[i].scales_l, x[i].scales_h);
+ s8k.accum_mins(scales128, q8, i, -128.f*d, accd);
+ auto scales256 = MM256_SET_M128I(scales128, scales128);
+ auto all_scales = _mm512_inserti32x8(_mm512_castsi256_si512(scales256), scales256, 1);
+ scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]);
+ scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]);
+ }
+ static __m512i load_values() {
+ static const uint8_t kvalues_iq4nl[16] = {1, 24, 45, 63, 79, 93, 106, 118, 129, 141, 153, 166, 181, 197, 217, 241};
+ auto val128 = _mm_loadu_si128((const __m128i *)kvalues_iq4nl);
+ auto val256 = MM256_SET_M128I(val128, val128);
+ return _mm512_inserti32x8(_mm512_castsi256_si512(val256), val256, 1);
+ }
+ inline void prepare(const uint8_t * q4) {
+ bits.prepare64(q4);
+ // We now have in bits.valuse[0]: 0...15, 32...47, 64...79, 96...111
+ // bits.valuse[1]: 16..31, 48...63, 80...95, 112..127
+ // etc.
+ auto tmp = _mm512_permutex2var_epi64(bits.values[0], permute1, bits.values[1]);
+ bits.values[1] = _mm512_shuffle_epi8(values, _mm512_permutex2var_epi64(bits.values[0], permute2, bits.values[1]));
+ bits.values[0] = _mm512_shuffle_epi8(values, tmp);
+ tmp = _mm512_permutex2var_epi64(bits.values[2], permute1, bits.values[3]);
+ bits.values[3] = _mm512_shuffle_epi8(values, _mm512_permutex2var_epi64(bits.values[2], permute2, bits.values[3]));
+ bits.values[2] = _mm512_shuffle_epi8(values, tmp);
+ }
+
+ Q4Bits bits;
+ Scales8K s8k;
+ ScaleIQ4XS siq4;
+ const __m512i values;
+ const __m512i permute1 = _mm512_set_epi64(11, 10, 3, 2, 9, 8, 1, 0);
+ const __m512i permute2 = _mm512_set_epi64(15, 14, 7, 6, 13, 12, 5, 4);
+};
+
+struct HighBit5 {
+ inline void apply(const uint8_t * h, Q4Bits& bits) {
+ auto hbits256 = _mm256_loadu_si256((const __m256i *)h);
+ auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(hbits256), _mm256_srli_epi16(hbits256, 1), 1);
+ bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_and_si512(_mm512_slli_epi16(hbits, 4), mh));
+ bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh));
+ bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_and_si512(hbits, mh));
+ bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh));
+ }
+ const __m512i mh = _mm512_set1_epi8(0x10);
+};
+
+struct HighBit3 {
+ inline void apply(const uint8_t * h, Q2Bits& bits) {
+ auto hbits256 = _mm256_loadu_si256((const __m256i *)h);
+ auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(hbits256), _mm256_srli_epi16(hbits256, 1), 1);
+ bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh));
+ bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_and_si512(hbits, mh));
+ bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh));
+ bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_and_si512(_mm512_srli_epi16(hbits, 4), mh));
+ }
+ const __m512i mh = _mm512_set1_epi8(0x04);
+};
+
+struct DequantizerQ5K final : public BaseDequantizer<block_q5_K> {
+ DequantizerQ5K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ bits.prepare(x[i].qs);
+ hbits.apply(x[i].qh, bits);
+ auto all_scales = s8k.process_mins_and_scales_64(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd);
+ scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]);
+ scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]);
+ }
+
+ Q4Bits bits;
+ HighBit5 hbits;
+ Scales8K s8k;
+};
+
+struct Scale16 {
+ inline void make_scales(const __m128i& scales8, __m512i * scales) const {
+ auto all_scales8 = MM256_SET_M128I(scales8, scales8);
+ auto scales1 = _mm256_shuffle_epi8(all_scales8, shuffle1);
+ auto scales2 = _mm256_shuffle_epi8(all_scales8, shuffle2);
+ scales[0] = _mm512_cvtepi8_epi16(scales1);
+ scales[1] = _mm512_cvtepi8_epi16(scales2);
+ }
+ template <typename Q8>
+ inline void process_mins_and_scales(int i, float c, const __m128i& mins8, const __m128i& scales8,
+ const Q8& q8, __m256 * accm, __m512i * scales) const {
+ process_mins_16(_mm256_cvtepi8_epi16(mins8), q8, i, c, accm);
+ make_scales(scales8, scales);
+ }
+ const __m256i shuffle1 = _mm256_set_epi32(0x07070707, 0x03030303, 0x06060606, 0x02020202,
+ 0x05050505, 0x01010101, 0x04040404, 0x00000000);
+ const __m256i shuffle2 = _mm256_set_epi32(0x0f0f0f0f, 0x0b0b0b0b, 0x0e0e0e0e, 0x0a0a0a0a,
+ 0x0d0d0d0d, 0x09090909, 0x0c0c0c0c, 0x08080808);
+};
+
+struct DequantizerQ2K final : public BaseDequantizer<block_q2_K> {
+ DequantizerQ2K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ bits.prepare(x[i].qs);
+ const __m128i mins_and_scales = _mm_loadu_si128((const __m128i*)x[i].scales);
+ const __m128i scales8 = _mm_and_si128(mins_and_scales, m4);
+ const __m128i mins8 = _mm_and_si128(_mm_srli_epi16(mins_and_scales, 4), m4);
+ sc16.process_mins_and_scales(i, -GGML_FP16_TO_FP32(x[i].dmin), mins8, scales8, q8, accm, scales);
+ }
+
+ Q2Bits bits;
+ Scale16 sc16;
+ const __m128i m4 = _mm_set1_epi8(0xf);
+
+};
+
+struct DequantizerQ3K final : public BaseDequantizer<block_q3_K> {
+ DequantizerQ3K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ bits.prepare(x[i].qs);
+ hbits.apply(x[i].hmask, bits);
+ auto scales128 = sc3.make_scales((const uint16_t *)x[i].scales);
+ sc16.process_mins_and_scales(i, -4.f*d, scales128, scales128, q8, accm, scales);
+ }
+
+ Q2Bits bits;
+ HighBit3 hbits;
+ ScaleQ3 sc3;
+ Scale16 sc16;
+ const __m128i m4 = _mm_set1_epi8(0xf);
+ const __m128i m32 = _mm_set1_epi8(-32);
+};
+
+struct DequantizerQ6K final : public BaseDequantizer<block_q6_K> {
+ DequantizerQ6K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ bits.prepare64(x[i].ql);
+ add_high_bits(x[i].qh, bits);
+ auto scales128 = _mm_loadu_si128((const __m128i *)x[i].scales);
+ sc16.process_mins_and_scales(i, -32.f*d, scales128, scales128, q8, accm, scales);
+ }
+
+ inline void add_high_bits(const uint8_t * qh, Q4Bits& bits) const {
+ auto hbits = _mm512_loadu_si512((const __m512i *)qh);
+ auto tmp1 = _mm512_and_si512(_mm512_slli_epi16(hbits, 4), mh);
+ auto tmp2 = _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh);
+ bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_permutex2var_epi64(tmp1, bits.perm.permute1, tmp2));
+ bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_permutex2var_epi64(tmp1, bits.perm.permute2, tmp2));
+ tmp1 = _mm512_and_si512(hbits, mh);
+ tmp2 = _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh);
+ bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_permutex2var_epi64(tmp1, bits.perm.permute1, tmp2));
+ bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_permutex2var_epi64(tmp1, bits.perm.permute2, tmp2));
+ }
+
+ Q4Bits bits;
+ HighBit3 hbits;
+ Scale16 sc16;
+
+ const __m512i mh = _mm512_set1_epi8(0x30);
+
+};
+
+template <typename Dequantizer, int nrc_y>
+static void mul_mat_qX_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ assert(n % QK_K == 0);
+ const int nb = n / QK_K;
+
+ Q8<nrc_y> q8(info);
+
+ Dequantizer deq(vx, bx);
+
+ __m256 accm[nrc_y];
+ __m512 accd[nrc_y];
+ __m512i scales[2];
+
+ for (int ix = 0; ix < nrc_x; ++ix) {
+
+ for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm512_setzero_ps();
+ for (int iy = 0; iy < nrc_y; ++iy) accm[iy] = _mm256_setzero_ps();
+
+ deq.new_row(ix);
+
+ for (int i = 0; i < nb; ++i) {
+
+ deq.new_block(i, q8, accm, scales);
+
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ const __m512i p1 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[0], q8.load_quants(iy, i, 0));
+ const __m512i p2 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[1], q8.load_quants(iy, i, 1));
+ const __m512i p3 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[2], q8.load_quants(iy, i, 2));
+ const __m512i p4 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[3], q8.load_quants(iy, i, 3));
+ auto sumi = _mm512_dpwssd_epi32(_mm512_setzero_si512(), scales[0], _mm512_packs_epi32(p1, p2));
+ sumi = _mm512_dpwssd_epi32(sumi, scales[1], _mm512_packs_epi32(p3, p4));
+ accd[iy] = _mm512_fmadd_ps(_mm512_set1_ps(deq.d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi), accd[iy]);
+ }
+
+ }
+
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ auto sum256 = _mm256_add_ps(_mm512_castps512_ps256(accd[iy]), _mm512_extractf32x8_ps(accd[iy], 1));
+ info.store(ix, iy, hsum_float_8(_mm256_add_ps(accm[iy], sum256)));
+ }
+
+ }
+}
+
+#else
+// ===================================== Vanilla AVX2 =====================================
+
+struct Q4Bits {
+ inline void prepare(const uint8_t * q4, int j) {
+ auto q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+0);
+ values[0] = _mm256_and_si256(q4bits, ml);
+ values[1] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml);
+ q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+1);
+ values[2] = _mm256_and_si256(q4bits, ml);
+ values[3] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml);
+ }
+ inline void prepare64(const uint8_t * q4, int j) {
+ auto q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+0);
+ values[0] = _mm256_and_si256(q4bits, ml);
+ values[2] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml);
+ q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+1);
+ values[1] = _mm256_and_si256(q4bits, ml);
+ values[3] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml);
+ }
+ inline void prepare16(const uint8_t * q4, int j) {
+ values[0] = dequant16(q4 + 64*j + 0);
+ values[1] = dequant16(q4 + 64*j + 16);
+ values[2] = dequant16(q4 + 64*j + 32);
+ values[3] = dequant16(q4 + 64*j + 48);
+ }
+ inline __m256i dequant16(const uint8_t * qs) const {
+ const __m128i aux128 = _mm_loadu_si128((const __m128i *)qs);
+ const __m256i aux256 = MM256_SET_M128I(_mm_srli_epi16(aux128, 4), aux128);
+ return _mm256_and_si256(ml, aux256);
+ };
+ __m256i values[4];
+ const __m256i ml = _mm256_set1_epi8(0xf);
+};
+
+struct Q2Bits {
+ inline void prepare(const uint8_t * q2, int j) {
+ auto q2bits = _mm256_loadu_si256((const __m256i *)q2 + j);
+ values[0] = _mm256_and_si256(q2bits, ml);
+ values[1] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 2), ml);
+ values[2] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 4), ml);
+ values[3] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 6), ml);
+ }
+ __m256i values[4];
+ const __m256i ml = _mm256_set1_epi8(0x03);
+};
+
+struct HighBit5 {
+ inline void load(const uint8_t * h) { hbits = _mm256_loadu_si256((const __m256i *)h); }
+ inline void apply(Q4Bits& bits, bool do_shift) {
+ bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 4), mh));
+ bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 3), mh));
+ bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh));
+ bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_slli_epi16(hbits, 1), mh));
+ if (do_shift) {
+ hbits = _mm256_srli_epi16(hbits, 4);
+ }
+ }
+ const __m256i mh = _mm256_set1_epi8(0x10);
+ __m256i hbits;
+};
+
+struct HighBit3 {
+ inline void load(const uint8_t * h) { hbits = _mm256_loadu_si256((const __m256i *)h); }
+ inline void apply(Q2Bits& bits, bool do_shift) {
+ bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh));
+ bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 1), mh));
+ bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(hbits, mh));
+ bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_srli_epi16(hbits, 1), mh));
+ if (do_shift) {
+ hbits = _mm256_srli_epi16(hbits, 4);
+ }
+ }
+ const __m256i mh = _mm256_set1_epi8(0x04);
+ __m256i hbits;
+};
+
+inline __m256i get_scale_shuffle_8(int i) {
+ return _mm256_set1_epi16((2*i) | ((2*i+1) << 8));
+}
+
+inline void set_scales_8(const __m256i& all_scales, int j, __m256i * scales) {
+ scales[0] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+0));
+ scales[1] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+1));
+ scales[2] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+2));
+ scales[3] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+3));
+}
+
+template <typename Q8, typename Bits>
+inline void multiply_add(const Bits& bits, const __m256i * scales, int j, int i, const Q8& q8, __m256i * sumi) {
+ if (j == 0) {
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 0)));
+ const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 1)));
+ const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 2)));
+ const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 3)));
+ sumi[iy] = _mm256_add_epi32(_mm256_add_epi32(p1, p3), _mm256_add_epi32(p2, p4));
+ }
+ } else {
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 4)));
+ const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 5)));
+ const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 6)));
+ const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 7)));
+ sumi[iy] = _mm256_add_epi32(sumi[iy], _mm256_add_epi32(p1, p3));
+ sumi[iy] = _mm256_add_epi32(sumi[iy], _mm256_add_epi32(p2, p4));
+ }
+ }
+}
+
+struct DequantizerQ4K final : public BaseDequantizer<block_q4_K> {
+ DequantizerQ4K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+ template <typename Q8>
+ inline __m256i new_block(int i, const Q8& q8, __m256 * accd) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ return s8k.process_mins_and_scales(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd);
+ }
+ inline void prepare(int i, int j) {
+ bits.prepare(x[i].qs, j);
+ }
+
+ Q4Bits bits;
+ Scales8K s8k;
+};
+
+struct DequantizerIQ4XS final : public BaseDequantizer<block_iq4_xs> {
+ DequantizerIQ4XS(const void * vx, size_t bx) : BaseDequantizer(vx, bx), values(load_values()) {}
+ template <typename Q8>
+ inline __m256i new_block(int i, const Q8& q8, __m256 * accd) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ auto scales128 = siq4.make_scales(*(const uint32_t *)x[i].scales_l, x[i].scales_h);
+ s8k.accum_mins(scales128, q8, i, -128.f*d, accd);
+ return MM256_SET_M128I(scales128, scales128);
+ }
+ inline void prepare(int i, int j) {
+ bits.prepare16(x[i].qs, j);
+ bits.values[0] = _mm256_shuffle_epi8(values, bits.values[0]);
+ bits.values[1] = _mm256_shuffle_epi8(values, bits.values[1]);
+ bits.values[2] = _mm256_shuffle_epi8(values, bits.values[2]);
+ bits.values[3] = _mm256_shuffle_epi8(values, bits.values[3]);
+ }
+
+ static __m256i load_values() {
+ static const uint8_t kvalues_iq4nl[16] = {1, 24, 45, 63, 79, 93, 106, 118, 129, 141, 153, 166, 181, 197, 217, 241};
+ auto val128 = _mm_loadu_si128((const __m128i *)kvalues_iq4nl);
+ return MM256_SET_M128I(val128, val128);
+ }
+
+ Q4Bits bits;
+ Scales8K s8k;
+ ScaleIQ4XS siq4;
+ const __m256i values;
+};
+
+struct DequantizerQ5K final : public BaseDequantizer<block_q5_K> {
+ DequantizerQ5K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+ template <typename Q8>
+ inline __m256i new_block(int i, const Q8& q8, __m256 * accd) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ hbits.load(x[i].qh);
+ return s8k.process_mins_and_scales(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd);
+ }
+ inline void prepare(int i, int j) {
+ bits.prepare(x[i].qs, j);
+ hbits.apply(bits, j == 0);
+ }
+
+ Q4Bits bits;
+ HighBit5 hbits;
+ Scales8K s8k;
+};
+
+template <typename Q8>
+inline void process_mins_and_scales_16(const __m128i& scales128, const Q8& q8, int i, float d,
+ __m256 * accm, __m256i * scales) {
+ const __m256i all_scales = _mm256_cvtepi8_epi16(scales128);
+ process_mins_16(all_scales, q8, i, d, accm);
+ prepare_scales_16(all_scales, scales);
+}
+
+struct DequantizerQ3K final : public BaseDequantizer<block_q3_K> {
+ DequantizerQ3K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ hbits.load(x[i].hmask);
+ process_mins_and_scales_16(sc3.make_scales((const uint16_t *)x[i].scales), q8, i, -4.f*d, accm, scales);
+ }
+ inline void prepare(int i, int j) {
+ bits.prepare(x[i].qs, j);
+ hbits.apply(bits, j == 0);
+ }
+
+ Q2Bits bits;
+ HighBit3 hbits;
+ ScaleQ3 sc3;
+
+ const __m128i m32 = _mm_set1_epi8(-32);
+};
+
+struct DequantizerQ2K final : public BaseDequantizer<block_q2_K> {
+ DequantizerQ2K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ const __m128i mins_and_scales = _mm_loadu_si128((const __m128i*)x[i].scales);
+ const __m128i scales8 = _mm_and_si128(mins_and_scales, m4);
+ const __m128i mins8 = _mm_and_si128(_mm_srli_epi16(mins_and_scales, 4), m4);
+ process_mins_16(_mm256_cvtepi8_epi16(mins8), q8, i, -GGML_FP16_TO_FP32(x[i].dmin), accm);
+ prepare_scales_16(_mm256_cvtepi8_epi16(scales8), scales);
+ }
+ inline void prepare(int i, int j) {
+ bits.prepare(x[i].qs, j);
+ }
+
+ Q2Bits bits;
+
+ const __m128i m4 = _mm_set1_epi8(0xf);
+};
+
+struct DequantizerQ6K final : public BaseDequantizer<block_q6_K> {
+ DequantizerQ6K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
+ template <typename Q8>
+ inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ process_mins_and_scales_16(_mm_loadu_si128((const __m128i *)x[i].scales), q8, i, -32.f*d, accm, scales);
+ }
+ inline void prepare(int i, int j) {
+ bits.prepare64(x[i].ql, j);
+ auto hbits = _mm256_loadu_si256((const __m256i *)x[i].qh + j);
+ bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 4), mh));
+ bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh));
+ bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(hbits, mh));
+ bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_srli_epi16(hbits, 2), mh));
+ }
+
+ Q4Bits bits;
+ const __m256i mh = _mm256_set1_epi8(0x30);
+};
+
+inline __m256i get_scale_shuffle_16(int i) {
+ static const uint8_t k_shuffle[128] = {
+ 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3,
+ 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7,
+ 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,
+ 12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13, 14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,
+ };
+ return _mm256_loadu_si256((const __m256i*)k_shuffle + i);
+}
+
+inline void set_scales_16(const __m256i& all_scales, __m256i * scales) {
+ scales[0] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(0));
+ scales[1] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(1));
+ scales[2] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(2));
+ scales[3] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(3));
+}
+
+template <typename Dequantizer, int nrc_y>
+static void mul_mat_qY_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ assert(n%QK_K == 0);
+ const int nb = n/QK_K;
+
+ Q8<nrc_y> q8(info);
+
+ __m256i all_scales[2];
+ __m256i scales[4];
+ __m256 accd[nrc_y];
+
+ Dequantizer deq(vx, bx);
+
+ for (int ix = 0; ix < nrc_x; ++ix) {
+
+ deq.new_row(ix);
+
+ for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_ps();
+
+ for (int i = 0; i < nb; ++i) {
+
+ deq.new_block(i, q8, accd, all_scales);
+
+ __m256i sumi[nrc_y];
+
+ for (int j = 0; j < QK_K/128; ++j) {
+ deq.prepare(i, j);
+ set_scales_16(all_scales[j], scales);
+ multiply_add(deq.bits, scales, j, i, q8, sumi);
+ }
+
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ accd[iy] = _mm256_fmadd_ps(_mm256_set1_ps(deq.d*q8.scale(iy, i)), _mm256_cvtepi32_ps(sumi[iy]), accd[iy]);
+ }
+
+ }
+
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ info.store(ix, iy, hsum_float_8(accd[iy]));
+ }
+
+ }
+
+}
+
+template <typename Dequantizer, int nrc_y>
+static void mul_mat_qX_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ assert(n % QK_K == 0);
+ const int nb = n / QK_K;
+
+ Q8<nrc_y> q8(info);
+
+ Dequantizer deq(vx, bx);
+
+ __m256 accd[nrc_y];
+ __m256i scales[4];
+
+ for (int ix = 0; ix < nrc_x; ++ix) {
+
+ for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_ps();
+
+ deq.new_row(ix);
+
+ for (int i = 0; i < nb; ++i) {
+
+ auto all_scales = deq.new_block(i, q8, accd);
+
+ __m256i sumi[nrc_y];
+
+ for (int j = 0; j < QK_K/128; ++j) {
+
+ deq.prepare(i, j);
+
+ set_scales_8(all_scales, j, scales);
+
+ multiply_add(deq.bits, scales, j, i, q8, sumi);
+
+ }
+
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ const __m256 vd = _mm256_set1_ps(deq.d*q8.scale(iy, i));
+ accd[iy] = _mm256_fmadd_ps(vd, _mm256_cvtepi32_ps(sumi[iy]), accd[iy]);
+ }
+
+ }
+
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ info.store(ix, iy, hsum_float_8(accd[iy]));
+ }
+
+ }
+}
+#endif // Zen4 or vanilla AVX2
+
+//
+// ============================== Legacy quants
+//
+
+struct DotHelper {
+ const __m256i m1 = _mm256_set1_epi16(1);
+#if defined(__AVX512VNNI__) && defined(__AVX512VL__)
+ inline __m256i dot(__m256i x, __m256i y) const {
+ return _mm256_dpbusd_epi32(_mm256_setzero_si256(), x, y);
+ }
+#else
+ inline __m256i dot(__m256i x, __m256i y) const {
+ return _mm256_madd_epi16(m1, _mm256_maddubs_epi16(x, y));
+ }
+#endif
+};
+
+struct SignedDot {
+ DotHelper helper;
+ inline __m256i compute(__m256i x, __m256i y) const {
+ return helper.dot(_mm256_sign_epi8(x, x), _mm256_sign_epi8(y, x));
+ }
+};
+struct UnsignedDot {
+ DotHelper helper;
+ inline __m256i compute(__m256i x, __m256i y) const {
+ return helper.dot(x, y);
+ }
+};
+template <typename Q8, typename Dot> struct Sum4 {
+ Dot dot;
+ inline __m256i compute(const __m256i * qx, const Q8 * y) const {
+ const __m256i p0 = dot.compute(qx[0], _mm256_loadu_si256((const __m256i *)y[0].qs));
+ const __m256i p1 = dot.compute(qx[1], _mm256_loadu_si256((const __m256i *)y[1].qs));
+ const __m256i p2 = dot.compute(qx[2], _mm256_loadu_si256((const __m256i *)y[2].qs));
+ const __m256i p3 = dot.compute(qx[3], _mm256_loadu_si256((const __m256i *)y[3].qs));
+ const __m256i p01 = _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p0, p1)); // 0,0, 1,1, 0,0, 1,1
+ const __m256i p23 = _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p2, p3)); // 2,2, 3,3, 2,2, 3,3
+ return _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p01, p23)); // 0,1,2,3, 0,1,2,3
+ }
+};
+
+struct Sum4_Q8 {
+ SignedDot dot;
+ static inline __m256i add1(__m256i a, __m256i b) {
+ return _mm256_add_epi32(_mm256_unpacklo_epi32(a, b), _mm256_unpackhi_epi32(a, b));
+ }
+ static inline __m256i add2(__m256i a, __m256i b) {
+ return _mm256_add_epi32(_mm256_unpacklo_epi64(a, b), _mm256_unpackhi_epi64(a, b));
+ }
+ inline __m256i compute(const __m256i * qx, const block_q8_0 * y) const {
+ const __m256i p0 = dot.compute(qx[0], _mm256_loadu_si256((const __m256i *)y[0].qs));
+ const __m256i p1 = dot.compute(qx[1], _mm256_loadu_si256((const __m256i *)y[1].qs));
+ const __m256i p2 = dot.compute(qx[2], _mm256_loadu_si256((const __m256i *)y[2].qs));
+ const __m256i p3 = dot.compute(qx[3], _mm256_loadu_si256((const __m256i *)y[3].qs));
+ const __m256i p01 = add1(p0, p1); // 0,1, 0,1, 0,1, 0,1
+ const __m256i p23 = add1(p2, p3); // 2,3, 2,3, 2,3, 2,3
+ return add2(p01, p23); // returns 0,1,2,3, 0,1,2,3
+ }
+};
+
+struct ScaleHelperQ_0 {
+ ggml_half scales8[4];
+ template <typename Q>
+ inline __m128 prepare4(const Q * y) {
+ for (int j = 0; j < 4; ++j) scales8[j] = y[j].d;
+ return _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)scales8));
+ }
+ template <typename Q>
+ inline __m128 prepare4(__m128 other_scales, const Q * y) {
+ return _mm_mul_ps(other_scales, prepare4<Q>(y));
+ }
+ template <typename Q> inline float prepare1(const Q * y) const { return GGML_FP16_TO_FP32(y->d); }
+ template <typename Q> inline float prepare1(float d, const Q * y) const { return d*prepare1(y); }
+};
+
+struct ScaleHelperQ_1 {
+ uint32_t scales8[4];
+ const __m128i shuffle = _mm_set_epi16(0x0f0e, 0x0b0a, 0x0706, 0x0302, 0x0d0c, 0x0908, 0x0504, 0x0100);
+
+ template <typename Q>
+ inline __m256 prepare4(const Q * y) {
+ for (int j = 0; j < 4; ++j) {
+ // it is slightly faster to directly dereference (const uint32 *)&y[j].d, but some compilers
+ // complain that this breaks strict-aliasing rules.
+ memcpy(scales8 + j, &y[j].d, sizeof(uint32_t));
+ }
+ return _mm256_cvtph_ps(_mm_shuffle_epi8(_mm_loadu_si128((const __m128i *)scales8), shuffle));
+ }
+
+ template <typename Q>
+ inline __m256 prepare4(__m256 other_scales, const Q * y) {
+ return _mm256_mul_ps(other_scales, prepare4<Q>(y));
+ }
+
+ template <typename Q> inline std::pair<float, float> prepare1(const Q * y) const {
+ return std::make_pair(GGML_FP16_TO_FP32(y->d), GGML_FP16_TO_FP32(y->m));
+ }
+ template <typename Q> inline std::pair<float, float> prepare1(const std::pair<float, float>& dm, const Q * y) const {
+ return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->m));
+ }
+ std::pair<float, float> inline prepare1(const std::pair<float, float>& dm, const block_q8_1 * y) const {
+ return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->s));
+ }
+};
+
+struct MinusType0 {
+ inline __m256 compute(__m128 d, int) const { return _mm256_set_m128(d, d); }
+ inline float compute(float d, int) const { return d; }
+ inline float result(__m256 acc, int) const { return hsum_float_8(acc); }
+};
+
+template <int nrc_y> struct MinusType1 {
+ __m128 accm[nrc_y];
+ MinusType1() { for (int iy = 0; iy < nrc_y; ++iy) accm[iy] = _mm_setzero_ps(); }
+ inline __m256 compute(__m256 dm, int iy) {
+ const __m128 d = _mm256_castps256_ps128(dm);
+ const __m128 m = _mm256_extractf128_ps(dm, 1);
+ accm[iy] = _mm_add_ps(accm[iy], m);
+ return _mm256_set_m128(d, d);
+ }
+ inline float compute(const std::pair<float, float>& dm, int iy) {
+ accm[iy] = _mm_add_ps(accm[iy], _mm_set1_ps(dm.second*0.25f));
+ return dm.first;
+ }
+ inline float result(__m256 acc, int iy) const {
+ const __m128 sum = _mm_add_ps(_mm256_castps256_ps128(acc), _mm256_extractf128_ps(acc, 1));
+ return hsum_float_4(_mm_add_ps(sum, accm[iy]));
+ }
+};
+
+template <typename Minus, int nrc_y, bool is_multiple_of_4> struct AccumT {
+ __m256 acc[nrc_y];
+ Minus accm;
+ AccumT() { for (int iy = 0; iy < nrc_y; ++iy) acc[iy] = _mm256_setzero_ps(); }
+ template <typename Unpacker, typename Scales, typename Sum, typename Q8>
+ inline void compute(int nb, Unpacker& unp, Scales& scales, Sum& sum, const Q8 ** y, const DataInfo& info, int ix) {
+ auto qx = unp.quants();
+ __m256 dall[nrc_y];
+ for (int i = 0; i < nb/4; ++i) {
+ auto other_scales = unp.set_block_4(i);
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ auto s12 = scales.prepare4(other_scales, y[iy] + 4*i);
+ dall[iy] = accm.compute(s12, iy);
+ }
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ auto pall = sum.compute(qx, y[iy] + 4*i);
+ acc[iy] = _mm256_fmadd_ps(dall[iy], _mm256_cvtepi32_ps(pall), acc[iy]);
+ }
+ }
+ if (!is_multiple_of_4) {
+ for (int i = 4*(nb/4); i < nb; ++i) {
+ auto other_scales = unp.set_block(i);
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ auto s12 = scales.prepare1(other_scales, y[iy] + i);
+ auto d = accm.compute(s12, iy);
+ const __m256i p0 = sum.dot.compute(qx[0], _mm256_loadu_si256((const __m256i *)y[iy][i].qs));
+ acc[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(p0), acc[iy]);
+ }
+ }
+ }
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ info.store(ix, iy, accm.result(acc[iy], iy));
+ //s[iy*bs] = accm.result(acc[iy], iy);
+ }
+ }
+};
+
+template <int nrc_y, bool is_multiple_of_4>
+using AccumType0 = AccumT<MinusType0, nrc_y, is_multiple_of_4>;
+
+template <int nrc_y, bool is_multiple_of_4>
+using AccumType1 = AccumT<MinusType1<nrc_y>, nrc_y, is_multiple_of_4>;
+
+using Sum4Type0 = Sum4<block_q8_0, SignedDot>;
+using Sum4Type1 = Sum4<block_q8_1, UnsignedDot>;
+
+template <typename Unpacker, typename Sum4Type, typename AccumType, typename Scales, typename Q8, int nrc_y>
+void mul_mat_qX_q8_Helper(int nb, const void * vx, size_t bx, const DataInfo& info, const Q8 ** y, int nrc_x) {
+ Unpacker unp(vx, bx);
+ Sum4Type sum4;
+ Scales scales;
+ for (int ix = 0; ix < nrc_x; ++ix) {
+ unp.set_row(ix);
+ AccumType accum;
+ accum.compute(nb, unp, scales, sum4, y, info, ix);
+ }
+}
+
+template <typename Unpacker, int nrc_y>
+void mul_mat_qX_0_q8_0_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ assert(n%Unpacker::block_size() == 0);
+ Q8<nrc_y, block_q8_0> q8(info);
+ int nb = n/Unpacker::block_size();
+ if (nb%4 == 0) {
+ mul_mat_qX_q8_Helper<Unpacker, Sum4Type0, AccumType0<nrc_y, true>, ScaleHelperQ_0, block_q8_0, nrc_y>(
+ nb, vx, bx, info, q8.y, nrc_x
+ );
+ } else {
+ mul_mat_qX_q8_Helper<Unpacker, Sum4Type0, AccumType0<nrc_y, false>, ScaleHelperQ_0, block_q8_0, nrc_y>(
+ nb, vx, bx, info, q8.y, nrc_x
+ );
+ }
+}
+
+template <typename Unpacker, int nrc_y>
+void mul_mat_qX_1_q8_1_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ assert(n%Unpacker::block_size() == 0);
+ Q8<nrc_y, block_q8_1> q8(info);
+ int nb = n/Unpacker::block_size();
+ if (nb%4 == 0) {
+ mul_mat_qX_q8_Helper<Unpacker, Sum4Type1, AccumType1<nrc_y, true>, ScaleHelperQ_1, block_q8_1, nrc_y>(
+ nb, vx, bx, info, q8.y, nrc_x
+ );
+ } else {
+ mul_mat_qX_q8_Helper<Unpacker, Sum4Type1, AccumType1<nrc_y, false>, ScaleHelperQ_1, block_q8_1, nrc_y>(
+ nb, vx, bx, info, q8.y, nrc_x
+ );
+ }
+}
+
+struct Dequantizer4bit {
+ const __m256i m4 = _mm256_set1_epi8(0xf);
+ inline __m256i dequant(const uint8_t * qs) const {
+ const __m128i aux128 = _mm_loadu_si128((const __m128i *)qs);
+ return _mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(aux128, 4), aux128), m4);
+ }
+};
+
+struct Q8_0_Dequantizer {
+ inline __m256i dequant(const block_q8_0 * x) const {
+ return _mm256_loadu_si256((const __m256i *)x->qs);
+ }
+};
+
+struct Q4_0_Dequantizer {
+ Dequantizer4bit b4;
+ const __m256i m8 = _mm256_set1_epi8(-8);
+ inline __m256i dequant(const block_q4_0 * x) const {
+ return _mm256_add_epi8(b4.dequant(x->qs), m8);
+ }
+};
+
+struct Q4_1_Dequantizer {
+ Dequantizer4bit b4;
+ inline __m256i dequant(const block_q4_1 * x) const {
+ return b4.dequant(x->qs);
+ }
+};
+
+struct HBitDequantizer {
+ const __m256i shuffle = _mm256_set_epi64x(0x0303030303030303, 0x0202020202020202, 0x0101010101010101, 0x0000000000000000);
+ const __m256i mask = _mm256_set1_epi64x(0x7fbfdfeff7fbfdfe);
+ const __m256i minus1 = _mm256_set1_epi64x(-1);
+ inline __m256i to_bytes(const uint8_t * bits) const {
+ // Note: Data in all ggml quants is at least 2-byte aligned.
+ // => we can cast to uint16_t and use or on two consecutive entries
+ // which is faster than memcpy
+ const uint16_t * aux16 = (const uint16_t *)bits;
+ const uint32_t aux32 = aux16[0] | (aux16[1] << 16);
+ //uint32_t aux32; memcpy(&aux32, bits, sizeof(uint32_t));
+ __m256i bytes = _mm256_shuffle_epi8(_mm256_set1_epi32(aux32), shuffle);
+ bytes = _mm256_or_si256(bytes, mask);
+ return _mm256_cmpeq_epi8(bytes, minus1);
+ }
+};
+
+struct Q5_0_Dequantizer {
+ Dequantizer4bit b4;
+ HBitDequantizer hbit;
+ const __m256i mh = _mm256_set1_epi8((char)0xF0);
+ inline __m256i dequant(const block_q5_0 * x) const {
+ const __m256i vqh = _mm256_andnot_si256(hbit.to_bytes(x->qh), mh);
+ return _mm256_or_si256(b4.dequant(x->qs), vqh);
+ }
+};
+
+struct Q5_1_Dequantizer {
+ Dequantizer4bit b4;
+ HBitDequantizer hbit;
+ const __m256i mh = _mm256_set1_epi8(0x10);
+ inline __m256i dequant(const block_q5_1 * x) const {
+ const __m256i vqh = _mm256_and_si256(hbit.to_bytes(x->qh), mh);
+ return _mm256_or_si256(b4.dequant(x->qs), vqh);
+ }
+};
+
+template <typename Q, typename Scales, typename Dequantizer>
+struct Q_Unpacker {
+ Q_Unpacker(const void * vx, size_t bx) : cx_0((const char *)vx), x((const Q*)cx_0), bx(bx) {}
+
+ const char * cx_0;
+ const Q * x;
+ size_t bx;
+
+ Scales scales;
+ Dequantizer deq;
+
+ __m256i qx[4];
+
+ inline const __m256i* quants() const { return qx; }
+
+ inline void set_row(int ix) { x = (const Q*)(cx_0 + ix*bx); }
+
+ inline auto set_block_4(int i) {
+ for (int j = 0; j < 4; ++j) {
+ qx[j] = deq.dequant(x + 4*i + j);
+ }
+ return scales.prepare4(x + 4*i);
+ }
+ inline auto set_block(int i) {
+ qx[0] = deq.dequant(x + i);
+ return scales.prepare1(x + i);
+ }
+};
+
+struct Q8_0_Unpacker final : public Q_Unpacker<block_q8_0, ScaleHelperQ_0, Q8_0_Dequantizer> {
+ Q8_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
+ inline static int block_size() { return QK4_0; }
+};
+struct Q4_0_Unpacker final : public Q_Unpacker<block_q4_0, ScaleHelperQ_0, Q4_0_Dequantizer> {
+ Q4_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
+ inline static int block_size() { return QK4_0; }
+};
+struct Q5_0_Unpacker final : public Q_Unpacker<block_q5_0, ScaleHelperQ_0, Q5_0_Dequantizer> {
+ Q5_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
+ inline static int block_size() { return QK5_0; }
+};
+struct Q4_1_Unpacker final : public Q_Unpacker<block_q4_1, ScaleHelperQ_1, Q4_1_Dequantizer> {
+ Q4_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
+ inline static int block_size() { return QK4_1; }
+};
+struct Q5_1_Unpacker final : public Q_Unpacker<block_q5_1, ScaleHelperQ_1, Q5_1_Dequantizer> {
+ Q5_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
+ inline static int block_size() { return QK4_1; }
+};
+
+template <int nrc_y>
+void mul_mat_q8_0_q8_0_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ assert(n%Q8_0_Unpacker::block_size() == 0);
+ Q8<nrc_y, block_q8_0> q8(info);
+ int nb = n/Q8_0_Unpacker::block_size();
+ if (nb%4 == 0) {
+ mul_mat_qX_q8_Helper<Q8_0_Unpacker, Sum4_Q8, AccumType0<nrc_y, true>, ScaleHelperQ_0, block_q8_0, nrc_y>(
+ nb, vx, bx, info, q8.y, nrc_x
+ );
+ } else {
+ mul_mat_qX_q8_Helper<Q8_0_Unpacker, Sum4_Q8, AccumType0<nrc_y, false>, ScaleHelperQ_0, block_q8_0, nrc_y>(
+ nb, vx, bx, info, q8.y, nrc_x
+ );
+ }
+}
+
+template <typename Dequantizer> void MulMat::set_functions(MulMat& m) {
+ if constexpr (std::is_same_v<Dequantizer, Q4_0_Unpacker> || std::is_same_v<Dequantizer, Q5_0_Unpacker>) {
+ m.funcs[0] = mul_mat_qX_0_q8_0_T<Dequantizer, 1>;
+ m.funcs[1] = mul_mat_qX_0_q8_0_T<Dequantizer, 2>;
+ m.funcs[2] = mul_mat_qX_0_q8_0_T<Dequantizer, 3>;
+ m.funcs[3] = mul_mat_qX_0_q8_0_T<Dequantizer, 4>;
+ m.funcs[4] = mul_mat_qX_0_q8_0_T<Dequantizer, 5>;
+ m.funcs[5] = mul_mat_qX_0_q8_0_T<Dequantizer, 6>;
+ m.funcs[6] = mul_mat_qX_0_q8_0_T<Dequantizer, 7>;
+ m.funcs[7] = mul_mat_qX_0_q8_0_T<Dequantizer, 8>;
+ }
+ else if constexpr (std::is_same_v<Dequantizer, Q4_1_Unpacker> || std::is_same_v<Dequantizer, Q5_1_Unpacker>) {
+ m.funcs[0] = mul_mat_qX_1_q8_1_T<Dequantizer, 1>;
+ m.funcs[1] = mul_mat_qX_1_q8_1_T<Dequantizer, 2>;
+ m.funcs[2] = mul_mat_qX_1_q8_1_T<Dequantizer, 3>;
+ m.funcs[3] = mul_mat_qX_1_q8_1_T<Dequantizer, 4>;
+ m.funcs[4] = mul_mat_qX_1_q8_1_T<Dequantizer, 5>;
+ m.funcs[5] = mul_mat_qX_1_q8_1_T<Dequantizer, 6>;
+ m.funcs[6] = mul_mat_qX_1_q8_1_T<Dequantizer, 7>;
+ m.funcs[7] = mul_mat_qX_1_q8_1_T<Dequantizer, 8>;
+ }
+ else {
+#ifdef HAVE_FANCY_SIMD
+ m.funcs[0] = mul_mat_qX_K_q8_K_T<Dequantizer, 1>;
+ m.funcs[1] = mul_mat_qX_K_q8_K_T<Dequantizer, 2>;
+ m.funcs[2] = mul_mat_qX_K_q8_K_T<Dequantizer, 3>;
+ m.funcs[3] = mul_mat_qX_K_q8_K_T<Dequantizer, 4>;
+ m.funcs[4] = mul_mat_qX_K_q8_K_T<Dequantizer, 5>;
+ m.funcs[5] = mul_mat_qX_K_q8_K_T<Dequantizer, 6>;
+ m.funcs[6] = mul_mat_qX_K_q8_K_T<Dequantizer, 7>;
+ m.funcs[7] = mul_mat_qX_K_q8_K_T<Dequantizer, 8>;
+#else
+ if constexpr (std::is_same_v<Dequantizer, DequantizerQ2K> ||
+ std::is_same_v<Dequantizer, DequantizerQ3K> ||
+ std::is_same_v<Dequantizer, DequantizerQ6K>) {
+ m.funcs[0] = mul_mat_qY_K_q8_K_T<Dequantizer, 1>;
+ m.funcs[1] = mul_mat_qY_K_q8_K_T<Dequantizer, 2>;
+ m.funcs[2] = mul_mat_qY_K_q8_K_T<Dequantizer, 3>;
+ m.funcs[3] = mul_mat_qY_K_q8_K_T<Dequantizer, 4>;
+ m.funcs[4] = mul_mat_qY_K_q8_K_T<Dequantizer, 5>;
+ m.funcs[5] = mul_mat_qY_K_q8_K_T<Dequantizer, 6>;
+ m.funcs[6] = mul_mat_qY_K_q8_K_T<Dequantizer, 7>;
+ m.funcs[7] = mul_mat_qY_K_q8_K_T<Dequantizer, 8>;
+ } else {
+ m.funcs[0] = mul_mat_qX_K_q8_K_T<Dequantizer, 1>;
+ m.funcs[1] = mul_mat_qX_K_q8_K_T<Dequantizer, 2>;
+ m.funcs[2] = mul_mat_qX_K_q8_K_T<Dequantizer, 3>;
+ m.funcs[3] = mul_mat_qX_K_q8_K_T<Dequantizer, 4>;
+ m.funcs[4] = mul_mat_qX_K_q8_K_T<Dequantizer, 5>;
+ m.funcs[5] = mul_mat_qX_K_q8_K_T<Dequantizer, 6>;
+ m.funcs[6] = mul_mat_qX_K_q8_K_T<Dequantizer, 7>;
+ m.funcs[7] = mul_mat_qX_K_q8_K_T<Dequantizer, 8>;
+ }
+#endif
+ }
+}
+
+bool MulMat::set_mul_mat(int typeA, int ne00, MulMat& mm, int& row_size_q8, int) {
+
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_K, ne00);
+
+ switch (typeA) {
+ case GGML_TYPE_Q2_K:
+ assert (ne00 % QK_K == 0);
+ MulMat::set_functions<DequantizerQ2K>(mm);
+ break;
+ case GGML_TYPE_Q3_K:
+ assert (ne00 % QK_K == 0);
+ MulMat::set_functions<DequantizerQ3K>(mm);
+ break;
+ case GGML_TYPE_Q4_K:
+ assert (ne00 % QK_K == 0);
+ MulMat::set_functions<DequantizerQ4K>(mm);
+ break;
+ case GGML_TYPE_Q5_K:
+ assert (ne00 % QK_K == 0);
+ MulMat::set_functions<DequantizerQ5K>(mm);
+ break;
+ case GGML_TYPE_Q6_K:
+ assert (ne00 % QK_K == 0);
+ MulMat::set_functions<DequantizerQ6K>(mm);
+ break;
+ case GGML_TYPE_IQ4_XS:
+ assert (ne00 % QK_K == 0);
+ MulMat::set_functions<DequantizerIQ4XS>(mm);
+ break;
+ case GGML_TYPE_Q4_0:
+ assert (ne00 % QK4_0 == 0);
+ MulMat::set_functions<Q4_0_Unpacker>(mm);
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
+ break;
+ case GGML_TYPE_Q4_1:
+ assert (ne00 % QK4_1 == 0);
+ MulMat::set_functions<Q4_1_Unpacker>(mm);
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_1, ne00);
+ break;
+ case GGML_TYPE_Q5_0:
+ assert (ne00 % QK5_0 == 0);
+ MulMat::set_functions<Q5_0_Unpacker>(mm);
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
+ break;
+ case GGML_TYPE_Q5_1:
+ assert (ne00 % QK5_1 == 0);
+ MulMat::set_functions<Q5_1_Unpacker>(mm);
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_1, ne00);
+ break;
+
+ default:
+ return false;
+ }
+
+ return true;
+}
+
+} // namespace
+
+
+#else // __aarch64__
+
+namespace {
+
+template <int nrc, typename block_q8 = block_q8_K> struct Q8 {
+
+ constexpr static int nrc_y = nrc;
+
+ Q8(const DataInfo& info) {
+ for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8 *)info.src1_row(iy);
+ }
+
+ inline int8x16x2_t load_quants(int iy, int i, int j) const { return vld1q_s8_x2(y[iy][i].qs + 32*j); }
+ inline int8x16x4_t load_quants_64(int iy, int i, int j) const { return vld1q_s8_x4(y[iy][i].qs + 64*j); }
+ inline int16x8x2_t load_bsums(int iy, int i) const { return vld1q_s16_x2(y[iy][i].bsums); }
+ inline int16x8_t load_bsums8(int iy, int i) const {
+ auto q8s = vld1q_s16_x2(y[iy][i].bsums);
+ return vpaddq_s16(q8s.val[0], q8s.val[1]);
+ }
+ inline float scale(int iy, int i) const { return y[iy][i].d; }
+
+ const block_q8 * y[nrc_y];
+};
+
+template <typename Q8>
+inline void compute_8_blocks(const uint8x16x4_t& qx_1, const uint8x16x4_t& qx_2, const Q8& q8,
+ const int32x4x2_t& scales, int iy, int i, int j, int32x4_t& sumi) {
+ auto mzero = vdupq_n_s32(0);
+ auto q8b_1 = q8.load_quants(iy, i, 4*j+0);
+ auto p1 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[0]), q8b_1.val[0]),
+ vreinterpretq_s8_u8(qx_1.val[1]), q8b_1.val[1]); // block 1
+ auto q8b_2 = q8.load_quants(iy, i, 4*j+1);
+ auto p2 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[2]), q8b_2.val[0]),
+ vreinterpretq_s8_u8(qx_1.val[3]), q8b_2.val[1]); // block 2
+ auto p12 = vpaddq_s32(p1, p2);
+
+ auto q8b_3 = q8.load_quants(iy, i, 4*j+2);
+ auto p3 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[0]), q8b_3.val[0]),
+ vreinterpretq_s8_u8(qx_2.val[1]), q8b_3.val[1]); // block 1
+ auto q8b_4 = q8.load_quants(iy, i, 4*j+3);
+ auto p4 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[2]), q8b_4.val[0]),
+ vreinterpretq_s8_u8(qx_2.val[3]), q8b_4.val[1]); // block 2
+ auto p34 = vpaddq_s32(p3, p4);
+
+ auto pall = vpaddq_s32(p12, p34);
+ sumi = vmlaq_s32(sumi, scales.val[j], pall);
+}
+
+template <typename Q8>
+inline void compute_16_blocks(const uint8x16x4_t& qx_1, const uint8x16x4_t& qx_2, const Q8& q8,
+ const int32x4x4_t& scales, int iy, int i, int j, int32x4_t& sumi) {
+
+ auto mzero = vdupq_n_s32(0);
+ auto q8b_1 = q8.load_quants(iy, i, 4*j+0);
+ auto p1 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[0]), q8b_1.val[0]),
+ ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[1]), q8b_1.val[1])); // blocks 0, 0, 1, 1,
+ auto q8b_2 = q8.load_quants(iy, i, 4*j+1);
+ auto p2 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[2]), q8b_2.val[0]),
+ ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[3]), q8b_2.val[1])); // blocks 3, 3, 4, 4,
+ auto p12 = vpaddq_s32(p1, p2); // blocks 0, 1, 2, 3
+ sumi = vmlaq_s32(sumi, scales.val[2*j+0], p12);
+
+ auto q8b_3 = q8.load_quants(iy, i, 4*j+2);
+ auto p3 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[0]), q8b_3.val[0]),
+ ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[1]), q8b_3.val[1])); // block 4, 4, 5, 5,
+ auto q8b_4 = q8.load_quants(iy, i, 4*j+3);
+ auto p4 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[2]), q8b_4.val[0]),
+ ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[3]), q8b_4.val[1])); // block 6, 6, 7, 7,
+ auto p34 = vpaddq_s32(p3, p4); // blocks 4, 5, 6, 7
+ sumi = vmlaq_s32(sumi, scales.val[2*j+1], p34);
+}
+
+template <typename Q8>
+inline void accum_mins_8(const int16x8_t& mins, const Q8& q8, float32x4_t * acc, int i, float c) {
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ auto q8s = q8.load_bsums8(iy, i);
+ int32x4_t b1 = vmull_s16(vget_low_s16(mins), vget_low_s16(q8s));
+ int32x4_t b2 = vmull_s16(vget_high_s16(mins), vget_high_s16(q8s));
+ float32x4_t prod = vcvtq_f32_s32(vaddq_s32(b1, b2));
+ acc[iy] = vmlaq_f32(acc[iy], prod, vdupq_n_f32(c*q8.scale(iy, i)));
+ }
+}
+template <typename Q8>
+inline void accum_mins_16(const int16x8x2_t& mins, const Q8& q8, float32x4_t * acc, int i, float c) {
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ auto q8s = q8.load_bsums(iy, i);
+ int32x4_t b1 = vmull_s16(vget_low_s16 (mins.val[0]), vget_low_s16 (q8s.val[0]));
+ int32x4_t b2 = vmull_s16(vget_high_s16(mins.val[0]), vget_high_s16(q8s.val[0]));
+ int32x4_t b3 = vmull_s16(vget_low_s16 (mins.val[1]), vget_low_s16 (q8s.val[1]));
+ int32x4_t b4 = vmull_s16(vget_high_s16(mins.val[1]), vget_high_s16(q8s.val[1]));
+ float32x4_t prod = vcvtq_f32_s32(vaddq_s32(vaddq_s32(b1, b2), vaddq_s32(b3, b4)));
+ acc[iy] = vmlaq_f32(acc[iy], prod, vdupq_n_f32(c*q8.scale(iy, i)));
+ }
+}
+
+struct Scales8 {
+ uint32_t utmp[4];
+ const uint8_t * sc8 = (const uint8_t *)utmp;
+ template <typename Q8, typename Qx>
+ inline int32x4x2_t process_scales_mins(const Qx& x, const Q8& q8, int i, float32x4_t * acc) {
+ make_q4_scales(x.scales, utmp);
+ int16x8_t mins = vmovl_s8(vld1_s8((const int8_t *)sc8 + 8));
+ accum_mins_8(mins, q8, acc, i, -GGML_FP16_TO_FP32(x.dmin));
+
+ uint8x8_t scales8 = vld1_u8(sc8);
+ uint16x8_t scales16 = vmovl_u8(scales8);
+ int32x4x2_t scales = {vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(scales16))),
+ vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(scales16)))};
+ return scales;
+ }
+};
+
+struct Q4bits {
+ const uint8x16_t m4b = vdupq_n_u8(0xf);
+ uint8x16x4_t b1, b2;
+ inline void prepare4(uint8x16x4_t& b, const uint8x16_t * val) const {
+ b.val[0] = vandq_u8(val[0], m4b);
+ b.val[2] = vshrq_n_u8(val[0], 4);
+ b.val[1] = vandq_u8(val[1], m4b);
+ b.val[3] = vshrq_n_u8(val[1], 4);
+ }
+ inline void prepare4_16(uint8x16x4_t& b, const uint8x16_t * val) const {
+ b.val[0] = vandq_u8(val[0], m4b);
+ b.val[1] = vshrq_n_u8(val[0], 4);
+ b.val[2] = vandq_u8(val[1], m4b);
+ b.val[3] = vshrq_n_u8(val[1], 4);
+ }
+ inline void prepare(const uint8_t * qs) {
+ auto q4bits = vld1q_u8_x2(qs);
+ prepare4(b1, q4bits.val);
+ q4bits = vld1q_u8_x2(qs+32);
+ prepare4(b2, q4bits.val);
+ }
+ inline void prepare_v2(const uint8_t * qs) {
+ auto q4bits = vld1q_u8_x4(qs);
+ prepare4(b1, q4bits.val+0);
+ prepare4(b2, q4bits.val+2);
+ }
+ inline void prepare64(const uint8_t * qs) {
+ auto q4bits = vld1q_u8_x4(qs);
+ b1.val[0] = vandq_u8(q4bits.val[0], m4b);
+ b1.val[1] = vandq_u8(q4bits.val[1], m4b);
+ b1.val[2] = vandq_u8(q4bits.val[2], m4b);
+ b1.val[3] = vandq_u8(q4bits.val[3], m4b);
+ b2.val[0] = vshrq_n_u8(q4bits.val[0], 4);
+ b2.val[1] = vshrq_n_u8(q4bits.val[1], 4);
+ b2.val[2] = vshrq_n_u8(q4bits.val[2], 4);
+ b2.val[3] = vshrq_n_u8(q4bits.val[3], 4);
+ }
+ inline void prepare16(const uint8_t * qs) {
+ auto q4bits = vld1q_u8_x2(qs);
+ prepare4_16(b1, q4bits.val);
+ q4bits = vld1q_u8_x2(qs+32);
+ prepare4_16(b2, q4bits.val);
+ }
+ inline void prepare16_v2(const uint8_t * qs) {
+ auto q4bits = vld1q_u8_x4(qs);
+ prepare4_16(b1, q4bits.val+0);
+ prepare4_16(b2, q4bits.val+2);
+ }
+};
+
+struct Q2bits {
+ const uint8x16_t m4b = vdupq_n_u8(0x03);
+ uint8x16x4_t b1, b2;
+ inline void prepare(const uint8_t * qs) {
+ auto q2bits = vld1q_u8_x2(qs);
+ b1.val[0] = vandq_u8(q2bits.val[0], m4b);
+ b1.val[1] = vandq_u8(q2bits.val[1], m4b);
+
+ q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2);
+ q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2);
+ b1.val[2] = vandq_u8(q2bits.val[0], m4b);
+ b1.val[3] = vandq_u8(q2bits.val[1], m4b);
+
+ q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2);
+ q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2);
+ b2.val[0] = vandq_u8(q2bits.val[0], m4b);
+ b2.val[1] = vandq_u8(q2bits.val[1], m4b);
+
+ q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2);
+ q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2);
+ b2.val[2] = vandq_u8(q2bits.val[0], m4b);
+ b2.val[3] = vandq_u8(q2bits.val[1], m4b);
+ }
+};
+
+template <typename block_q>
+struct BaseDequantizer {
+ BaseDequantizer(const void * vx, size_t bx, int nrc) : vx(vx), x(nullptr), bx(bx), nrc(nrc) {}
+ inline void new_row(int ix) { x = (const block_q *)((const char *)vx + ix*bx); }
+ const void * vx;
+ const block_q * x;
+ const size_t bx;
+ const int nrc;
+};
+
+struct DequantizerQ4K final : public BaseDequantizer<block_q4_K> {
+ DequantizerQ4K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
+
+ constexpr static int num_blocks() { return 8; }
+ constexpr static bool should_scale_quants() { return false; }
+
+ template <typename Q8>
+ inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ return s8.process_scales_mins(x[i], q8, i, acc);
+ }
+ inline void prepare(int i, int j) {
+ if (nrc == 1) bits.prepare_v2(x[i].qs+64*j);
+ else bits.prepare(x[i].qs+64*j);
+ }
+
+ Q4bits bits;
+ Scales8 s8;
+
+ float d;
+};
+
+struct HighBit5 {
+ const uint8x16_t mhb = vdupq_n_u8(0x10);
+ uint8x16x2_t bits;
+ inline void apply(uint8x16x4_t& b1, uint8x16x4_t& b2, bool do_shift) {
+ b1.val[0] = vorrq_u8(b1.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 4), mhb));
+ b1.val[1] = vorrq_u8(b1.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 4), mhb));
+ b1.val[2] = vorrq_u8(b1.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 3), mhb));
+ b1.val[3] = vorrq_u8(b1.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 3), mhb));
+
+ b2.val[0] = vorrq_u8(b2.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 2), mhb));
+ b2.val[1] = vorrq_u8(b2.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 2), mhb));
+ b2.val[2] = vorrq_u8(b2.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 1), mhb));
+ b2.val[3] = vorrq_u8(b2.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 1), mhb));
+
+ if (do_shift) {
+ bits.val[0] = vshrq_n_u8(bits.val[0], 4);
+ bits.val[1] = vshrq_n_u8(bits.val[1], 4);
+ }
+ }
+};
+
+struct HighBit3 {
+ const uint8x16_t mhb = vdupq_n_u8(0x04);
+ uint8x16x2_t bits;
+ inline void apply(uint8x16x4_t& b1, uint8x16x4_t& b2, bool do_shift) {
+ b1.val[0] = vorrq_u8(b1.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 2), mhb));
+ b1.val[1] = vorrq_u8(b1.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 2), mhb));
+ b1.val[2] = vorrq_u8(b1.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 1), mhb));
+ b1.val[3] = vorrq_u8(b1.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 1), mhb));
+
+ b2.val[0] = vorrq_u8(b2.val[0], vandq_u8(bits.val[0], mhb));
+ b2.val[1] = vorrq_u8(b2.val[1], vandq_u8(bits.val[1], mhb));
+ b2.val[2] = vorrq_u8(b2.val[2], vandq_u8(vshrq_n_u8(bits.val[0], 1), mhb));
+ b2.val[3] = vorrq_u8(b2.val[3], vandq_u8(vshrq_n_u8(bits.val[1], 1), mhb));
+
+ if (do_shift) {
+ bits.val[0] = vshrq_n_u8(bits.val[0], 4);
+ bits.val[1] = vshrq_n_u8(bits.val[1], 4);
+ }
+ }
+};
+
+struct DequantizerQ5K final : public BaseDequantizer<block_q5_K> {
+ DequantizerQ5K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
+
+ constexpr static int num_blocks() { return 8; }
+ constexpr static bool should_scale_quants() { return false; }
+
+ template <typename Q8>
+ inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ h.bits = vld1q_u8_x2(x[i].qh);
+ return s8.process_scales_mins(x[i], q8, i, acc);
+ }
+ inline void prepare(int i, int j) {
+ if (nrc == 1) bits.prepare_v2(x[i].qs+64*j);
+ else bits.prepare(x[i].qs+64*j);
+ h.apply(bits.b1, bits.b2, j == 0);
+ }
+
+ Q4bits bits;
+ HighBit5 h;
+ Scales8 s8;
+
+ uint8x16x2_t hbits;
+
+ float d;
+};
+
+inline int32x4x4_t make_wider(const int16x8x2_t& scales16) {
+ int32x4x4_t scales = {
+ vmovl_s16(vget_low_s16 (scales16.val[0])),
+ vmovl_s16(vget_high_s16(scales16.val[0])),
+ vmovl_s16(vget_low_s16 (scales16.val[1])),
+ vmovl_s16(vget_high_s16(scales16.val[1])),
+ };
+ return scales;
+}
+
+template <typename Q8>
+inline int32x4x4_t process_scales_mins_16(const int8x16_t& scales8, const Q8& q8, float32x4_t * acc, int i, float c) {
+ int16x8x2_t scales16;
+ scales16.val[0] = vmovl_s8(vget_low_s8(scales8));
+ scales16.val[1] = vmovl_s8(vget_high_s8(scales8));
+ accum_mins_16(scales16, q8, acc, i, c);
+ return make_wider(scales16);
+}
+
+struct DequantizerQ6K final : public BaseDequantizer<block_q6_K> {
+ DequantizerQ6K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
+
+ constexpr static int num_blocks() { return 16; }
+ constexpr static bool should_scale_quants() { return false; }
+
+ template <typename Q8>
+ inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ return process_scales_mins_16(vld1q_s8(x[i].scales), q8, acc, i, -32.f*d);
+ }
+ inline void prepare(int i, int j) {
+
+ auto hbits = vld1q_u8_x2(x[i].qh + 32*j);
+
+ bits.prepare64(x[i].ql+64*j);
+ bits.b1.val[0] = vorrq_u8(bits.b1.val[0], vandq_u8(vshlq_n_u8(hbits.val[0], 4), mhb));
+ bits.b1.val[1] = vorrq_u8(bits.b1.val[1], vandq_u8(vshlq_n_u8(hbits.val[1], 4), mhb));
+ bits.b1.val[2] = vorrq_u8(bits.b1.val[2], vandq_u8(vshlq_n_u8(hbits.val[0], 2), mhb));
+ bits.b1.val[3] = vorrq_u8(bits.b1.val[3], vandq_u8(vshlq_n_u8(hbits.val[1], 2), mhb));
+
+ bits.b2.val[0] = vorrq_u8(bits.b2.val[0], vandq_u8(hbits.val[0], mhb));
+ bits.b2.val[1] = vorrq_u8(bits.b2.val[1], vandq_u8(hbits.val[1], mhb));
+ bits.b2.val[2] = vorrq_u8(bits.b2.val[2], vandq_u8(vshrq_n_u8(hbits.val[0], 2), mhb));
+ bits.b2.val[3] = vorrq_u8(bits.b2.val[3], vandq_u8(vshrq_n_u8(hbits.val[1], 2), mhb));
+
+ }
+
+ Q4bits bits;
+
+ const uint8x16_t mhb = vdupq_n_u8(0x30);
+
+ float d;
+};
+
+struct DequantizerQ3K final : public BaseDequantizer<block_q3_K> {
+ DequantizerQ3K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
+
+ constexpr static int num_blocks() { return 16; }
+ constexpr static bool should_scale_quants() { return false; }
+
+ template <typename Q8>
+ inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ h.bits = vld1q_u8_x2(x[i].hmask);
+ const uint16_t * sc16 = (const uint16_t *)x[i].scales;
+ uint32_t aux0 = sc16[0] | (sc16[1] << 16);
+ uint32_t aux1 = sc16[2] | (sc16[3] << 16);
+ uint32_t aux2 = sc16[4] | (sc16[5] << 16);
+ aux32[0] = (aux0 & 0x0f0f0f0f) | ((aux2 << 4) & 0x30303030);
+ aux32[1] = (aux1 & 0x0f0f0f0f) | ((aux2 << 2) & 0x30303030);
+ aux32[2] = ((aux0 >> 4) & 0x0f0f0f0f) | ((aux2 >> 0) & 0x30303030);
+ aux32[3] = ((aux1 >> 4) & 0x0f0f0f0f) | ((aux2 >> 2) & 0x30303030);
+ return process_scales_mins_16(vaddq_s8(vld1q_s8((const int8_t *)aux32), vdupq_n_s8(-32)), q8, acc, i, -4.f*d);
+ }
+
+ inline void prepare(int i, int j) {
+ bits.prepare(x[i].qs+32*j);
+ h.apply(bits.b1, bits.b2, j == 0);
+ }
+
+ uint32_t aux32[4];
+
+ Q2bits bits;
+
+ const uint8x16_t mhb = vdupq_n_u8(0x04);
+ HighBit3 h;
+
+ float d;
+};
+
+struct DequantizerQ2K final : public BaseDequantizer<block_q2_K> {
+ DequantizerQ2K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
+
+ constexpr static int num_blocks() { return 16; }
+ constexpr static bool should_scale_quants() { return true; }
+
+ template <typename Q8>
+ inline void process_scales(int i, const Q8& q8, float32x4_t * acc) {
+ d = GGML_FP16_TO_FP32(x[i].d);
+ auto scales_and_mins = vld1q_u8(x[i].scales);
+ auto mins8 = vreinterpretq_s8_u8(vshrq_n_u8(scales_and_mins, 4));
+ int16x8x2_t scales16;
+ scales16.val[0] = vmovl_s8(vget_low_s8(mins8));
+ scales16.val[1] = vmovl_s8(vget_high_s8(mins8));
+ accum_mins_16(scales16, q8, acc, i, -GGML_FP16_TO_FP32(x[i].dmin));
+
+ scales8 = vandq_u8(scales_and_mins, vdupq_n_u8(0xf));
+ }
+
+ template <typename Q8>
+ inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) {
+ process_scales(i, q8, acc);
+ int16x8x2_t scales16;
+ scales16.val[0] = vmovl_s8(vget_low_s8(vreinterpretq_s8_u8(scales8)));
+ scales16.val[1] = vmovl_s8(vget_high_s8(vreinterpretq_s8_u8(scales8)));
+ return make_wider(scales16);
+ }
+
+ template <typename Q8>
+ inline void compute(const Q8& q8, int i, int j, int32x4_t * sumi) {
+ auto m1 = vdupq_n_u8(1);
+ auto shuffle = vdupq_n_u8(8*j);
+ bits.b1.val[0] = vmulq_u8(bits.b1.val[0], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
+ bits.b1.val[1] = vmulq_u8(bits.b1.val[1], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
+ bits.b1.val[2] = vmulq_u8(bits.b1.val[2], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
+ bits.b1.val[3] = vmulq_u8(bits.b1.val[3], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
+ bits.b2.val[0] = vmulq_u8(bits.b2.val[0], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
+ bits.b2.val[1] = vmulq_u8(bits.b2.val[1], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
+ bits.b2.val[2] = vmulq_u8(bits.b2.val[2], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
+ bits.b2.val[3] = vmulq_u8(bits.b2.val[3], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ auto q8b_1 = q8.load_quants(iy, i, 4*j+0);
+ sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b1.val[0]), q8b_1.val[0]),
+ vreinterpretq_s8_u8(bits.b1.val[1]), q8b_1.val[1]);
+
+ auto q8b_2 = q8.load_quants(iy, i, 4*j+1);
+ sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b1.val[2]), q8b_2.val[0]),
+ vreinterpretq_s8_u8(bits.b1.val[3]), q8b_2.val[1]);
+
+ auto q8b_3 = q8.load_quants(iy, i, 4*j+2);
+ sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b2.val[0]), q8b_3.val[0]),
+ vreinterpretq_s8_u8(bits.b2.val[1]), q8b_3.val[1]);
+
+ auto q8b_4 = q8.load_quants(iy, i, 4*j+3);
+ sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b2.val[2]), q8b_4.val[0]),
+ vreinterpretq_s8_u8(bits.b2.val[3]), q8b_4.val[1]);
+ }
+ }
+
+ inline void prepare(int i, int j) {
+ bits.prepare(x[i].qs+32*j);
+ }
+
+ uint32_t aux32[4];
+
+ uint8x16_t scales8;
+
+ Q2bits bits;
+
+ float d;
+};
+
+struct DequantizerIQ4XS final : public BaseDequantizer<block_iq4_xs> {
+
+ static int8x16_t load_values() {
+ static const int8_t iq4nl_values[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113};
+ return vld1q_s8(iq4nl_values);
+ }
+
+ DequantizerIQ4XS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc), values(load_values()) {}
+
+ constexpr static int num_blocks() { return 8; }
+ constexpr static bool should_scale_quants() { return false; }
+
+ inline void new_row(int ix) { x = (const block_iq4_xs *)((const char *)vx + bx*ix); }
+
+ template <typename Q8>
+ inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) {
+ (void)q8;
+ (void)acc;
+ d = GGML_FP16_TO_FP32(x[i].d);
+ const uint16_t scales_h = x[i].scales_h;
+ const uint16_t * scales_l = (const uint16_t *)x[i].scales_l;
+ aux32[0] = scales_l[0] | (scales_l[1] << 16);
+ aux32[1] = aux32[0] >> 4;
+ // scl is ordered as 0, 2, 4, 6, 1, 3, 5, 7
+ uint8x8_t scl8 = vand_u8(vld1_u8((const uint8_t *)aux32), vdup_n_u8(0xf));
+ uint16_t * aux16 = (uint16_t *)aux32;
+ aux16[0] = scales_h << 4; aux16[1] = scales_h << 2; aux16[2] = scales_h; aux16[3] = scales_h >> 2;
+ // sch is ordered as 0, 4, 1, 5, 2, 6, 3, 7
+ uint8x8_t sch8 = vand_u8(vld1_u8((const uint8_t *)aux16), vdup_n_u8(0x30));
+ int8x8_t scales8 = vadd_s8(vreinterpret_s8_u8(vorr_u8(scl8, vtbl1_u8(sch8, vreinterpret_u8_u32(hshuff)))), vdup_n_s8(-32));
+ // shuffle 0, 2, 4, 6, 1, 3, 5, 7 -> 0, 1, 2, 3, 4, 5, 6, 7
+ scales8 = vtbl1_s8(scales8, vreinterpret_s8_u32(hshuff));
+ int16x8_t scales16 = vmovl_s8(scales8);
+ int32x4x2_t scales = {vmovl_s16(vget_low_s16(scales16)), vmovl_s16(vget_high_s16(scales16))};
+ return scales;
+ }
+ inline void prepare(int i, int j) {
+ bits.prepare16(x[i].qs+64*j);
+ //if (nrc == 1) {
+ // bits.prepare16_v2(x[i].qs+64*j);
+ //} else {
+ // bits.prepare16(x[i].qs+64*j);
+ //}
+ for (int k = 0; k < 4; ++k) {
+ bits.b1.val[k] = vreinterpretq_u8_s8(vqtbl1q_s8(values, bits.b1.val[k]));
+ bits.b2.val[k] = vreinterpretq_u8_s8(vqtbl1q_s8(values, bits.b2.val[k]));
+ }
+ }
+
+ Q4bits bits;
+ const int8x16_t values;
+ uint32_t aux32[2];
+
+ constexpr static uint32x2_t hshuff = {0x05010400, 0x07030602};
+
+ float d;
+};
+
+template <int nrc_y, typename Dequantizer>
+static void mul_mat_qX_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ assert(n % QK_K == 0);
+ const int nb = n / QK_K;
+
+ Q8<nrc_y, block_q8_K> q8(info);
+
+ Dequantizer deq(vx, bx, nrc_y);
+
+ for (int ix = 0; ix < nrc_x; ++ix) {
+
+ deq.new_row(ix);
+
+ float32x4_t acc[nrc_y];
+ for (int iy = 0; iy < nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f);
+
+ for (int i = 0; i < nb; ++i) {
+
+ int32x4_t sumi[nrc_y];
+ for (int iy = 0; iy < nrc_y; ++iy) sumi[iy] = vdupq_n_s32(0);
+
+ if constexpr (nrc_y > 1 && Dequantizer::should_scale_quants()) {
+ deq.process_scales(i, q8, acc);
+ deq.prepare(i, 0);
+ deq.compute(q8, i, 0, sumi);
+ deq.prepare(i, 1);
+ deq.compute(q8, i, 1, sumi);
+ } else {
+ if constexpr (Dequantizer::num_blocks() == 8) {
+ auto scales = deq.new_block(i, q8, acc);
+ deq.prepare(i, 0);
+ for (int iy = 0; iy < nrc_y; ++iy) compute_8_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 0, sumi[iy]);
+ deq.prepare(i, 1);
+ for (int iy = 0; iy < nrc_y; ++iy) compute_8_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 1, sumi[iy]);
+ }
+ else if constexpr (Dequantizer::num_blocks() == 16) {
+ auto scales = deq.new_block(i, q8, acc);
+ deq.prepare(i, 0);
+ for (int iy = 0; iy < nrc_y; ++iy) compute_16_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 0, sumi[iy]);
+ deq.prepare(i, 1);
+ for (int iy = 0; iy < nrc_y; ++iy) compute_16_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 1, sumi[iy]);
+ }
+ else {
+ GGML_ASSERT(false);
+ }
+ }
+
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ acc[iy] = vmlaq_f32(acc[iy], vcvtq_f32_s32(sumi[iy]), vdupq_n_f32(deq.d*q8.scale(iy, i)));
+ }
+ }
+
+ for (int iy = 0; iy < nrc_y; ++iy) {
+ info.store(ix, iy, vaddvq_f32(acc[iy]));
+ }
+ }
+}
+
+// =========================================== Legacy quants
+
+template <typename Block>
+inline float16x4_t load_scales_q0(const Block * x, ggml_half * aux) {
+ for (int k = 0; k < 4; ++k) aux[k] = x[k].d;
+ return vld1_f16((const float16_t *)aux);
+}
+
+template <typename Block>
+inline float16x8_t load_scales_q1(const Block * x, ggml_half * aux) {
+ if constexpr (std::is_same_v<Block, block_q8_1>) {
+ for (int k = 0; k < 4; ++k) { aux[k] = x[k].d; aux[k+4] = x[k].s; }
+ } else {
+ for (int k = 0; k < 4; ++k) { aux[k] = x[k].d; aux[k+4] = x[k].m; }
+ }
+ return vld1q_f16((const float16_t *)aux);
+}
+
+struct Q4LegacyBits {
+ template <typename Block>
+ inline void prepare(const Block * x) {
+ for (int i = 0; i < 4; ++i) {
+ auto q4bits = vld1q_u8(x[i].qs);
+ b[2*i+0] = vreinterpretq_s8_u8(vandq_u8(q4bits, m4b));
+ b[2*i+1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits, 4));
+ }
+ }
+ inline void prepare1(const uint8_t * qs, int8x16_t * q) const {
+ auto q4bits = vld1q_u8(qs);
+ q[0] = vreinterpretq_s8_u8(vandq_u8(q4bits, m4b));
+ q[1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits, 4));
+ }
+ inline void prepare1(const uint8_t * qs) {
+ prepare1(qs, b);
+ }
+ const uint8x16_t m4b = vdupq_n_u8(0xf);
+ int8x16_t b[8];
+};
+
+// One would think this commented out version would do better than the one below
+// because it offers more opportunities to execute instructions in parallel.
+// Instead, it runs significantly slower. Why? If the compiler is running out of vector registers
+// cannot it just do the sequential version below on its own?
+//inline int32x4_t sum_4_blocks(const int8x16_t * b, const int8_t * qs) {
+// const auto q8b_1 = vld1q_s8_x2(qs + 0);
+// auto p12 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[0], q8b_1.val[0]), b[1], q8b_1.val[1]);
+// const auto q8b_2 = vld1q_s8_x2(qs + 32);
+// auto p34 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[2], q8b_2.val[0]), b[3], q8b_2.val[1]);
+// auto p1234 = vpaddq_s32(p12, p34);
+// const auto q8b_3 = vld1q_s8_x2(qs + 64);
+// auto p56 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[4], q8b_3.val[0]), b[5], q8b_3.val[1]);
+// const auto q8b_4 = vld1q_s8_x2(qs + 96);
+// auto p78 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[6], q8b_4.val[0]), b[7], q8b_4.val[1]);
+// return vpaddq_s32(p1234, vpaddq_s32(p56, p78));
+//}
+
+inline int32x4_t sum_4_blocks(const int8x16_t * b, const int8_t * qs) {
+ auto q8b = vld1q_s8_x2(qs + 0);
+ auto p12 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[0], q8b.val[0]), b[1], q8b.val[1]);
+ q8b = vld1q_s8_x2(qs + 32);
+ auto p34 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[2], q8b.val[0]), b[3], q8b.val[1]);
+ auto p1234 = vpaddq_s32(p12, p34);
+ q8b = vld1q_s8_x2(qs + 64);
+ auto p56 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[4], q8b.val[0]), b[5], q8b.val[1]);
+ q8b = vld1q_s8_x2(qs + 96);
+ auto p78 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[6], q8b.val[0]), b[7], q8b.val[1]);
+ return vpaddq_s32(p1234, vpaddq_s32(p56, p78));
+}
+
+template <int nrc> struct Q80 {
+
+ constexpr static int nrc_y = nrc;
+
+ Q80(const DataInfo& info) {
+ for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8_0 *)info.src1_row(iy);
+ }
+
+ inline const int8_t * quant_data(int iy, int i) const {
+ const block_q8_0_x4 * y4 = (const block_q8_0_x4 *)y[iy] + i;
+ return y4->qs;
+ }
+
+ inline float16x4_t load_scales(int iy, int i) const {
+ const block_q8_0_x4 * y4 = (const block_q8_0_x4 *)y[iy] + i;
+ return vld1_f16((const float16_t *)y4->d);
+ }
+
+ template <typename Dequantizer>
+ inline void process_scales(int i, Dequantizer& deq, float16x4_t * sc16, float32x4_t * /*acc*/) const {
+ auto qx_scales = deq.new_block(i);
+ for (int iy = 0; iy < nrc; ++iy) {
+ auto q8_scales = load_scales(iy, i);
+ sc16[iy] = vmul_f16(qx_scales, q8_scales);
+ }
+ }
+
+ template <typename Dequantizer>
+ inline void process_1_block(int i, Dequantizer& deq, float32x4_t * acc) const {
+ deq.prepare1(i);
+ float d = GGML_FP16_TO_FP32(deq.x[i].d);
+ for (int iy = 0; iy < nrc; ++iy) {
+ auto q8b = vld1q_s8_x2(y[iy][i].qs);
+ auto p = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), deq.bits.b[0], q8b.val[0]), deq.bits.b[1], q8b.val[1]);
+ acc[iy] = vmlaq_f32(acc[iy], vdupq_n_f32(d*GGML_FP16_TO_FP32(y[iy][i].d)), vcvtq_f32_s32(p));
+ }
+ }
+
+ const block_q8_0 * y[nrc_y];
+};
+
+template <int nrc> struct Q81 {
+
+ constexpr static int nrc_y = nrc;
+
+ Q81(const DataInfo& info) {
+ for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8_1 *)info.src1_row(iy);
+ }
+
+ inline const int8_t * quant_data(int iy, int i) const {
+ const block_q8_1_x4 * y4 = (const block_q8_1_x4 *)y[iy] + i;
+ return y4->qs;
+ }
+
+ inline float16x8_t load_scales(int iy, int i) const {
+ const block_q8_1_x4 * y4 = (const block_q8_1_x4 *)y[iy] + i;
+ return vld1q_f16((const float16_t *)y4->d);
+ }
+
+ template <typename Dequantizer>
+ inline void process_scales(int i, Dequantizer& deq, float16x4_t * sc16, float32x4_t * acc) const {
+ auto qx_scales = deq.new_block(i);
+ for (int iy = 0; iy < nrc; ++iy) {
+ auto q8_scales = load_scales(iy, i);
+ auto m = vmul_f16(vget_high_f16(qx_scales), vget_high_f16(q8_scales));
+ acc[iy] = vaddq_f32(acc[iy], vcvt_f32_f16(m));
+ sc16[iy] = vmul_f16(vget_low_f16(qx_scales), vget_low_f16(q8_scales));
+ }
+ }
+
+ template <typename Dequantizer>
+ inline void process_1_block(int i, Dequantizer& deq, float32x4_t * acc) const {
+ deq.prepare1(i);
+ float d = GGML_FP16_TO_FP32(deq.x[i].d), m = 0.25f*GGML_FP16_TO_FP32(deq.x[i].m);
+ for (int iy = 0; iy < nrc; ++iy) {
+ auto q8b = vld1q_s8_x2(y[iy][i].qs);
+ auto p = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), deq.bits.b[0], q8b.val[0]), deq.bits.b[1], q8b.val[1]);
+ acc[iy] = vmlaq_f32(acc[iy], vdupq_n_f32(d*GGML_FP16_TO_FP32(y[iy][i].d)), vcvtq_f32_s32(p));
+ acc[iy] = vaddq_f32(acc[iy], vdupq_n_f32(m*GGML_FP16_TO_FP32(y[iy][i].s)));
+ }
+ }
+
+ const block_q8_1 * y[nrc_y];
+};
+
+template <typename block_q>
+struct BaseLegacyDequantizer {
+
+ BaseLegacyDequantizer(const void * vx, size_t bx) : vx(vx), x(nullptr), bx(bx) {}
+
+ inline void new_row(int ix) { x = (const block_q *)((const char *)vx + bx*ix); }
+
+ Q4LegacyBits bits;
+
+ const void * vx;
+ const block_q * x;
+ size_t bx;
+};
+
+struct DequantizerQ40 final : public BaseLegacyDequantizer<block_q4_0> {
+
+ DequantizerQ40(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
+
+ inline void prepare1(int i, int8x16_t * q) const {
+ bits.prepare1(x[i].qs, q);
+ q[0] = vaddq_s8(q[0], m8);
+ q[1] = vaddq_s8(q[1], m8);
+ }
+ inline void prepare1(int i) {
+ prepare1(i, bits.b);
+ }
+
+ inline float16x4_t new_block(int i) {
+ ggml_half aux[4];
+ for (int k = 0; k < 4; ++k) {
+ aux[k] = x[4*i+k].d;
+ prepare1(4*i+k, bits.b + 2*k);
+ }
+ return vld1_f16((const float16_t *)aux);
+ }
+
+ const int8x16_t m8 = vdupq_n_s8(-8);
+ //ggml_half aux[4];
+};
+
+struct DequantizerQ41 : public BaseLegacyDequantizer<block_q4_1> {
+
+ DequantizerQ41(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
+
+ inline void prepare1(int i) {
+ bits.prepare1(x[i].qs);
+ }
+
+ inline float16x8_t new_block(int i) {
+ uint32_t aux32[4];
+ const uint32_t * s32 = (const uint32_t *)&x[4*i].d;
+ for (int k = 0; k < 4; ++k) {
+ aux32[k] = *s32; s32 += sizeof(block_q4_1)/4;
+ bits.prepare1(x[4*i+k].qs, bits.b + 2*k);
+ }
+ return vreinterpretq_f16_u8(vqtbl1q_u8(vld1q_u8((const uint8_t *)aux32), vreinterpretq_u8_u64(shuffle)));
+ }
+ // Leaving this commented out attempt to be reminded that I already tried this.
+ // It has basically the same performance as the version above.
+ //inline float16x8_t new_block(int i) {
+ // uint32x4_t scales = {};
+ // const block_q4_1 * xi = x + 4*i;
+ // const uint32_t * s32 = (const uint32_t *)&xi->d;
+ // scales = vsetq_lane_u32(*s32, scales, 0); s32 += sizeof(block_q4_1)/4;
+ // bits.prepare1(xi[0].qs, bits.b + 0);
+ // scales = vsetq_lane_u32(*s32, scales, 1); s32 += sizeof(block_q4_1)/4;
+ // bits.prepare1(xi[1].qs, bits.b + 2);
+ // scales = vsetq_lane_u32(*s32, scales, 2); s32 += sizeof(block_q4_1)/4;
+ // bits.prepare1(xi[2].qs, bits.b + 4);
+ // scales = vsetq_lane_u32(*s32, scales, 3);
+ // bits.prepare1(xi[3].qs, bits.b + 6);
+ // return vreinterpretq_f16_u8(vqtbl1q_u8(vreinterpretq_u8_u32(scales), vreinterpretq_u8_u64(shuffle)));
+ //}
+
+ const uint64x2_t shuffle = {0x0d0c090805040100, 0x0f0e0b0a07060302};
+};
+
+struct HighBit5Legacy {
+ inline uint8x16_t to_bytes(const uint8_t * qh) const {
+ uint8x16_t h = vqtbl1q_u8(vreinterpretq_u8_u16(vdupq_n_u16(*(const uint16_t *)qh)), shuffle);
+ return vceqq_u8(vandq_u8(h, vreinterpretq_u8_u64(mask)), vreinterpretq_u8_u64(mask));
+ }
+ inline uint8x16_t to_negated_bytes(const uint8_t * qh) const {
+ uint8x16_t h = vqtbl1q_u8(vreinterpretq_u8_u16(vdupq_n_u16(*(const uint16_t *)qh)), shuffle);
+ return vceqq_u8(vandq_u8(h, vreinterpretq_u8_u64(mask)), vdupq_n_u8(0));
+ }
+ const uint64x2_t mask = vdupq_n_u64(0x8040201008040201);
+ const uint8x16_t shuffle = vcombine_u8(vdup_n_u8(0), vdup_n_u8(1));
+};
+
+struct DequantizerQ50 final : public BaseLegacyDequantizer<block_q5_0> {
+
+ DequantizerQ50(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
+
+ inline void prepare1(int i, int8x16_t * q) const {
+ bits.prepare1(x[i].qs, q);
+ auto qh = x[i].qh;
+ q[0] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[0]), vandq_u8(mh, hbits.to_negated_bytes(qh+0))));
+ q[1] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[1]), vandq_u8(mh, hbits.to_negated_bytes(qh+2))));
+ }
+ inline void prepare1(int i) {
+ prepare1(i, bits.b);
+ }
+
+ inline float16x4_t new_block(int i) {
+ ggml_half aux[4];
+ for (int k = 0; k < 4; ++k) {
+ aux[k] = x[4*i+k].d;
+ prepare1(4*i+k, bits.b + 2*k);
+ }
+ return vld1_f16((const float16_t *)aux);
+ }
+
+ HighBit5Legacy hbits;
+
+ const uint8x16_t mh = vdupq_n_u8(0xf0);
+
+};
+
+struct DequantizerQ51 final : public BaseLegacyDequantizer<block_q5_1> {
+
+ DequantizerQ51(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
+
+ inline void prepare1(int i, int8x16_t * q) const {
+ bits.prepare1(x[i].qs, q);
+ auto qh = x[i].qh;
+ q[0] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[0]), vandq_u8(mh, hbits.to_bytes(qh+0))));
+ q[1] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[1]), vandq_u8(mh, hbits.to_bytes(qh+2))));
+ }
+ inline void prepare1(int i) {
+ bits.prepare1(x[i].qs, bits.b);
+ }
+
+ inline float16x8_t new_block(int i) {
+ uint32_t aux32[4];
+ const uint32_t * s32 = (const uint32_t *)&x[4*i].d;
+ for (int k = 0; k < 4; ++k) {
+ aux32[k] = *s32; s32 += sizeof(block_q5_1)/4;
+ prepare1(4*i+k, bits.b + 2*k);
+ }
+ return vreinterpretq_f16_u8(vqtbl1q_u8(vld1q_u8((const uint8_t *)aux32), vreinterpretq_u8_u64(shuffle)));
+ }
+
+ HighBit5Legacy hbits;
+
+ const uint8x16_t mh = vdupq_n_u8(0x10);
+ const uint64x2_t shuffle = {0x0d0c090805040100, 0x0f0e0b0a07060302};
+
+};
+
+template <typename Dequantizer, typename Q8>
+inline void sum_4(int i, Dequantizer& deq, const Q8& q8, const float16x4_t * sc16, float32x4_t * acc) {
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ auto pall = sum_4_blocks(deq.bits.b, q8.quant_data(iy, i));
+ auto scale = vcvt_f32_f16(sc16[iy]);
+ acc[iy] = vmlaq_f32(acc[iy], scale, vcvtq_f32_s32(pall));
+ }
+}
+
+template <typename Dequantizer, typename Q8>
+inline void mul_mat_qX_Y_q8_Y(int n, Dequantizer& deq, Q8& q8, const DataInfo& info, int nrc_x) {
+ const int nb = n / QK4_1;
+
+ float16x4_t sc16[Q8::nrc_y];
+
+ for (int ix = 0; ix < nrc_x; ++ix) {
+
+ deq.new_row(ix);
+
+ float32x4_t acc[Q8::nrc_y];
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f);
+
+ for (int i = 0; i < nb/4; ++i) {
+ q8.process_scales(i, deq, sc16, acc);
+ sum_4(i, deq, q8, sc16, acc);
+ }
+ for (int i = 4*(nb/4); i < nb; ++i) {
+ q8.process_1_block(i, deq, acc);
+ }
+
+ for (int iy = 0; iy < Q8::nrc_y; ++iy) {
+ info.store(ix, iy, vaddvq_f32(acc[iy]));
+ }
+ }
+}
+
+template <typename Dequantizer, typename Q8>
+inline void mul_mat_qX_Y_q8_Y_1(int n, Dequantizer& deq1, Dequantizer& deq2, Q8& q8, const DataInfo& info, int nrc_x) {
+ const int nb = n / QK4_1;
+
+ float16x4_t sc16[2];
+
+ for (int ix = 0; ix < nrc_x; ++ix) {
+
+ deq1.new_row(ix);
+ deq2.new_row(ix);
+
+ float32x4_t acc[2] = { vdupq_n_f32(0.f), vdupq_n_f32(0.f) };
+
+ for (int i = 0; i < nb/8; ++i) {
+ q8.process_scales(2*i+0, deq1, sc16+0, acc+0);
+ q8.process_scales(2*i+1, deq2, sc16+1, acc+1);
+ sum_4(2*i+0, deq1, q8, sc16+0, acc+0);
+ sum_4(2*i+1, deq2, q8, sc16+1, acc+1);
+ }
+ for (int i = 2*(nb/8); i < nb/4; ++i) {
+ q8.process_scales(i, deq1, sc16, acc);
+ sum_4(i, deq1, q8, sc16, acc);
+ }
+ for (int i = 4*(nb/4); i < nb; ++i) {
+ q8.process_1_block(i, deq1, acc);
+ }
+
+ info.store(ix, 0, vaddvq_f32(vaddq_f32(acc[0], acc[1])));
+ }
+}
+
+template <typename Dequantizer, int nrc_y>
+static void mul_mat_qX_1_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ Q81<nrc_y> q8(info);
+ if constexpr (nrc_y == 1) {
+ Dequantizer deq1(vx, bx), deq2(vx, bx);
+ mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x);
+ } else {
+ Dequantizer deq(vx, bx);
+ mul_mat_qX_Y_q8_Y(n, deq, q8, info, nrc_x);
+ }
+}
+
+template <typename Dequantizer, int nrc_y>
+static void mul_mat_qX_0_q8_0(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ Q80<nrc_y> q8(info);
+ if constexpr (nrc_y == 1) {
+ Dequantizer deq1(vx, bx), deq2(vx, bx);
+ mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x);
+ } else {
+ Dequantizer deq(vx, bx);
+ mul_mat_qX_Y_q8_Y(n, deq, q8, info, nrc_x);
+ }
+}
+
+template <typename Dequantizer>
+static void mul_mat_qX_1_q8_1_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ Dequantizer deq1(vx, bx), deq2(vx, bx);
+ Q81<1> q8(info);
+ mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x);
+}
+
+template <typename Dequantizer>
+static void mul_mat_qX_0_q8_0_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
+ Dequantizer deq1(vx, bx), deq2(vx, bx);
+ Q80<1> q8(info);
+ mul_mat_qX_Y_q8_Y(n, deq1, deq2, q8, info, nrc_x);
+}
+
+template <typename Dequantizer> void MulMat::set_functions(MulMat& m) {
+ if constexpr (std::is_same_v<Dequantizer, DequantizerQ40> || std::is_same_v<Dequantizer, DequantizerQ50>) {
+ m.funcs[0] = mul_mat_qX_0_q8_0<Dequantizer, 1>;
+ m.funcs[1] = mul_mat_qX_0_q8_0<Dequantizer, 2>;
+ m.funcs[2] = mul_mat_qX_0_q8_0<Dequantizer, 3>;
+ m.funcs[3] = mul_mat_qX_0_q8_0<Dequantizer, 4>;
+ m.funcs[4] = mul_mat_qX_0_q8_0<Dequantizer, 5>;
+ m.funcs[5] = mul_mat_qX_0_q8_0<Dequantizer, 6>;
+ m.funcs[6] = mul_mat_qX_0_q8_0<Dequantizer, 7>;
+ m.funcs[7] = mul_mat_qX_0_q8_0<Dequantizer, 8>;
+ }
+ else if constexpr (std::is_same_v<Dequantizer, DequantizerQ41> || std::is_same_v<Dequantizer, DequantizerQ51>) {
+ m.funcs[0] = mul_mat_qX_1_q8_1<Dequantizer, 1>;
+ m.funcs[1] = mul_mat_qX_1_q8_1<Dequantizer, 2>;
+ m.funcs[2] = mul_mat_qX_1_q8_1<Dequantizer, 3>;
+ m.funcs[3] = mul_mat_qX_1_q8_1<Dequantizer, 4>;
+ m.funcs[4] = mul_mat_qX_1_q8_1<Dequantizer, 5>;
+ m.funcs[5] = mul_mat_qX_1_q8_1<Dequantizer, 6>;
+ m.funcs[6] = mul_mat_qX_1_q8_1<Dequantizer, 7>;
+ m.funcs[7] = mul_mat_qX_1_q8_1<Dequantizer, 8>;
+ }
+ else {
+ m.funcs[0] = mul_mat_qX_K_q8_K_T<1, Dequantizer>;
+ m.funcs[1] = mul_mat_qX_K_q8_K_T<2, Dequantizer>;
+ m.funcs[2] = mul_mat_qX_K_q8_K_T<3, Dequantizer>;
+ m.funcs[3] = mul_mat_qX_K_q8_K_T<4, Dequantizer>;
+ m.funcs[4] = mul_mat_qX_K_q8_K_T<5, Dequantizer>;
+ m.funcs[5] = mul_mat_qX_K_q8_K_T<6, Dequantizer>;
+ m.funcs[6] = mul_mat_qX_K_q8_K_T<7, Dequantizer>;
+ m.funcs[7] = mul_mat_qX_K_q8_K_T<8, Dequantizer>;
+ }
+}
+
+bool MulMat::set_mul_mat(int typeA, int ne00, MulMat& m, int& row_size_q8, int /*Ny*/) {
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_K, ne00);
+
+ switch (typeA) {
+ case GGML_TYPE_Q2_K:
+ MulMat::set_functions<DequantizerQ2K>(m);
+ break;
+ case GGML_TYPE_Q3_K:
+ MulMat::set_functions<DequantizerQ3K>(m);
+ break;
+ case GGML_TYPE_Q4_K:
+ MulMat::set_functions<DequantizerQ4K>(m);
+ break;
+ case GGML_TYPE_Q5_K:
+ MulMat::set_functions<DequantizerQ5K>(m);
+ break;
+ case GGML_TYPE_Q6_K:
+ MulMat::set_functions<DequantizerQ6K>(m);
+ break;
+ case GGML_TYPE_IQ4_XS:
+ MulMat::set_functions<DequantizerIQ4XS>(m);
+ break;
+ case GGML_TYPE_Q4_0:
+ MulMat::set_functions<DequantizerQ40>(m);
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
+ break;
+ case GGML_TYPE_Q4_1:
+ MulMat::set_functions<DequantizerQ41>(m);
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_1, ne00);
+ break;
+ case GGML_TYPE_Q5_0:
+ MulMat::set_functions<DequantizerQ50>(m);
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
+ break;
+ case GGML_TYPE_Q5_1:
+ MulMat::set_functions<DequantizerQ51>(m);
+ row_size_q8 = ggml_row_size(GGML_TYPE_Q8_1, ne00);
+ break;
+ default:
+ return false;
+ }
+ return true;
+}
+
+}
+
+#endif // __x86_64__ or __aarch64__
diff --git a/sgemm.cpp b/sgemm.cpp
index bbe263dd..e926ba88 100644
--- a/sgemm.cpp
+++ b/sgemm.cpp
@@ -849,6 +849,11 @@ class tinyBLAS_Q0_AVX {
* @param Ctype is GGML data type of `C`
* @return true if this function was able to service the matmul request
*/
+
+bool iqk_mul_mat(long Nx, long Ny, long ne00, int typeA, const void * A, const void * B,
+ float * C, long stride_C, int ith, int nth);
+
+
bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda, const void *B, int64_t ldb, void *C,
int64_t ldc, int ith, int nth, int task, int Atype, int Btype, int Ctype) {
@@ -861,6 +866,18 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
assert(nth > 0);
assert(ith < nth);
+ if (Btype == GGML_TYPE_Q8_K && Ctype == GGML_TYPE_F32) {
+ if (iqk_mul_mat(m, n, k * QK_K, Atype, A, B, (float *)C, ldc, ith, nth)) {
+ return true;
+ }
+ }
+ if ((Btype == GGML_TYPE_Q8_0 || Btype == GGML_TYPE_Q8_1) && Ctype == GGML_TYPE_F32) {
+ assert(QK8_0 == QK8_1 == QK4_0 == QK4_1 == QK5_0 == QK5_1 == 32);
+ if (iqk_mul_mat(m, n, k * QK8_0, Atype, A, B, (float *)C, ldc, ith, nth)) {
+ return true;
+ }
+ }
+
if (Ctype != GGML_TYPE_F32)
return false;