From 50648de0af67c1ee6bc8590d83bc994422a2547d Mon Sep 17 00:00:00 2001 From: Concedo <39025047+LostRuins@users.noreply.github.com> Date: Thu, 19 Dec 2024 22:57:43 +0800 Subject: [PATCH] rephrase tensor moved warning, cleanup and prepare for ci --- CMakeLists.txt | 5 + cmake/x64-windows-llvm.cmake | 11 - ggml/src/ggml-cpu/amx/amx.cpp | 220 --- ggml/src/ggml-cpu/amx/amx.h | 8 - ggml/src/ggml-cpu/amx/common.h | 91 - ggml/src/ggml-cpu/amx/mmq.cpp | 2511 ------------------------ ggml/src/ggml-cpu/amx/mmq.h | 10 - ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp | 3 +- ggml/src/ggml-cpu/ggml-cpu.c | 2 +- ggml/src/ggml-cpu/ggml-cpu.cpp | 12 +- src/llama.cpp | 15 +- version.txt | 2 +- version_template.txt | 2 +- 13 files changed, 25 insertions(+), 2867 deletions(-) delete mode 100644 cmake/x64-windows-llvm.cmake delete mode 100644 ggml/src/ggml-cpu/amx/amx.cpp delete mode 100644 ggml/src/ggml-cpu/amx/amx.h delete mode 100644 ggml/src/ggml-cpu/amx/common.h delete mode 100644 ggml/src/ggml-cpu/amx/mmq.cpp delete mode 100644 ggml/src/ggml-cpu/amx/mmq.h diff --git a/CMakeLists.txt b/CMakeLists.txt index 774282cb9caeb..43cde58e12c99 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -70,6 +70,11 @@ add_compile_definitions(LOG_DISABLE_LOGS) add_compile_definitions(GGML_USE_CPU) add_compile_definitions(GGML_USE_CPU_AARCH64) +if (MSVC) + add_compile_options("$<$:/utf-8>") + add_compile_options("$<$:/utf-8>") +endif() + file(GLOB GGML_SOURCES_CUDA "ggml/src/ggml-cuda/*.cu") list(APPEND GGML_SOURCES_CUDA "ggml/src/ggml-cuda/ggml-cuda.cu") file(GLOB SRCS "ggml/src/ggml-cuda/template-instances/fattn-wmma*.cu") diff --git a/cmake/x64-windows-llvm.cmake b/cmake/x64-windows-llvm.cmake deleted file mode 100644 index 0603d738fbef0..0000000000000 --- a/cmake/x64-windows-llvm.cmake +++ /dev/null @@ -1,11 +0,0 @@ -set( CMAKE_SYSTEM_NAME Windows ) -set( CMAKE_SYSTEM_PROCESSOR x86_64 ) - -set( CMAKE_C_COMPILER clang ) -set( CMAKE_CXX_COMPILER clang++ ) - -set( arch_c_flags "-march=native" ) - -set( CMAKE_C_FLAGS_INIT "${arch_c_flags}" ) -set( CMAKE_CXX_FLAGS_INIT "${arch_c_flags}" ) - diff --git a/ggml/src/ggml-cpu/amx/amx.cpp b/ggml/src/ggml-cpu/amx/amx.cpp deleted file mode 100644 index 5ec5263ceb4ba..0000000000000 --- a/ggml/src/ggml-cpu/amx/amx.cpp +++ /dev/null @@ -1,220 +0,0 @@ -#include "amx.h" -#include "common.h" -#include "mmq.h" -#include "ggml-backend-impl.h" -#include "ggml-backend.h" -#include "ggml-impl.h" -#include "ggml-cpu.h" -#include "ggml-cpu-traits.h" - -#if defined(__gnu_linux__) -#include -#include -#endif - -#include -#include -#include - -#if defined(__AMX_INT8__) && defined(__AVX512VNNI__) - -// AMX type_trais -namespace ggml::cpu::amx { -class tensor_traits : public ggml::cpu::tensor_traits { - bool work_size(int /* n_threads */, const struct ggml_tensor * op, size_t & size) override { - size = ggml_backend_amx_desired_wsize(op); - return true; - } - - bool compute_forward(struct ggml_compute_params * params, struct ggml_tensor * op) override { - if (op->op == GGML_OP_MUL_MAT) { - ggml_backend_amx_mul_mat(params, op); - return true; - } - return false; - } -}; - -static ggml::cpu::tensor_traits * get_tensor_traits(ggml_backend_buffer_t, struct ggml_tensor *) { - static tensor_traits traits; - return &traits; -} -} // namespace ggml::cpu::amx - -// AMX buffer interface -static void ggml_backend_amx_buffer_free_buffer(ggml_backend_buffer_t buffer) { - free(buffer->context); -} - -static void * ggml_backend_amx_buffer_get_base(ggml_backend_buffer_t buffer) { - return (void *) (buffer->context); -} - -static void ggml_backend_amx_buffer_init_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) { - tensor->extra = (void *) ggml::cpu::amx::get_tensor_traits(buffer, tensor); - - GGML_UNUSED(buffer); -} - -static void ggml_backend_amx_buffer_memset_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, - uint8_t value, size_t offset, size_t size) { - memset((char *) tensor->data + offset, value, size); - - GGML_UNUSED(buffer); -} - -static void ggml_backend_amx_buffer_set_tensor(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor, - const void * data, size_t offset, size_t size) { - if (qtype_has_amx_kernels(tensor->type)) { - GGML_LOG_DEBUG("%s: amx repack tensor %s of type %s\n", __func__, tensor->name, ggml_type_name(tensor->type)); - ggml_backend_amx_convert_weight(tensor, data, offset, size); - } else { - memcpy((char *) tensor->data + offset, data, size); - } - - GGML_UNUSED(buffer); -} - -/* -// need to figure what we need to do with buffer->extra. -static void ggml_backend_amx_buffer_get_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { - GGML_ASSERT(!qtype_has_amx_kernels(tensor->type)); - memcpy(data, (const char *)tensor->data + offset, size); - - GGML_UNUSED(buffer); -} - -static bool ggml_backend_amx_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) { - if (ggml_backend_buffer_is_host(src->buffer)) { - if (qtype_has_amx_kernels(src->type)) { - ggml_backend_amx_convert_weight(dst, src->data, 0, ggml_nbytes(dst)); - } else { - memcpy(dst->data, src->data, ggml_nbytes(src)); - } - return true; - } - return false; - - GGML_UNUSED(buffer); -} -*/ - -static void ggml_backend_amx_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) { - memset(buffer->context, value, buffer->size); -} - -static ggml_backend_buffer_i ggml_backend_amx_buffer_interface = { - /* .free_buffer = */ ggml_backend_amx_buffer_free_buffer, - /* .get_base = */ ggml_backend_amx_buffer_get_base, - /* .init_tensor = */ ggml_backend_amx_buffer_init_tensor, - /* .memset_tensor = */ ggml_backend_amx_buffer_memset_tensor, - /* .set_tensor = */ ggml_backend_amx_buffer_set_tensor, - /* .get_tensor = */ nullptr, - /* .cpy_tensor = */ nullptr, - /* .clear = */ ggml_backend_amx_buffer_clear, - /* .reset = */ nullptr, -}; - -static const char * ggml_backend_amx_buffer_type_get_name(ggml_backend_buffer_type_t buft) { - return "AMX"; - - GGML_UNUSED(buft); -} - -static ggml_backend_buffer_t ggml_backend_amx_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { - void * data = ggml_aligned_malloc(size); - if (data == NULL) { - fprintf(stderr, "%s: failed to allocate buffer of size %zu\n", __func__, size); - return NULL; - } - - return ggml_backend_buffer_init(buft, ggml_backend_amx_buffer_interface, data, size); -} - -static size_t ggml_backend_amx_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) { - return TENSOR_ALIGNMENT; - - GGML_UNUSED(buft); -} - -namespace ggml::cpu::amx { -class extra_buffer_type : ggml::cpu::extra_buffer_type { - bool supports_op(ggml_backend_dev_t, const struct ggml_tensor * op) override { - // handle only 2d gemm for now - auto is_contiguous_2d = [](const struct ggml_tensor * t) { - return ggml_is_contiguous(t) && t->ne[3] == 1 && t->ne[2] == 1; - }; - - if (op->op == GGML_OP_MUL_MAT && is_contiguous_2d(op->src[0]) && // src0 must be contiguous - is_contiguous_2d(op->src[1]) && // src1 must be contiguous - op->src[0]->buffer && op->src[0]->buffer->buft == ggml_backend_amx_buffer_type() && - op->ne[0] % (TILE_N * 2) == 0 && // out_features is 32x - (qtype_has_amx_kernels(op->src[0]->type) || (op->src[0]->type == GGML_TYPE_F16))) { - // src1 must be host buffer - if (op->src[1]->buffer && !ggml_backend_buft_is_host(op->src[1]->buffer->buft)) { - return false; - } - // src1 must be float32 - if (op->src[1]->type == GGML_TYPE_F32) { - return true; - } - } - return false; - } - - ggml::cpu::tensor_traits * get_tensor_traits(const struct ggml_tensor * op) override { - if (op->op == GGML_OP_MUL_MAT && op->src[0]->buffer && - op->src[0]->buffer->buft == ggml_backend_amx_buffer_type()) { - return (ggml::cpu::tensor_traits *) op->src[0]->extra; - } - - return nullptr; - } -}; -} // namespace ggml::cpu::amx - -static size_t ggml_backend_amx_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) { - return ggml_backend_amx_get_alloc_size(tensor); - - GGML_UNUSED(buft); -} - -#define ARCH_GET_XCOMP_PERM 0x1022 -#define ARCH_REQ_XCOMP_PERM 0x1023 -#define XFEATURE_XTILECFG 17 -#define XFEATURE_XTILEDATA 18 - -static bool ggml_amx_init() { -#if defined(__gnu_linux__) - if (syscall(SYS_arch_prctl, ARCH_REQ_XCOMP_PERM, XFEATURE_XTILEDATA)) { - fprintf(stderr, "AMX is not ready to be used!\n"); - return false; - } - return true; -#elif defined(_WIN32) - return true; -#endif -} - -ggml_backend_buffer_type_t ggml_backend_amx_buffer_type() { - static struct ggml_backend_buffer_type ggml_backend_buffer_type_amx = { - /* .iface = */ { - /* .get_name = */ ggml_backend_amx_buffer_type_get_name, - /* .alloc_buffer = */ ggml_backend_amx_buffer_type_alloc_buffer, - /* .get_alignment = */ ggml_backend_amx_buffer_type_get_alignment, - /* .get_max_size = */ nullptr, // defaults to SIZE_MAX - /* .get_alloc_size = */ ggml_backend_amx_buffer_type_get_alloc_size, - /* .is_host = */ nullptr, - }, - /* .device = */ ggml_backend_reg_dev_get(ggml_backend_cpu_reg(), 0), - /* .context = */ new ggml::cpu::amx::extra_buffer_type(), - }; - - if (!ggml_amx_init()) { - return nullptr; - } - - return &ggml_backend_buffer_type_amx; -} - -#endif // defined(__AMX_INT8__) && defined(__AVX512VNNI__) diff --git a/ggml/src/ggml-cpu/amx/amx.h b/ggml/src/ggml-cpu/amx/amx.h deleted file mode 100644 index 5b65d76bdc89c..0000000000000 --- a/ggml/src/ggml-cpu/amx/amx.h +++ /dev/null @@ -1,8 +0,0 @@ -#include "ggml-backend.h" -#include "ggml-cpu-impl.h" - -// GGML internal header - -#if defined(__AMX_INT8__) && defined(__AVX512VNNI__) -ggml_backend_buffer_type_t ggml_backend_amx_buffer_type(void); -#endif diff --git a/ggml/src/ggml-cpu/amx/common.h b/ggml/src/ggml-cpu/amx/common.h deleted file mode 100644 index f392e898518a7..0000000000000 --- a/ggml/src/ggml-cpu/amx/common.h +++ /dev/null @@ -1,91 +0,0 @@ -#pragma once - -#include "ggml.h" -#include "ggml-cpu-impl.h" - -#include -#include -#include - -#if defined(GGML_USE_OPENMP) -#include -#endif - -#define TILE_M 16 -#define TILE_N 16 -#define TILE_K 32 -#define VNNI_BLK 4 - -#define AMX_BLK_SIZE 32 - -#define TMM0 0 -#define TMM1 1 -#define TMM2 2 -#define TMM3 3 -#define TMM4 4 -#define TMM5 5 -#define TMM6 6 -#define TMM7 7 - -// parallel routines -template ::value, int>::type = 0> -inline T div_up(T x, T y) { return (x + y - 1) / y; } - -template -inline void balance211(T n, T nth, T ith, T& n_start, T& n_end) { -#if 0 - // onednn partition pattern - T& n_my = n_end; - if (nth <= 1 || n == 0) { - n_start = 0; - n_my = n; - } else { - T n1 = div_up(n, nth); - T n2 = n1 - 1; - T T1 = n - n2 * nth; - n_my = ith < T1 ? n1 : n2; - n_start = ith <= T1 ? ith*n1 : T1 * n1 + (ith - T1) * n2; - } - n_end += n_start; -#else - // pytorch aten partition pattern - T n_my = div_up(n, nth); - n_start = ith * n_my; - n_end = std::min(n_start + n_my, n); -#endif -} - -template -inline void parallel_for(int n, const func_t& f) { -#if defined(GGML_USE_OPENMP) -#pragma omp parallel -{ - int nth = omp_get_num_threads(); - int ith = omp_get_thread_num(); - int tbegin, tend; - balance211(n, nth, ith, tbegin, tend); - f(tbegin, tend); -} -#else - f(0, n); -#endif -} - -template -inline void parallel_for_ggml(const ggml_compute_params * params, int n, const func_t & f) { - int tbegin, tend; - balance211(n, params->nth, params->ith, tbegin, tend); - f(tbegin, tend); -} - -// quantized types that have AMX support -inline bool qtype_has_amx_kernels(const enum ggml_type type) { - // TODO: fix padding for vnni format - return (type == GGML_TYPE_Q4_0) || - (type == GGML_TYPE_Q4_1) || - (type == GGML_TYPE_Q8_0) || - (type == GGML_TYPE_Q4_K) || - (type == GGML_TYPE_Q5_K) || - (type == GGML_TYPE_Q6_K) || - (type == GGML_TYPE_IQ4_XS); -} diff --git a/ggml/src/ggml-cpu/amx/mmq.cpp b/ggml/src/ggml-cpu/amx/mmq.cpp deleted file mode 100644 index 0ea91596bc7e2..0000000000000 --- a/ggml/src/ggml-cpu/amx/mmq.cpp +++ /dev/null @@ -1,2511 +0,0 @@ - -#if defined(__GNUC__) -#pragma GCC diagnostic ignored "-Wpedantic" -#pragma GCC diagnostic ignored "-Wunused-local-typedefs" -#endif - -#include "amx.h" -#include "mmq.h" -#include "ggml-impl.h" -#include "ggml-cpu-impl.h" -#include "ggml-cpu-quants.h" -#include "ggml-quants.h" -#include -#include - -#if defined(__gnu_linux__) -#include -#include -#endif - -#if (defined(_WIN32) || defined(_WIN64)) -#define RESTRICT __restrict -#else -#define RESTRICT __restrict__ -#endif - -#if (defined(_WIN32) || defined(_WIN64)) -#define ALWAYS_INLINE __forceinline -#elif __has_attribute(always_inline) || defined(__GNUC__) -#define ALWAYS_INLINE __attribute__((__always_inline__)) inline -#else -#define ALWAYS_INLINE inline -#endif - -#if defined(__AMX_INT8__) && defined(__AVX512VNNI__) - -namespace { - -// Forced unrolling -template -struct Unroll { - template - ALWAYS_INLINE void operator()(const Func& f, Args... args) const { - Unroll{}(f, args...); - f(std::integral_constant{}, args...); - } -}; - -template <> -struct Unroll<1> { - template - ALWAYS_INLINE void operator()(const Func& f, Args... args) const { - f(std::integral_constant{}, args...); - } -}; - -// type traits -template struct PackedTypes {}; -template <> struct PackedTypes { using type = int8_t; }; -template <> struct PackedTypes { using type = uint8_t; }; -template <> struct PackedTypes { using type = int8_t; }; -template using packed_B_type = typename PackedTypes::type; - -template -struct do_compensate : std::integral_constant::value> {}; - -template -struct do_unpack : std::integral_constant::value || - std::is_same::value> {}; - -template -struct is_type_qkk : std::integral_constant::value || - std::is_same::value || - std::is_same::value || - std::is_same::value> {}; - -#define GGML_DISPATCH_FLOATING_TYPES(TYPE, ...) \ - [&] { \ - switch (TYPE) { \ - case GGML_TYPE_F16: { \ - using type = ggml_fp16_t; \ - constexpr int blck_size = 16; \ - return __VA_ARGS__(); \ - } \ - case GGML_TYPE_BF16: { \ - using type = ggml_bf16_t; \ - constexpr int blck_size = 32; \ - return __VA_ARGS__(); \ - } \ - default: \ - fprintf(stderr, "Unsupported floating data type\n"); \ - } \ - }() - -#define GGML_DISPATCH_QTYPES(QT, ...) \ - [&] { \ - switch (QT) { \ - case GGML_TYPE_Q4_0: { \ - using type = block_q4_0; \ - using vec_dot_type = block_q8_0; \ - constexpr int blck_size = QK4_0; \ - return __VA_ARGS__(); \ - } \ - case GGML_TYPE_Q4_1: { \ - using type = block_q4_1; \ - using vec_dot_type = block_q8_1; \ - constexpr int blck_size = QK4_1; \ - return __VA_ARGS__(); \ - } \ - case GGML_TYPE_Q8_0: { \ - using type = block_q8_0; \ - using vec_dot_type = block_q8_0; \ - constexpr int blck_size = QK8_0; \ - return __VA_ARGS__(); \ - } \ - case GGML_TYPE_Q4_K: { \ - using type = block_q4_K; \ - using vec_dot_type = block_q8_K; \ - constexpr int blck_size = QK_K; \ - return __VA_ARGS__(); \ - } \ - case GGML_TYPE_Q5_K: { \ - using type = block_q5_K; \ - using vec_dot_type = block_q8_K; \ - constexpr int blck_size = QK_K; \ - return __VA_ARGS__(); \ - } \ - case GGML_TYPE_Q6_K: { \ - using type = block_q6_K; \ - using vec_dot_type = block_q8_K; \ - constexpr int blck_size = QK_K; \ - return __VA_ARGS__(); \ - } \ - case GGML_TYPE_IQ4_XS: { \ - using type = block_iq4_xs; \ - using vec_dot_type = block_q8_K; \ - constexpr int blck_size = QK_K; \ - return __VA_ARGS__(); \ - } \ - default: \ - fprintf(stderr, "Unsupported quantized data type: %d\n", int(TYPE)); \ - } \ - }() - -#define GGML_DISPATCH_BOOL(BOOL_V, BOOL_NAME, ...) \ - [&] { \ - if (BOOL_V) { \ - constexpr bool BOOL_NAME = true; \ - return __VA_ARGS__(); \ - } else { \ - constexpr bool BOOL_NAME = false; \ - return __VA_ARGS__(); \ - } \ - }() - -// define amx tile config data structure -struct tile_config_t{ - uint8_t palette_id = 0; - uint8_t start_row = 0; - uint8_t reserved_0[14] = {0}; - uint16_t colsb[16] = {0}; - uint8_t rows[16] = {0}; -}; - -// Notes: amx tile config -// -// Typically, TMUL calculates A and B of size 16 x 64 containing INT8 values, -// and accumulate the result to a 16 x 16 matrix C containing INT32 values, -// -// As many GGUF quantized types as `block_size` of 32, so a 16-16-32 config is used -// instead of the normally used 16-16-64 config. -// -// Block A: {16, 32}, dtype = int8_t -// Block B: {16, 32}, dtype = uint8_t/int8_t -// Block C: {16, 16}, dtype = int32_t -// -// Block B needs to be prepacked to vnni format before feeding into TMUL: -// packed_B: from {n, k} to {k/vnni_blk, n, vnni_blck}, viewed in 2d, we get {8, 64} -// -// Therefore, we get tileconfig: -// A B C -// rows 16 8 16 -// colsb 32 64 16 -// -// For tile distribution, follow a 2-2-4 pattern, e.g. A used TMM2-TMM3, B used TMM0-TMM1, -// C used TMM4-TMM7: -// B TMM0 B TMM1 -// A TMM2 C TMM4 C TMM6 -// A TMM3 C TMM5 C TMM7 -// -// Each `amx` kernel handles 4 blocks at a time: 2MB * 2NB, when m < 2 * BLOCK_M, unpack A -// will be needed. -// -// Here another commonly used pattern 1-3-3 is skipped, as it is mostly used when m <=16; -// and the sinlge batch gemm (m=1) has a special fast path with `avx512-vnni`. -// -// ref: https://www.intel.com/content/www/us/en/developer/articles/code-sample/ -// advanced-matrix-extensions-intrinsics-functions.html -// - -#define TC_CONFIG_TILE(i, r, cb) tc.rows[i] = r; tc.colsb[i] = cb -void ggml_tile_config_init(void) { - static thread_local bool is_first_time = true; - - if (!is_first_time) { - return; - } - - static thread_local tile_config_t tc; - tile_config_t current_tc; - _tile_storeconfig(¤t_tc); - - // load only when config changes - if (tc.palette_id == 0 || (memcmp(¤t_tc.colsb, &tc.colsb, sizeof(uint16_t) * 8) != 0 && - memcmp(¤t_tc.rows, &tc.rows, sizeof(uint8_t) * 8) != 0)) { - tc.palette_id = 1; - tc.start_row = 0; - TC_CONFIG_TILE(TMM0, 8, 64); - TC_CONFIG_TILE(TMM1, 8, 64); - TC_CONFIG_TILE(TMM2, 16, 32); - TC_CONFIG_TILE(TMM3, 16, 32); - TC_CONFIG_TILE(TMM4, 16, 64); - TC_CONFIG_TILE(TMM5, 16, 64); - TC_CONFIG_TILE(TMM6, 16, 64); - TC_CONFIG_TILE(TMM7, 16, 64); - _tile_loadconfig(&tc); - } - - is_first_time = false; -} - -// we need an extra 16 * 4B (TILE_N * int32_t) for each NB/KB block for compensation. -// See the notes `s8s8 igemm compensation in avx512-vnni` for detail. -template -int get_tile_size() { - int tile_size = TILE_N * sizeof(TB); - if (do_compensate::value) { - tile_size += TILE_N * sizeof(int32_t); - } - if (std::is_same::value || - std::is_same::value) { - tile_size += TILE_N * 4; - } - if (std::is_same::value) { - tile_size += TILE_N * 2; - } - return tile_size; -} - -template -int get_row_size(int K) { - int KB = K / BLOCK_K; - int row_size = KB * sizeof(TB); - if (do_compensate::value) { - row_size += KB * sizeof(int32_t); - } - if (std::is_same::value || - std::is_same::value) { - row_size += KB * 4; - } - if (std::is_same::value) { - row_size += KB * 2; - } - return row_size; -} - -// vectorized dtype conversion -inline float FP16_TO_FP32(ggml_half val) { - __m256i v = _mm256_setr_epi16( - val, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); - __m512 o = _mm512_cvtph_ps(v); - return _mm512_cvtss_f32(o); -} - -inline __m512 FP16_TO_FP32_VEC(ggml_half val) { - __m256i v = _mm256_set1_epi16(val); - return _mm512_cvtph_ps(v); -} - -// horizontal reduce -inline float _mm512_reduce_max_ps(const __m512 x) { - __m512 v = x; - __m512 v1 = _mm512_shuffle_f32x4(v, v, 0x4E); - v = _mm512_max_ps(v, v1); - v1 = _mm512_shuffle_f32x4(v, v, 0xB1); - v = _mm512_max_ps(v, v1); - v1 = _mm512_shuffle_ps(v, v, 0x4E); - v = _mm512_max_ps(v, v1); - v1 = _mm512_shuffle_ps(v, v, 0xB1); - v = _mm512_max_ps(v, v1); - return _mm512_cvtss_f32(v); -} - -// transpose utils -#define SHUFFLE_EPI32(a, b, mask) \ - _mm256_castps_si256(_mm256_shuffle_ps(_mm256_castsi256_ps(a), _mm256_castsi256_ps(b), mask)) -inline void transpose_8x8_32bit(__m256i * v, __m256i * v1) { - // unpacking and 32-bit elements - v1[0] = _mm256_unpacklo_epi32(v[0], v[1]); - v1[1] = _mm256_unpackhi_epi32(v[0], v[1]); - v1[2] = _mm256_unpacklo_epi32(v[2], v[3]); - v1[3] = _mm256_unpackhi_epi32(v[2], v[3]); - v1[4] = _mm256_unpacklo_epi32(v[4], v[5]); - v1[5] = _mm256_unpackhi_epi32(v[4], v[5]); - v1[6] = _mm256_unpacklo_epi32(v[6], v[7]); - v1[7] = _mm256_unpackhi_epi32(v[6], v[7]); - - // shuffling the 32-bit elements - v[0] = SHUFFLE_EPI32(v1[0], v1[2], 0x44); - v[1] = SHUFFLE_EPI32(v1[0], v1[2], 0xee); - v[2] = SHUFFLE_EPI32(v1[4], v1[6], 0x44); - v[3] = SHUFFLE_EPI32(v1[4], v1[6], 0xee); - v[4] = SHUFFLE_EPI32(v1[1], v1[3], 0x44); - v[5] = SHUFFLE_EPI32(v1[1], v1[3], 0xee); - v[6] = SHUFFLE_EPI32(v1[5], v1[7], 0x44); - v[7] = SHUFFLE_EPI32(v1[5], v1[7], 0xee); - - // shuffling 128-bit elements - v1[0] = _mm256_permute2f128_si256(v[2], v[0], 0x02); - v1[1] = _mm256_permute2f128_si256(v[3], v[1], 0x02); - v1[2] = _mm256_permute2f128_si256(v[6], v[4], 0x02); - v1[3] = _mm256_permute2f128_si256(v[7], v[5], 0x02); - v1[4] = _mm256_permute2f128_si256(v[2], v[0], 0x13); - v1[5] = _mm256_permute2f128_si256(v[3], v[1], 0x13); - v1[6] = _mm256_permute2f128_si256(v[6], v[4], 0x13); - v1[7] = _mm256_permute2f128_si256(v[7], v[5], 0x13); -} - -inline void transpose_16x4_32bit(__m512i * r, __m512i * d) { - - static const __m512i index1 = _mm512_set_epi32( - 0x0f, 0x0b, 0x07, 0x03, - 0x0e, 0x0a, 0x06, 0x02, - 0x0d, 0x09, 0x05, 0x01, - 0x0c, 0x08, 0x04, 0x00); - - d[0] = _mm512_permutexvar_epi32(index1, r[0]); - d[1] = _mm512_permutexvar_epi32(index1, r[1]); - d[2] = _mm512_permutexvar_epi32(index1, r[2]); - d[3] = _mm512_permutexvar_epi32(index1, r[3]); - - r[0] = _mm512_shuffle_i32x4(d[0], d[1], 0x44); - r[1] = _mm512_shuffle_i32x4(d[0], d[1], 0xee); - r[2] = _mm512_shuffle_i32x4(d[2], d[3], 0x44); - r[3] = _mm512_shuffle_i32x4(d[2], d[3], 0xee); - - d[0] = _mm512_shuffle_i32x4(r[0], r[2], 0x88); - d[1] = _mm512_shuffle_i32x4(r[0], r[2], 0xdd); - d[2] = _mm512_shuffle_i32x4(r[1], r[3], 0x88); - d[3] = _mm512_shuffle_i32x4(r[1], r[3], 0xdd); -} - -inline void transpose_16x16_32bit(__m512i * v) { - __m512i v1[16]; - v1[0] = _mm512_unpacklo_epi32(v[0], v[1]); - v1[1] = _mm512_unpackhi_epi32(v[0], v[1]); - v1[2] = _mm512_unpacklo_epi32(v[2], v[3]); - v1[3] = _mm512_unpackhi_epi32(v[2], v[3]); - v1[4] = _mm512_unpacklo_epi32(v[4], v[5]); - v1[5] = _mm512_unpackhi_epi32(v[4], v[5]); - v1[6] = _mm512_unpacklo_epi32(v[6], v[7]); - v1[7] = _mm512_unpackhi_epi32(v[6], v[7]); - v1[8] = _mm512_unpacklo_epi32(v[8], v[9]); - v1[9] = _mm512_unpackhi_epi32(v[8], v[9]); - v1[10] = _mm512_unpacklo_epi32(v[10], v[11]); - v1[11] = _mm512_unpackhi_epi32(v[10], v[11]); - v1[12] = _mm512_unpacklo_epi32(v[12], v[13]); - v1[13] = _mm512_unpackhi_epi32(v[12], v[13]); - v1[14] = _mm512_unpacklo_epi32(v[14], v[15]); - v1[15] = _mm512_unpackhi_epi32(v[14], v[15]); - - v[0] = _mm512_unpacklo_epi64(v1[0], v1[2]); - v[1] = _mm512_unpackhi_epi64(v1[0], v1[2]); - v[2] = _mm512_unpacklo_epi64(v1[1], v1[3]); - v[3] = _mm512_unpackhi_epi64(v1[1], v1[3]); - v[4] = _mm512_unpacklo_epi64(v1[4], v1[6]); - v[5] = _mm512_unpackhi_epi64(v1[4], v1[6]); - v[6] = _mm512_unpacklo_epi64(v1[5], v1[7]); - v[7] = _mm512_unpackhi_epi64(v1[5], v1[7]); - v[8] = _mm512_unpacklo_epi64(v1[8], v1[10]); - v[9] = _mm512_unpackhi_epi64(v1[8], v1[10]); - v[10] = _mm512_unpacklo_epi64(v1[9], v1[11]); - v[11] = _mm512_unpackhi_epi64(v1[9], v1[11]); - v[12] = _mm512_unpacklo_epi64(v1[12], v1[14]); - v[13] = _mm512_unpackhi_epi64(v1[12], v1[14]); - v[14] = _mm512_unpacklo_epi64(v1[13], v1[15]); - v[15] = _mm512_unpackhi_epi64(v1[13], v1[15]); - - v1[0] = _mm512_shuffle_i32x4(v[0], v[4], 0x88); - v1[1] = _mm512_shuffle_i32x4(v[1], v[5], 0x88); - v1[2] = _mm512_shuffle_i32x4(v[2], v[6], 0x88); - v1[3] = _mm512_shuffle_i32x4(v[3], v[7], 0x88); - v1[4] = _mm512_shuffle_i32x4(v[0], v[4], 0xdd); - v1[5] = _mm512_shuffle_i32x4(v[1], v[5], 0xdd); - v1[6] = _mm512_shuffle_i32x4(v[2], v[6], 0xdd); - v1[7] = _mm512_shuffle_i32x4(v[3], v[7], 0xdd); - v1[8] = _mm512_shuffle_i32x4(v[8], v[12], 0x88); - v1[9] = _mm512_shuffle_i32x4(v[9], v[13], 0x88); - v1[10] = _mm512_shuffle_i32x4(v[10], v[14], 0x88); - v1[11] = _mm512_shuffle_i32x4(v[11], v[15], 0x88); - v1[12] = _mm512_shuffle_i32x4(v[8], v[12], 0xdd); - v1[13] = _mm512_shuffle_i32x4(v[9], v[13], 0xdd); - v1[14] = _mm512_shuffle_i32x4(v[10], v[14], 0xdd); - v1[15] = _mm512_shuffle_i32x4(v[11], v[15], 0xdd); - - v[0] = _mm512_shuffle_i32x4(v1[0], v1[8], 0x88); - v[1] = _mm512_shuffle_i32x4(v1[1], v1[9], 0x88); - v[2] = _mm512_shuffle_i32x4(v1[2], v1[10], 0x88); - v[3] = _mm512_shuffle_i32x4(v1[3], v1[11], 0x88); - v[4] = _mm512_shuffle_i32x4(v1[4], v1[12], 0x88); - v[5] = _mm512_shuffle_i32x4(v1[5], v1[13], 0x88); - v[6] = _mm512_shuffle_i32x4(v1[6], v1[14], 0x88); - v[7] = _mm512_shuffle_i32x4(v1[7], v1[15], 0x88); - v[8] = _mm512_shuffle_i32x4(v1[0], v1[8], 0xdd); - v[9] = _mm512_shuffle_i32x4(v1[1], v1[9], 0xdd); - v[10] = _mm512_shuffle_i32x4(v1[2], v1[10], 0xdd); - v[11] = _mm512_shuffle_i32x4(v1[3], v1[11], 0xdd); - v[12] = _mm512_shuffle_i32x4(v1[4], v1[12], 0xdd); - v[13] = _mm512_shuffle_i32x4(v1[5], v1[13], 0xdd); - v[14] = _mm512_shuffle_i32x4(v1[6], v1[14], 0xdd); - v[15] = _mm512_shuffle_i32x4(v1[7], v1[15], 0xdd); -} - -void quantize_row_q8_K_vnni(const float * RESTRICT x, void * RESTRICT vy, int64_t k) { - assert(k % QK_K == 0); - const int KB = k / QK_K; - constexpr int kVecs = QK_K / 16; - - block_q8_K * y = reinterpret_cast(vy); - - // hold 16 float vecs from x - __m512 v[kVecs]; - - // hold the quants vecs - __m512i vq[kVecs / 4]; - - // hold the packed quants vecs - __m512i vq_packed[kVecs / 4]; - - const __m512 signBit = _mm512_set1_ps(-0.f); - - for (int i = 0; i < KB; ++i) { - // Compute max(abs(e)) for the block - __m512 vamax = _mm512_set1_ps(0.f); - for (int j = 0; j < kVecs; ++j) { - v[j] = _mm512_loadu_ps(x); x += 16; - vamax = _mm512_max_ps(vamax, _mm512_andnot_ps(signBit, v[j])); - } - const float amax = _mm512_reduce_max_ps(vamax); - - // Quantize these floats - const float iscale = 127.f / amax; - y[i].d = GGML_FP32_TO_FP16(1 / iscale); - const float id = ( amax != 0.0f ) ? iscale : 0.f; - const __m512 vscale = _mm512_set1_ps(id); - - // Apply multiplier and round to nearest integer - for (int j = 0; j < kVecs; ++j) { - v[j] = _mm512_mul_ps(v[j], vscale); - v[j] = _mm512_roundscale_ps(v[j], (_MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC)); - } - - // Pack to epi8 vecs - for (int j = 0; j < kVecs / 4; ++j) { - __m128i q8_0 = _mm512_cvtepi32_epi8(_mm512_cvtps_epi32(v[j * 4 + 0])); - __m128i q8_1 = _mm512_cvtepi32_epi8(_mm512_cvtps_epi32(v[j * 4 + 1])); - __m128i q8_2 = _mm512_cvtepi32_epi8(_mm512_cvtps_epi32(v[j * 4 + 2])); - __m128i q8_3 = _mm512_cvtepi32_epi8(_mm512_cvtps_epi32(v[j * 4 + 3])); - - __m256i q8_01 = _mm256_insertf128_si256(_mm256_castsi128_si256(q8_0), (q8_1), 1); - __m256i q8_23 = _mm256_insertf128_si256(_mm256_castsi128_si256(q8_2), (q8_3), 1); - - vq[j] = _mm512_inserti32x8(_mm512_castsi256_si512(q8_01), q8_23, 1); - _mm512_storeu_si512((__m512i *)(y[i].qs + j * 64), vq[j]); - } - - // Compute the bsums with vnni - transpose_16x4_32bit(vq, vq_packed); - - const __m512i one = _mm512_set1_epi8(1); - __m512i sum = _mm512_setzero_si512(); - for (int k = 0; k < 4; ++k) { - sum = _mm512_dpbusd_epi32(sum, one, vq_packed[k]); - } - _mm256_storeu_si256((__m256i *)(y[i].bsums), _mm512_cvtepi32_epi16(sum)); - } -} - -// quantize A from float to `vec_dot_type` -template -inline void from_float(const float * x, char * vy, int64_t k); - -template <> -inline void from_float(const float * x, char * vy, int64_t k) { - quantize_row_q8_0(x, (block_q8_0 *)vy, k); -} - -template <> -inline void from_float(const float * x, char * vy, int64_t k) { - quantize_row_q8_1(x, (block_q8_1 *)vy, k); -} - -template <> -inline void from_float(const float * x, char * vy, int64_t k) { -#if 1 - // TODO: this is reference impl! - quantize_row_q8_K_ref(x, (block_q8_K *)vy, k); -#else - quantize_row_q8_K_vnni(x, vy, k); -#endif -} - -// load A from memory to array when nrows can not fill in whole tile -void unpack_A(int8_t * RESTRICT tile, const block_q8_0 * RESTRICT A, int lda, int nr) { - assert(nr != TILE_M); - for (int m = 0; m < nr; ++m) { - const __m256i v = _mm256_loadu_si256((const __m256i *)(A[m * lda].qs)); - _mm256_storeu_si256((__m256i *)(tile + m * TILE_K), v); - } -} - -void unpack_A(int8_t * RESTRICT tile, const block_q8_1 * RESTRICT A, int lda, int nr) { - assert(nr != TILE_M); - for (int m = 0; m < nr; ++m) { - const __m256i v = _mm256_loadu_si256((const __m256i *)(A[m * lda].qs)); - _mm256_storeu_si256((__m256i *)(tile + m * TILE_K), v); - } -} - -template -void unpack_A(int8_t * RESTRICT tile, const block_q8_K * RESTRICT A, int lda, int k, int nr) { - assert(nr <= TILE_M); - for (int m = 0; m < nr; ++m) { - const __m256i v = _mm256_loadu_si256((const __m256i *)(A[m * lda].qs + k * 32)); - _mm256_storeu_si256((__m256i *)(tile + m * TILE_K), v); - } -} - -template <> -void unpack_A(int8_t * RESTRICT tile, const block_q8_K * RESTRICT A, int lda, int k, int nr) { - assert(nr <= TILE_M); - // zero padding k from 16 to 32, so that we don't have to re-config amx - const __m128i zero = _mm_setzero_si128(); - for (int m = 0; m < nr; ++m) { - const __m128i v = _mm_loadu_si128((const __m128i *)(A[m * lda].qs + k * 16)); - const __m256i r = _mm256_insertf128_si256(_mm256_castsi128_si256(v), zero, 1); - _mm256_storeu_si256((__m256i *)(tile + m * TILE_K), r); - } -} - -#define MM256_SET_M128I(a, b) _mm256_insertf128_si256(_mm256_castsi128_si256(b), (a), 1) -inline __m256i bytes_from_nibbles_32(const uint8_t * rsi) { - const __m128i tmp = _mm_loadu_si128((const __m128i *)rsi); - const __m256i bytes = MM256_SET_M128I(_mm_srli_epi16(tmp, 4), tmp); - const __m256i lowMask = _mm256_set1_epi8(0xF); - return _mm256_and_si256(lowMask, bytes); -} - -// used for block_q4_K -inline __m512i bytes_from_nibbles_64(const uint8_t * rsi) { - const __m256i tmp = _mm256_loadu_si256((const __m256i *)rsi); - const __m256i lowMask = _mm256_set1_epi8(0xF); - const __m256i q4l = _mm256_and_si256(tmp, lowMask); - const __m256i q4h = _mm256_and_si256(_mm256_srli_epi16(tmp, 4), lowMask); - return _mm512_inserti32x8(_mm512_castsi256_si512(q4l), q4h, 1); -} - -// used for block_q5_K -inline __m512i bytes_from_nibbles_64(const uint8_t * qs, const uint8_t * qh, int k) { - const __m256i lowMask = _mm256_set1_epi8(0xF); - __m256i hmask = _mm256_set1_epi8(1); - hmask = _mm256_slli_epi16(hmask, k); - - const __m256i q5bits = _mm256_loadu_si256((const __m256i *)qs); - const __m256i hbits = _mm256_loadu_si256((const __m256i *)qh); - - const __m256i q5l_0 = _mm256_and_si256(q5bits, lowMask); - const __m256i q5h_0 = _mm256_slli_epi16(_mm256_srli_epi16(_mm256_and_si256(hbits, hmask), k + 0), 4); - const __m256i q5_0 = _mm256_add_epi8(q5l_0, q5h_0); - hmask = _mm256_slli_epi16(hmask, 1); - - const __m256i q5l_1 = _mm256_and_si256(_mm256_srli_epi16(q5bits, 4), lowMask); - const __m256i q5h_1 = _mm256_slli_epi16(_mm256_srli_epi16(_mm256_and_si256(hbits, hmask), k + 1), 4); - const __m256i q5_1 = _mm256_add_epi8(q5l_1, q5h_1); - - return _mm512_inserti32x8(_mm512_castsi256_si512(q5_0), q5_1, 1); -} - -// used for block_q6_K -inline void bytes_from_nibbles_128(__m512i& r0, __m512i& r1, const uint8_t * qs, const uint8_t * qh) { - const __m256i m4 = _mm256_set1_epi8(0xF); - const __m256i m2 = _mm256_set1_epi8(0x3); - - const __m256i q6bits1 = _mm256_loadu_si256((const __m256i *)qs); - const __m256i q6bits2 = _mm256_loadu_si256((const __m256i *)(qs + 32)); - const __m256i q6bitsH = _mm256_loadu_si256((const __m256i *)qh); - - const __m256i q6h_0 = _mm256_slli_epi16(_mm256_and_si256( q6bitsH, m2), 4); - const __m256i q6h_1 = _mm256_slli_epi16(_mm256_and_si256(_mm256_srli_epi16(q6bitsH, 2), m2), 4); - const __m256i q6h_2 = _mm256_slli_epi16(_mm256_and_si256(_mm256_srli_epi16(q6bitsH, 4), m2), 4); - const __m256i q6h_3 = _mm256_slli_epi16(_mm256_and_si256(_mm256_srli_epi16(q6bitsH, 6), m2), 4); - - const __m256i q6_0 = _mm256_or_si256(_mm256_and_si256(q6bits1, m4), q6h_0); - const __m256i q6_1 = _mm256_or_si256(_mm256_and_si256(q6bits2, m4), q6h_1); - const __m256i q6_2 = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(q6bits1, 4), m4), q6h_2); - const __m256i q6_3 = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(q6bits2, 4), m4), q6h_3); - - r0 = _mm512_inserti32x8(_mm512_castsi256_si512(q6_0), q6_1, 1); - r1 = _mm512_inserti32x8(_mm512_castsi256_si512(q6_2), q6_3, 1); -} - -inline __m512i packNibbles(__m512i r0, __m512i r1) { - return _mm512_or_si512(r0, _mm512_slli_epi16(r1, 4)); -} - -template -inline void pack_qs(void * RESTRICT packed_B, const TB * RESTRICT B, int KB) { - int8_t tmp[8 * 64]; - __m256i v[8], v2[8]; - for (int n = 0; n < 8; ++n) { - v[n] = bytes_from_nibbles_32(B[n * KB].qs); - } - transpose_8x8_32bit(v, v2); - for (int n = 0; n < 8; ++n) { - _mm256_storeu_si256((__m256i *)(tmp + n * 64), v2[n]); - } - for (int n = 0; n < 8; ++n) { - v[n] = bytes_from_nibbles_32(B[(n + 8) * KB].qs); - } - transpose_8x8_32bit(v, v2); - for (int n = 0; n < 8; ++n) { - _mm256_storeu_si256((__m256i *)(tmp + n * 64 + 32), v2[n]); - } - - // pack again with 128 to fully utilize vector length - for (int n = 0; n < 8; n += 2) { - __m512i r0 = _mm512_loadu_si512((const __m512i *)(tmp + n * 64)); - __m512i r1 = _mm512_loadu_si512((const __m512i *)(tmp + n * 64 + 64)); - __m512i r1r0 = packNibbles(r0, r1); - _mm512_storeu_si512((__m512i *)((char *)packed_B + n * 32), r1r0); - } -} - -template <> -inline void pack_qs(void * RESTRICT packed_B, const block_q8_0 * RESTRICT B, int KB) { - __m256i v[8], v2[8]; - for (int n = 0; n < 8; ++n) { - v[n] = _mm256_loadu_si256((const __m256i *)(B[n * KB].qs)); - } - transpose_8x8_32bit(v, v2); - for (int n = 0; n < 8; ++n) { - _mm256_storeu_si256((__m256i *)((char *)packed_B + n * 64), v2[n]); - } - for (int n = 0; n < 8; ++n) { - v[n] = _mm256_loadu_si256((const __m256i *)(B[(n + 8) * KB].qs)); - } - transpose_8x8_32bit(v, v2); - for (int n = 0; n < 8; ++n) { - _mm256_storeu_si256((__m256i *)((char *)packed_B + n * 64 + 32), v2[n]); - } -} - -template <> -inline void pack_qs(void * RESTRICT packed_B, const block_q4_K * RESTRICT B, int KB) { - __m512i v[16]; - // QK_K 256 with 8 groups, handle 2 groups at a time - char * pb = (char *)packed_B; - for (int k = 0; k < QK_K / 64; ++k) { - // pack 2 groups { n, g, k} to {g, k/4, 4n} - // e.g. {16, 2, 32} to {2, 8, 64} - for (int n = 0; n < TILE_N; ++n) { - v[n] = bytes_from_nibbles_64(B[n * KB].qs + k * 32); - } - - transpose_16x16_32bit(v); - - // pack again with 128 to fully utilize vector length - for (int n = 0; n < TILE_N; n += 2) { - _mm512_storeu_si512((__m512i *)pb, packNibbles(v[n], v[n + 1])); - pb += 64; - } - } -} - -template <> -inline void pack_qs(void * RESTRICT packed_B, const block_q5_K * RESTRICT B, int KB) { - __m512i v[16]; - const __m512i lowMask = _mm512_set1_epi8(0xF); - // QK_K 256 with 8 groups, handle 2 groups at a time - char * pb = (char *)packed_B; - char * ph = (char *)packed_B + (QK_K / 2) * TILE_N; - for (int k = 0; k < QK_K / 64; ++k) { - // pack 2 groups { n, g, k} to {g, k/4, 4n} - // e.g. {16, 2, 32} to {2, 8, 64} - for (int n = 0; n < TILE_N; ++n) { - v[n] = bytes_from_nibbles_64(B[n * KB].qs + k * 32, B[n * KB].qh, /* group */2 * k); - } - - transpose_16x16_32bit(v); - - // 1. pack lower 4bits with 2 groups - for (int n = 0; n < TILE_N; n += 2) { - // get lower 4 bits - const __m512i r0 = _mm512_and_si512(v[n], lowMask); - const __m512i r1 = _mm512_and_si512(v[n + 1], lowMask); - _mm512_storeu_si512((__m512i *)pb, packNibbles(r0, r1)); pb += 64; - } - - // 2. pack higher 1bit with 2 groups - const __m512i hmask = _mm512_set1_epi8(0x10); - for (int g = 0; g < 2; ++g) { - __m512i hbits = _mm512_setzero_si512(); - hbits = _mm512_add_epi8(hbits, _mm512_srli_epi16(_mm512_and_si512(v[g * 8 + 0], hmask), 4)); - hbits = _mm512_add_epi8(hbits, _mm512_srli_epi16(_mm512_and_si512(v[g * 8 + 1], hmask), 3)); - hbits = _mm512_add_epi8(hbits, _mm512_srli_epi16(_mm512_and_si512(v[g * 8 + 2], hmask), 2)); - hbits = _mm512_add_epi8(hbits, _mm512_srli_epi16(_mm512_and_si512(v[g * 8 + 3], hmask), 1)); - hbits = _mm512_add_epi8(hbits, _mm512_and_si512(v[g * 8 + 4], hmask) ); - hbits = _mm512_add_epi8(hbits, _mm512_slli_epi16(_mm512_and_si512(v[g * 8 + 5], hmask), 1)); - hbits = _mm512_add_epi8(hbits, _mm512_slli_epi16(_mm512_and_si512(v[g * 8 + 6], hmask), 2)); - hbits = _mm512_add_epi8(hbits, _mm512_slli_epi16(_mm512_and_si512(v[g * 8 + 7], hmask), 3)); - _mm512_storeu_si512((__m512i *)ph, hbits); ph += 64; - } - } -} - -template <> -inline void pack_qs(void * RESTRICT packed_B, const block_q6_K * RESTRICT B, int KB) { - __m512i v[32]; - const __m512i lowMask = _mm512_set1_epi8(0xF); - // QK_K 256 with 8 groups, handle 4 groups at a time - char * pb = (char *)packed_B; - char * ph = (char *)packed_B + (QK_K / 2) * TILE_N; - for (int k = 0; k < QK_K / 128; ++k) { - for (int n = 0; n < TILE_N; ++n) { - bytes_from_nibbles_128(v[n], v[n + 16], B[n * KB].ql + k * 64, B[n * KB].qh + k * 32); - } - - // top half: group 0,1 or 4,5; bottom half: group 2,3 or 6,7 - transpose_16x16_32bit(v); - transpose_16x16_32bit(v + 16); - - // 1. pack lower 4bits with 4 groups - for (int n = 0; n < 32; n += 2) { - const __m512i r0 = _mm512_and_si512(v[n], lowMask); - const __m512i r1 = _mm512_and_si512(v[n + 1], lowMask); - _mm512_storeu_si512((__m512i *)pb, packNibbles(r0, r1)); pb += 64; - } - - // 2. pack higher 2bit with 4 groups - const __m512i hmask = _mm512_set1_epi8(0x30); - for (int g = 0; g < 8; ++g) { - __m512i hbits = _mm512_setzero_si512(); - hbits = _mm512_add_epi8(hbits, _mm512_srli_epi16(_mm512_and_si512(v[g * 4 + 0], hmask), 4)); - hbits = _mm512_add_epi8(hbits, _mm512_srli_epi16(_mm512_and_si512(v[g * 4 + 1], hmask), 2)); - hbits = _mm512_add_epi8(hbits, _mm512_and_si512(v[g * 4 + 2], hmask) ); - hbits = _mm512_add_epi8(hbits, _mm512_slli_epi16(_mm512_and_si512(v[g * 4 + 3], hmask), 2)); - _mm512_storeu_si512((__m512i *)ph, hbits); ph += 64; - } - } -} - -template <> -inline void pack_qs(void * RESTRICT packed_B, const block_iq4_xs * RESTRICT B, int KB) { - __m512i v[16]; - char * pb = (char *)packed_B; - for (int k = 0; k < QK_K / 64; ++k) { - for (int n = 0; n < TILE_N; ++n) { - __m256i r0 = bytes_from_nibbles_32(B[n * KB].qs + k * 32 + 0); - __m256i r1 = bytes_from_nibbles_32(B[n * KB].qs + k * 32 + 16); - v[n] = _mm512_inserti32x8(_mm512_castsi256_si512(r0), r1, 1); - } - - transpose_16x16_32bit(v); - - // pack again with 128 to fully utilize vector length - for (int n = 0; n < TILE_N; n += 2) { - _mm512_storeu_si512((__m512i *)pb, packNibbles(v[n], v[n + 1])); - pb += 64; - } - } -} - -// pack B to vnni formats in 4bits or 8 bits -void pack_B(void * RESTRICT packed_B, const block_q4_0 * RESTRICT B, int KB) { - pack_qs(packed_B, B, KB); - ggml_half * d0 = reinterpret_cast((char *)packed_B + TILE_N * TILE_K / 2); - for (int n = 0; n < TILE_N; ++n) { - d0[n] = B[n * KB].d; - } -} - -void pack_B(void * RESTRICT packed_B, const block_q4_1 * RESTRICT B, int KB) { - pack_qs(packed_B, B, KB); - ggml_half * d0 = reinterpret_cast((char *)packed_B + TILE_N * TILE_K / 2); - ggml_half * m0 = d0 + TILE_N; - for (int n = 0; n < TILE_N; ++n) { - d0[n] = B[n * KB].d; - m0[n] = B[n * KB].m; - } -} - -inline void s8s8_compensation(void * RESTRICT packed_B) { - // packed_B layout: - // quants {TILE_N, TILEK} int8_t - // d0 {TILE_N} ggml_half - // comp {TILE_N} int32_t - const int offset = TILE_N * TILE_K + TILE_N * sizeof(ggml_half); - __m512i vcomp = _mm512_setzero_si512(); - const __m512i off = _mm512_set1_epi8(static_cast(0x80)); - for (int k = 0; k < 8; ++k) { - __m512i vb = _mm512_loadu_si512((const __m512i *)((const char *)packed_B + k * 64)); - vcomp = _mm512_dpbusd_epi32(vcomp, off, vb); - } - _mm512_storeu_si512((__m512i *)((char *)(packed_B) + offset), vcomp); -} - -void pack_B(void * RESTRICT packed_B, const block_q8_0 * RESTRICT B, int KB) { - pack_qs(packed_B, B, KB); - ggml_half * d0 = reinterpret_cast((char *)packed_B + TILE_N * TILE_K); - for (int n = 0; n < TILE_N; ++n) { - d0[n] = B[n * KB].d; - } - s8s8_compensation(packed_B); -} - -// convert 8 * {min, scale} from int6 to int8 -inline void unpack_mins_and_scales(const uint8_t * scales, uint32_t * utmp) { - const uint32_t kmask1 = 0x3f3f3f3f; - const uint32_t kmask2 = 0x0f0f0f0f; - const uint32_t kmask3 = 0x03030303; - - memcpy(utmp, scales, 12); - utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4); - const uint32_t uaux = utmp[1] & kmask1; - utmp[1] = (utmp[2] & kmask2) | (((utmp[0] >> 6) & kmask3) << 4); - utmp[2] = uaux; - utmp[0] &= kmask1; -} - -// packed_B layout: -// quants {8, TILE_N, 16} uint8 -// scales {8, TILE_N} uint8 -// mins {8, TILE_N} uint8 -// d {TILE_N} ggml_half -// dmin {TILE_N} ggml_half -void pack_B(void * RESTRICT packed_B, const block_q4_K * RESTRICT B, int KB) { - pack_qs(packed_B, B, KB); - - uint8_t * scales = reinterpret_cast((char *)packed_B + (QK_K / 2) * TILE_N); - uint8_t * mins = scales + 8 * TILE_N; - ggml_half * d = reinterpret_cast(mins + 8 * TILE_N); - ggml_half * dmin = d + TILE_N; - - union { - uint32_t u32[4]; - uint8_t u8[16]; - } s; - - for (int n = 0; n < TILE_N; ++n) { - unpack_mins_and_scales(B[n * KB].scales, s.u32); - for (int k = 0; k < 8; ++k) { - scales[k * TILE_N + n] = s.u8[k]; - mins[(k >> 1) * TILE_N * 2 + n * 2 + (k & 0x1)] = s.u8[k + 8]; - } - d[n] = B[n * KB].d; - dmin[n] = B[n * KB].dmin; - } -} - -// packed_B layout: -// quants {8, TILE_N, 16} uint8 -// qh {8, TILE_N, 4} uint8 -// scales {8, TILE_N} uint8 -// mins {8, TILE_N} uint8 -// d {TILE_N} ggml_half -// dmin {TILE_N} ggml_half -void pack_B(void * RESTRICT packed_B, const block_q5_K * RESTRICT B, int KB) { - pack_qs(packed_B, B, KB); - - uint8_t * scales = reinterpret_cast((char *)packed_B + (QK_K / 2) * TILE_N + (QK_K / 8) * TILE_N); - uint8_t * mins = scales + 8 * TILE_N; - ggml_half * d = reinterpret_cast(mins + 8 * TILE_N); - ggml_half * dmin = d + TILE_N; - - union { - uint32_t u32[4]; - uint8_t u8[16]; - } s; - - for (int n = 0; n < TILE_N; ++n) { - unpack_mins_and_scales(B[n * KB].scales, s.u32); - for (int k = 0; k < 8; ++k) { - scales[k * TILE_N + n] = s.u8[k]; - mins[(k >> 1) * TILE_N * 2 + n * 2 + (k & 0x1)] = s.u8[k + 8]; - } - d[n] = B[n * KB].d; - dmin[n] = B[n * KB].dmin; - } -} - -// packed_B layout: -// quants {16, TILE_N, 8} uint8 -// qh {16, TILE_N, 4} uint8 -// scales {16, TILE_N} uint8 -// d {TILE_N} ggml_half -void pack_B(void * RESTRICT packed_B, const block_q6_K * RESTRICT B, int KB) { - pack_qs(packed_B, B, KB); - - uint8_t * scales = reinterpret_cast((char *)packed_B + (QK_K / 2) * TILE_N + (QK_K / 4) * TILE_N); - ggml_half * d = reinterpret_cast(scales + 16 * TILE_N); - for (int n = 0; n < TILE_N; ++n) { - const int8_t * ps = B[n * KB].scales; - for (int k = 0; k < 16; ++k) { - scales[k * TILE_N + n] = ps[k]; - } - d[n] = B[n * KB].d; - } -} - -// packed_B layout: -// quants {8, TILE_N, 16} uint8 -// scales {8, TILE_N} int8 -// d {TILE_N} ggml_half -void pack_B(void * RESTRICT packed_B, const block_iq4_xs * RESTRICT B, int KB) { - pack_qs(packed_B, B, KB); - - int8_t * scales = reinterpret_cast((char *)packed_B + (QK_K / 2) * TILE_N); - ggml_half * d = reinterpret_cast(scales + 8 * TILE_N); - - // pack the scales - for (int n = 0; n < TILE_N; ++n) { - uint16_t sh = B[n * KB].scales_h; - for (int k = 0; k < 8; k += 2) { - const int16_t ls1 = ((B[n * KB].scales_l[k / 2] & 0xf) | ((sh << 4) & 0x30)) - 32; - const int16_t ls2 = ((B[n * KB].scales_l[k / 2] >> 4) | ((sh << 2) & 0x30)) - 32; - scales[(k + 0) * TILE_N + n] = ls1; - scales[(k + 1) * TILE_N + n] = ls2; - sh >>= 4; - } - d[n] = B[n * KB].d; - } -} - -template> -void unpack_B(packed_B_t * RESTRICT tile, const void * RESTRICT packed_B) { - GGML_UNUSED(tile); - GGML_UNUSED(packed_B); -} - -template <> -void unpack_B(int8_t * RESTRICT tile, const void * RESTRICT packed_B) { - const __m512i off = _mm512_set1_epi8(8); - const __m512i lowMask = _mm512_set1_epi8(0xF); - for (int n = 0; n < 8; n += 2) { - __m512i bytes = _mm512_loadu_si512((const __m512i *)((const char *)packed_B + n * 32)); - const __m512i r0 = _mm512_sub_epi8(_mm512_and_si512(bytes, lowMask), off); - const __m512i r1 = _mm512_sub_epi8(_mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask), off); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 0), r0); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 64), r1); - } -} - -template <> -void unpack_B(uint8_t * RESTRICT tile, const void * RESTRICT packed_B) { - const __m512i lowMask = _mm512_set1_epi8(0xF); - for (int n = 0; n < 8; n += 2) { - __m512i bytes = _mm512_loadu_si512((const __m512i *)((const char *)packed_B + n * 32)); - const __m512i r0 = _mm512_and_si512(bytes, lowMask); - const __m512i r1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 0), r0); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 64), r1); - } -} - -// packed_B_t for QKK is int8_t -template -void unpack_B(int8_t * RESTRICT tile, const void * RESTRICT packed_B, int k) { - const int packed_B_group_size = QK_K / 2 * TILE_N / 8; - const char * packed_B_group = (const char *)packed_B + k * packed_B_group_size; - const __m512i lowMask = _mm512_set1_epi8(0xF); - for (int n = 0; n < 8; n += 2) { - __m512i bytes = _mm512_loadu_si512(packed_B_group + n * 32); - const __m512i r0 = _mm512_and_si512(bytes, lowMask); - const __m512i r1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 0), r0); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 64), r1); - } -} - -template <> -void unpack_B(int8_t * RESTRICT tile, const void * RESTRICT packed_B, int k) { - // lower 4bits, stride 256 bytes - const int packed_l4_group_size = QK_K / 2 * TILE_N / 8; - const char * pb = (const char *)packed_B + k * packed_l4_group_size; - - // higher 1bit, stride 64 bytes - const int packed_h1_group_size = QK_K / 8 * TILE_N / 8; - const char * ph = (const char *)packed_B + (QK_K / 2) * TILE_N + k * packed_h1_group_size; - const __m512i hbits = _mm512_loadu_si512(ph); - - const __m512i lowMask = _mm512_set1_epi8(0xF); - __m512i hmask0 = _mm512_set1_epi8(0x1); - __m512i hmask1 = _mm512_set1_epi8(0x2); - - for (int n = 0; n < 8; n += 2) { - __m512i bytes = _mm512_loadu_si512(pb + n * 32); - __m512i r0 = _mm512_and_si512(bytes, lowMask); - __m512i r1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - __m512i h0 = _mm512_slli_epi16(_mm512_srli_epi16(_mm512_and_si512(hbits, hmask0), n), 4); - __m512i h1 = _mm512_slli_epi16(_mm512_srli_epi16(_mm512_and_si512(hbits, hmask1), n + 1), 4); - - hmask0 = _mm512_slli_epi16(hmask0, 2); - hmask1 = _mm512_slli_epi16(hmask1, 2); - r0 = _mm512_add_epi8(r0, h0); - r1 = _mm512_add_epi8(r1, h1); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 0), r0); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 64), r1); - } -} - -template <> -void unpack_B(int8_t * RESTRICT tile, const void * RESTRICT packed_B, int k) { - // lower 4bits, stride 128 bytes - const int packed_l4_group_size = QK_K / 2 * TILE_N / 16; - const char * pb = (const char *)packed_B + k * packed_l4_group_size; - - // higher 2bits, stride 64 bytes - const int packed_h2_group_size = QK_K / 4 * TILE_N / 16; - const char * ph = (const char *)packed_B + (QK_K / 2) * TILE_N + k * packed_h2_group_size; - const __m512i hbits = _mm512_loadu_si512(ph); - - const __m512i off = _mm512_set1_epi8(32); - const __m512i lowMask = _mm512_set1_epi8(0xF); - __m512i hmask0 = _mm512_set1_epi8(0x3); // 0011 - __m512i hmask1 = _mm512_set1_epi8(0xC); // 1100 - - // notes: skip zero padding from row4 to row7 as we have done so in `unpack_A` - __m512i bytes = _mm512_loadu_si512(pb); - __m512i r0 = _mm512_and_si512(bytes, lowMask); - __m512i r1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - __m512i h0 = _mm512_slli_epi16(_mm512_and_si512(hbits, hmask0), 4); - __m512i h1 = _mm512_slli_epi16(_mm512_and_si512(hbits, hmask1), 2); - _mm512_storeu_si512((__m512i *)(tile + 0), _mm512_sub_epi8(_mm512_add_epi8(r0, h0), off)); - _mm512_storeu_si512((__m512i *)(tile + 64), _mm512_sub_epi8(_mm512_add_epi8(r1, h1), off)); - - hmask0 = _mm512_slli_epi16(hmask0, 4); - hmask1 = _mm512_slli_epi16(hmask1, 4); - - bytes = _mm512_loadu_si512(pb + 64); - r0 = _mm512_and_si512(bytes, lowMask); - r1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - h0 = _mm512_and_si512(hbits, hmask0); - h1 = _mm512_srli_epi16(_mm512_and_si512(hbits, hmask1), 2); - _mm512_storeu_si512((__m512i *)(tile + 128), _mm512_sub_epi8(_mm512_add_epi8(r0, h0), off)); - _mm512_storeu_si512((__m512i *)(tile + 192), _mm512_sub_epi8(_mm512_add_epi8(r1, h1), off)); -} - -template <> -void unpack_B(int8_t * RESTRICT tile, const void * RESTRICT packed_B, int k) { - static const __m512i values128 = _mm512_set_epi8( - 113, 89, 69, 53, 38, 25, 13, 1, -10, -22, -35, -49, -65, -83, -104, -127, - 113, 89, 69, 53, 38, 25, 13, 1, -10, -22, -35, -49, -65, -83, -104, -127, - 113, 89, 69, 53, 38, 25, 13, 1, -10, -22, -35, -49, -65, -83, -104, -127, - 113, 89, 69, 53, 38, 25, 13, 1, -10, -22, -35, -49, -65, -83, -104, -127 - ); - - const int packed_B_group_size = QK_K / 2 * TILE_N / 8; - const char * pb = (const char *)packed_B + k * packed_B_group_size; - const __m512i lowMask = _mm512_set1_epi8(0xF); - - for (int n = 0; n < 8; n += 2) { - __m512i bytes = _mm512_loadu_si512(pb + n * 32); - const __m512i r0 = _mm512_shuffle_epi8(values128, _mm512_and_si512(bytes, lowMask)); - const __m512i r1 = _mm512_shuffle_epi8(values128, _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask)); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 0), r0); - _mm512_storeu_si512((__m512i *)(tile + n * 64 + 64), r1); - } -} - -template -struct acc_C {}; - -template -struct acc_C { - static void apply(float * RESTRICT C, int ldc, const int32_t * RESTRICT tile, const block_q8_0 * A, int lda, const void * packed_B, int nr) { - const int offset = TILE_N * TILE_K / 2; - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)((const char *)packed_B + offset))); - - for (int m = 0; m < nr; ++m) { - const __m512 vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[m * lda].d)); - const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N)); - - __m512 vsum; - if (is_acc) { - vsum = _mm512_loadu_ps(C + m * ldc); - } else { - vsum = _mm512_set1_ps(0.f); - } - vsum = _mm512_fmadd_ps(vtile, _mm512_mul_ps(vd0, vd1), vsum); - _mm512_storeu_ps(C + m * ldc, vsum); - } - } -}; - -template -struct acc_C { - static void apply(float * RESTRICT C, int ldc, const int32_t * RESTRICT tile, const block_q8_1 * A, int lda, const void * packed_B, int nr) { - const int offset = TILE_N * TILE_K / 2; - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)((const char *)packed_B + offset))); - const __m512 vm0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)((const char *)packed_B + offset + TILE_N * sizeof(ggml_half)))); - - for (int m = 0; m < nr; ++m) { - const __m512 vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[m * lda].d)); - const __m512 vs1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[m * lda].s)); - const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N)); - - __m512 vsum; - if (is_acc) { - vsum = _mm512_loadu_ps(C + m * ldc); - } else { - vsum = _mm512_set1_ps(0.f); - } - vsum = _mm512_fmadd_ps(vtile, _mm512_mul_ps(vd0, vd1), vsum); - vsum = _mm512_fmadd_ps(vm0, vs1, vsum); - _mm512_storeu_ps(C + m * ldc, vsum); - } - } -}; - -template -struct acc_C { - static void apply(float * RESTRICT C, int ldc, const int32_t * RESTRICT tile, const block_q8_0 * A, int lda, const void * packed_B, int nr) { - const int offset = TILE_N * TILE_K; - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)((const char *)packed_B + offset))); - - for (int m = 0; m < nr; ++m) { - const __m512 vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[m * lda].d)); - const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N)); - - __m512 vsum; - if (is_acc) { - vsum = _mm512_loadu_ps(C + m * ldc); - } else { - vsum = _mm512_set1_ps(0.f); - } - vsum = _mm512_fmadd_ps(vtile, _mm512_mul_ps(vd0, vd1), vsum); - _mm512_storeu_ps(C + m * ldc, vsum); - } - } -}; - -template -struct acc_C { - static void apply(float * RESTRICT C, int ldc, const int32_t * RESTRICT tile, const block_q8_K * A, int lda, const void * packed_B, int nr) { - const uint8_t * scales = reinterpret_cast((const char *)packed_B + (QK_K / 2) * TILE_N); - const uint8_t * mins = scales + 8 * TILE_N; - const ggml_half * d0 = reinterpret_cast(mins + 8 * TILE_N); - const ggml_half * dmin = d0 + TILE_N; - - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)d0)); - const __m512 vdmin = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)dmin)); - - for (int m = 0; m < nr; ++m) { - const float d1 = A[m * lda].d; - const __m512 vd = _mm512_mul_ps(_mm512_set1_ps(d1), vd0); - const __m512 vdm = _mm512_mul_ps(_mm512_set1_ps(-d1), vdmin); - const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N)); - - __m512 vsum; - if (is_acc) { - vsum = _mm512_loadu_ps(C + m * ldc); - } else { - vsum = _mm512_set1_ps(0.f); - } - - const __m256i q8sums = _mm256_loadu_si256((const __m256i *)A[m * lda].bsums); - const __m128i q8s = _mm_hadd_epi16(_mm256_extracti128_si256(q8sums, 0), _mm256_extracti128_si256(q8sums, 1)); - - __m512i acc_m = _mm512_setzero_si512(); - for (int k = 0; k < 4; ++k) { - __m512i vmask = _mm512_set1_epi32(k); - __m512i va = _mm512_permutexvar_epi32(vmask, _mm512_castsi128_si512(q8s)); - __m512i vb = _mm512_cvtepi8_epi16(_mm256_loadu_si256((const __m256i *)(mins + k * 32))); - acc_m = _mm512_dpwssds_epi32(acc_m, va, vb); - } - - vsum = _mm512_fmadd_ps(vtile, vd, vsum); - vsum = _mm512_fmadd_ps(_mm512_cvtepi32_ps(acc_m), vdm, vsum); - _mm512_storeu_ps(C + m * ldc, vsum); - } - } -}; - -template -struct acc_C { - static void apply(float * RESTRICT C, int ldc, const int32_t * RESTRICT tile, const block_q8_K * A, int lda, const void * packed_B, int nr) { - const uint8_t * scales = reinterpret_cast((const char *)packed_B + (QK_K / 2) * TILE_N + (QK_K / 8) * TILE_N); - const uint8_t * mins = scales + 8 * TILE_N; - const ggml_half * d0 = reinterpret_cast(mins + 8 * TILE_N); - const ggml_half * dmin = d0 + TILE_N; - - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)d0)); - const __m512 vdmin = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)dmin)); - - for (int m = 0; m < nr; ++m) { - const float d1 = A[m * lda].d; - const __m512 vd = _mm512_mul_ps(_mm512_set1_ps(d1), vd0); - const __m512 vdm = _mm512_mul_ps(_mm512_set1_ps(-d1), vdmin); - const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N)); - - __m512 vsum; - if (is_acc) { - vsum = _mm512_loadu_ps(C + m * ldc); - } else { - vsum = _mm512_set1_ps(0.f); - } - - const __m256i q8sums = _mm256_loadu_si256((const __m256i *)A[m * lda].bsums); - const __m128i q8s = _mm_hadd_epi16(_mm256_extracti128_si256(q8sums, 0), _mm256_extracti128_si256(q8sums, 1)); - - __m512i acc_m = _mm512_setzero_si512(); - for (int k = 0; k < 4; ++k) { - __m512i vmask = _mm512_set1_epi32(k); - __m512i va = _mm512_permutexvar_epi32(vmask, _mm512_castsi128_si512(q8s)); - __m512i vb = _mm512_cvtepi8_epi16(_mm256_loadu_si256((const __m256i *)(mins + k * 32))); - acc_m = _mm512_dpwssds_epi32(acc_m, va, vb); - } - - vsum = _mm512_fmadd_ps(vtile, vd, vsum); - vsum = _mm512_fmadd_ps(_mm512_cvtepi32_ps(acc_m), vdm, vsum); - _mm512_storeu_ps(C + m * ldc, vsum); - } - } -}; - -template -struct acc_C { - static void apply(float * RESTRICT C, int ldc, const int32_t * RESTRICT tile, const block_q8_K * A, int lda, const void * packed_B, int nr) { - const uint8_t * scales = reinterpret_cast((const char *)packed_B + (QK_K / 2) * TILE_N + (QK_K / 4) * TILE_N); - const ggml_half * d0 = reinterpret_cast(scales + 16 * TILE_N); - - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)d0)); - - for (int m = 0; m < nr; ++m) { - const float d1 = A[m * lda].d; - const __m512 vd = _mm512_mul_ps(_mm512_set1_ps(d1), vd0); - const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N)); - - __m512 vsum; - if (is_acc) { - vsum = _mm512_loadu_ps(C + m * ldc); - } else { - vsum = _mm512_set1_ps(0.f); - } - - vsum = _mm512_fmadd_ps(vtile, vd, vsum); - _mm512_storeu_ps(C + m * ldc, vsum); - } - } -}; - -template -struct acc_C { - static void apply(float * RESTRICT C, int ldc, const int32_t * RESTRICT tile, const block_q8_K * A, int lda, const void * packed_B, int nr) { - const int8_t * scales = reinterpret_cast((const char *)packed_B + (QK_K / 2) * TILE_N); - const ggml_half * d0 = reinterpret_cast(scales + 8 * TILE_N); - - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)d0)); - - for (int m = 0; m < nr; ++m) { - const float d1 = A[m * lda].d; - const __m512 vd = _mm512_mul_ps(_mm512_set1_ps(d1), vd0); - const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N)); - - __m512 vsum; - if (is_acc) { - vsum = _mm512_loadu_ps(C + m * ldc); - } else { - vsum = _mm512_set1_ps(0.f); - } - - vsum = _mm512_fmadd_ps(vtile, vd, vsum); - _mm512_storeu_ps(C + m * ldc, vsum); - } - } -}; - -template constexpr int get_quants_size(); -template <> constexpr int get_quants_size() { return (QK_K / 2) * TILE_N; } -template <> constexpr int get_quants_size() { return (QK_K / 2) * TILE_N + (QK_K / 8) * TILE_N; } -template <> constexpr int get_quants_size() { return (QK_K / 2) * TILE_N + (QK_K / 4) * TILE_N; } -template <> constexpr int get_quants_size() { return (QK_K / 2) * TILE_N; } - -// used for QKK format -template ::value, int>::type = 0> -inline void scale_C(const int32_t * RESTRICT tile, int32_t * RESTRICT sumi, const void * packed_B, int k, int nr) { - const uint8_t * scales = reinterpret_cast((const char *)packed_B + get_quants_size()); - const __m512i vscale = _mm512_cvtepi8_epi32(_mm_loadu_si128((const __m128i *)(scales + k * TILE_N))); - - for (int m = 0; m < nr; ++m) { - __m512i vsumi; - if (is_acc) { - vsumi = _mm512_loadu_si512(sumi + m * TILE_N); - } else { - vsumi = _mm512_setzero_si512(); - } - __m512i vtile = _mm512_loadu_si512(tile + m * TILE_N); - vsumi = _mm512_add_epi32(vsumi, _mm512_mullo_epi32(vtile, vscale)); - _mm512_storeu_si512((__m512i *)(sumi + m * TILE_N), vsumi); - } -} - -template -struct tinygemm_kernel_avx { - static void apply(int K, const TA * RESTRICT A, const TB * RESTRICT B, TC * RESTRICT C, int ldc) { - GGML_UNUSED(K); - GGML_UNUSED(A); - GGML_UNUSED(B); - GGML_UNUSED(C); - GGML_UNUSED(ldc); - } -}; - -template -struct tinygemm_kernel_avx { - static void apply(int K, const float * RESTRICT A, const ggml_fp16_t * RESTRICT B, float * RESTRICT C, int ldc) { - constexpr int ROWS = BLOCK_M; - constexpr int COLS = BLOCK_N; - assert(BLOCK_K == 16); - - __m512 va; - __m512 vb[COLS]; - __m512 vc[ROWS * COLS]; - - auto loadc = [&](auto idx) { - vc[idx] = _mm512_setzero_ps(); - }; - Unroll{}(loadc); - - auto compute = [&](auto idx, auto k) { - constexpr int row = idx / COLS; - constexpr int col = idx % COLS; - - if constexpr (col == 0) { - va = _mm512_loadu_ps(A + row * K + k); - } - if constexpr (row == 0) { - vb[col] = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(B + col * K + k))); - } - vc[idx] = _mm512_fmadd_ps(va, vb[col], vc[idx]); - }; - - for (int k = 0; k < K; k += 16) { - Unroll{}(compute, k); - } - - auto storec = [&](auto idx) { - constexpr int row = idx / COLS; - constexpr int col = idx % COLS; - C[row * ldc + col] = _mm512_reduce_add_ps(vc[idx]); - }; - Unroll{}(storec); - } -}; - -#define LAUNCH_TINYGEMM_KERNEL_AVX(MB_SIZE, NB_SIZE) \ - tinygemm_kernel_avx::apply( \ - K, (const float *)src1->data + mb_start * K, \ - (const type *)src0->data + nb_start * K, \ - (float *)dst->data + mb_start * ldc + nb_start, ldc); - - -// re-organize in the format {NB, KB, TILE_SIZE}: -#define PACKED_INDEX(n, k, KB, tile_size) (n * KB + k) * tile_size - -template -void convert_B_packed_format(void * RESTRICT packed_B, const TB * RESTRICT B, int N, int K) { - const int NB = N / TILE_N; - const int KB = K / BLOCK_K; - const int TILE_SIZE = get_tile_size(); - - // parallel on NB should be enough - parallel_for(NB, [&](int begin, int end) { - for (int n = begin; n < end; ++n) { - for (int k = 0; k < KB; ++k) { - int n0 = n * TILE_N; - pack_B((char *)packed_B + PACKED_INDEX(n, k, KB, TILE_SIZE), &B[n0 * KB + k], KB); - } - } - }); -} - -template -struct tinygemm_kernel_vnni {}; - -template -struct tinygemm_kernel_vnni { - static void apply(int KB, const void * RESTRICT _A, const void * RESTRICT _B, float * RESTRICT C, int ldc) { - - constexpr int COLS = BLOCK_N / 16; - const int TILE_SIZE = TILE_N * sizeof(block_q4_0); - - const block_q8_0 * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - __m512i va[8]; - __m512 vc[COLS]; - __m512 vd1; - - // sum of offsets, shared across COLS - // - // avx512-vnni does not have `_mm512_dpbssd_epi32`, - // need to transfrom ss to us: - // a * (b - 8) is equavilent to b * a - 8 * a - // s u u u s u s - // - __m512i vcomp; - - const __m512i off = _mm512_set1_epi8(8); - const __m512i lowMask = _mm512_set1_epi8(0xF); - - auto loadc = [&](auto col) { - vc[col] = _mm512_setzero_ps(); - }; - Unroll{}(loadc); - - auto compute = [&](auto col, auto i) { - // load a and compute compensation - if constexpr (col == 0) { - const int32_t * a_ptr = reinterpret_cast(A[0 * KB + i].qs); - vcomp = _mm512_setzero_si512(); - for (int k = 0; k < 8; ++k) { - va[k] = _mm512_set1_epi32(a_ptr[k]); - vcomp = _mm512_dpbusd_epi32(vcomp, off, va[k]); - } - vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[0 * KB + i].d)); - } - - // load b - __m512i vsum = _mm512_setzero_si512(); - const char * b_ptr = B + PACKED_INDEX(col, i, KB, TILE_SIZE); - for (int k = 0; k < 8; k += 2) { - __m512i bytes = _mm512_loadu_si512((const __m512i *)(b_ptr + k * 32)); - __m512i vb0 = _mm512_and_si512(bytes, lowMask); - vsum = _mm512_dpbusd_epi32(vsum, vb0, va[k + 0]); - __m512i vb1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - vsum = _mm512_dpbusd_epi32(vsum, vb1, va[k + 1]); - } - const int offset = TILE_N * TILE_K / 2; - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset))); - vsum = _mm512_sub_epi32(vsum, vcomp); - - vc[col] = _mm512_fmadd_ps(_mm512_cvtepi32_ps(vsum), _mm512_mul_ps(vd0, vd1), vc[col]); - }; - - for (int i = 0; i < KB; ++i) { - Unroll{}(compute, i); - } - - //store to C - auto storec = [&](auto col) { - _mm512_storeu_ps((__m512i*)(C + 0 * ldc + col * 16), vc[col]); - }; - Unroll{}(storec); - } -}; - -template -struct tinygemm_kernel_vnni { - static void apply(int KB, const void * RESTRICT _A, const void * RESTRICT _B, float * RESTRICT C, int ldc) { - - constexpr int COLS = BLOCK_N / 16; - const int TILE_SIZE = TILE_N * sizeof(block_q4_1); - - const block_q8_1 * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - __m512i va[8]; - __m512i vb[8]; - __m512 vc[COLS]; - __m512 vd1, vs1; - - const __m512i lowMask = _mm512_set1_epi8(0xF); - - auto loadc = [&](auto col) { - vc[col] = _mm512_setzero_ps(); - }; - Unroll{}(loadc); - - auto compute = [&](auto col, auto i) { - // load a - if constexpr (col == 0) { - const int32_t * a_ptr = reinterpret_cast(A[0 * KB + i].qs); - for (int k = 0; k < 8; ++k) { - va[k] = _mm512_set1_epi32(a_ptr[k]); - } - vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[0 * KB + i].d)); - vs1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[0 * KB + i].s)); - } - - // load b - const char * b_ptr = B + PACKED_INDEX(col, i, KB, TILE_SIZE); - for (int k = 0; k < 8; k += 2) { - __m512i bytes = _mm512_loadu_si512((const __m512i *)(b_ptr + k * 32)); - vb[k + 0] = _mm512_and_si512(bytes, lowMask); - vb[k + 1] = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - } - const int offset = TILE_N * TILE_K / 2; - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset))); - const __m512 vm0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset + TILE_N * sizeof(ggml_half)))); - - __m512i vsum = _mm512_setzero_si512(); - for (int k = 0; k < 8; ++k) { - vsum = _mm512_dpbusd_epi32(vsum, vb[k], va[k]); - } - - vc[col] = _mm512_fmadd_ps(_mm512_cvtepi32_ps(vsum), _mm512_mul_ps(vd0, vd1), vc[col]); - vc[col] = _mm512_fmadd_ps(vm0, vs1, vc[col]); - }; - - for (int i = 0; i < KB; ++i) { - Unroll{}(compute, i); - } - - //store to C - auto storec = [&](auto col) { - _mm512_storeu_ps((__m512i*)(C + 0 * ldc + col * 16), vc[col]); - }; - Unroll{}(storec); - } -}; - -template -struct tinygemm_kernel_vnni { - static void apply(int KB, const void * RESTRICT _A, const void * RESTRICT _B, float * RESTRICT C, int ldc) { - - constexpr int COLS = BLOCK_N / 16; - const int TILE_SIZE = TILE_N * sizeof(block_q8_0) + TILE_N * sizeof(int32_t); - - const block_q8_0 * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - __m512i va[8]; - __m512i vb[8]; - __m512 vc[COLS]; - __m512 vd1; - - // Notes: s8s8 igemm compensation in avx512-vnni - // change s8s8 to u8s8 with compensate - // a * b = (a + 128) * b - 128 * b - // s s u s u s - // - // (128 * b is pre-computed when packing B to vnni formats) - // - const __m512i off = _mm512_set1_epi8(static_cast(0x80)); - - auto loadc = [&](auto col) { - vc[col] = _mm512_setzero_ps(); - }; - Unroll{}(loadc); - - auto compute = [&](auto col, auto i) { - // load a and add offset 128 - if constexpr (col == 0) { - const int32_t * a_ptr = reinterpret_cast(A[0 * KB + i].qs); - for (int k = 0; k < 8; ++k) { - va[k] = _mm512_set1_epi32(a_ptr[k]); - va[k] = _mm512_add_epi8(va[k], off); - } - vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[0 * KB + i].d)); - } - - // load b - const char * b_ptr = B + PACKED_INDEX(col, i, KB, TILE_SIZE); - for (int k = 0; k < 8; ++k) { - vb[k] = _mm512_loadu_si512((const __m512i *)(b_ptr + k * 64)); - } - const int offset = TILE_N * TILE_K; - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset))); - const int offset2 = TILE_N * TILE_K + TILE_N * sizeof(ggml_half); - const __m512i vcomp = _mm512_loadu_si512((const __m512i *)(b_ptr + offset2)); - - __m512i vsum = _mm512_setzero_si512(); - for (int k = 0; k < 8; ++k) { - vsum = _mm512_dpbusd_epi32(vsum, va[k], vb[k]); - } - vsum = _mm512_sub_epi32(vsum, vcomp); - - vc[col] = _mm512_fmadd_ps(_mm512_cvtepi32_ps(vsum), _mm512_mul_ps(vd0, vd1), vc[col]); - }; - - for (int i = 0; i < KB; ++i) { - Unroll{}(compute, i); - } - - //store to C - auto storec = [&](auto col) { - _mm512_storeu_ps((__m512i*)(C + 0 * ldc + col * 16), vc[col]); - }; - Unroll{}(storec); - } -}; - -template -struct tinygemm_kernel_vnni { - static void apply(int KB, const void * RESTRICT _A, const void * RESTRICT _B, float * RESTRICT C, int ldc) { - - constexpr int COLS = BLOCK_N / 16; - const int TILE_SIZE = TILE_N * sizeof(block_q4_K) + TILE_N * 4; - - const block_q8_K * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - // a.qs: 8 groups, 32 bytes each group (m256i) - __m512i va[8]; - // a.bsum: 8 groups, 2 bytes each group (m128i) - __m512i va_bsum; - __m512 vc[COLS]; - __m512 vd1; - - // packed_B: - const int offset_scales = (QK_K / 2) * TILE_N; - const int offset_mins = (QK_K / 2) * TILE_N + 8 * TILE_N; - const int offset_d0 = (QK_K / 2) * TILE_N + 16 * TILE_N; - const int offset_dmin = (QK_K / 2) * TILE_N + 16 * TILE_N + TILE_N * sizeof(ggml_half); - - const __m512i lowMask = _mm512_set1_epi8(0xF); - - auto loadc = [&](auto col) { - vc[col] = _mm512_setzero_ps(); - }; - Unroll{}(loadc); - - // Notes: vnni formats in QK_K - // a) quants vnni format - // int8 {k/4, n, 4}, viewed as 2d {k/4, 4n}, k = 32 - // from {16, 32} to {8, 64} - // - // b) min vnni format - // int16 {k/2, n, 2}, viewed as 2d {k/2, 2n}, k = 8 - // from {16, 8} to {4, 32} - // - auto compute = [&](auto col, auto i) { - // load a - if constexpr (col == 0) { - for (int k_group = 0; k_group < QK_K / 32; ++k_group) { - va[k_group] = _mm512_castsi256_si512(_mm256_loadu_si256((const __m256i *)(A[0 * KB + i].qs + k_group * 32))); - } - const __m256i q8sums = _mm256_loadu_si256((const __m256i *)A[0 * KB + i].bsums); - const __m128i q8s = _mm_hadd_epi16(_mm256_extracti128_si256(q8sums, 0), _mm256_extracti128_si256(q8sums, 1)); - va_bsum = _mm512_castsi128_si512(q8s); - vd1 = _mm512_set1_ps(A[0 * KB + i].d); - } - - // step 1: accumultate the quants - __m512i acc = _mm512_setzero_si512(); - const char * b_ptr = B + PACKED_INDEX(col, i, KB, TILE_SIZE); - const char * b_qs = b_ptr; - for (int k_group = 0; k_group < QK_K / 32; ++k_group) { - __m512i vsum = _mm512_setzero_si512(); - for (int k = 0; k < 8; k += 2) { - __m512i va0 = _mm512_permutexvar_epi32(_mm512_set1_epi32(k + 0), va[k_group]); - __m512i va1 = _mm512_permutexvar_epi32(_mm512_set1_epi32(k + 1), va[k_group]); - - __m512i bytes = _mm512_loadu_si512((const __m512i *)b_qs); - __m512i vb0 = _mm512_and_si512(bytes, lowMask); - vsum = _mm512_dpbusd_epi32(vsum, vb0, va0); - __m512i vb1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - vsum = _mm512_dpbusd_epi32(vsum, vb1, va1); - - b_qs += 64; - } - // vacc += scale * (q8 @ q4) - const __m512i vscale = _mm512_cvtepi8_epi32(_mm_loadu_si128((const __m128i *)(b_ptr + offset_scales + k_group * TILE_N))); - acc = _mm512_add_epi32(acc, _mm512_mullo_epi32(vsum, vscale)); - } - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset_d0))); - vc[col] = _mm512_fmadd_ps(_mm512_cvtepi32_ps(acc), _mm512_mul_ps(vd0, vd1), vc[col]); - - // step 2: accumulate the mins - __m512i acc_m = _mm512_setzero_si512(); - for (int k = 0; k < 4; ++k) { - __m512i vmask = _mm512_set1_epi32(k); - __m512i va = _mm512_permutexvar_epi32(vmask, va_bsum); - __m512i vb = _mm512_cvtepi8_epi16(_mm256_loadu_si256((const __m256i *)(b_ptr + offset_mins + k * 32))); - acc_m = _mm512_dpwssds_epi32(acc_m, va, vb); - } - const __m512 vdmin = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset_dmin))); - vc[col] = _mm512_fnmadd_ps(_mm512_cvtepi32_ps(acc_m), _mm512_mul_ps(vdmin, vd1), vc[col]); - }; - - for (int i = 0; i < KB; ++i) { - Unroll{}(compute, i); - } - - //store to C - auto storec = [&](auto col) { - _mm512_storeu_ps((__m512i*)(C + 0 * ldc + col * 16), vc[col]); - }; - Unroll{}(storec); - } -}; - -template -struct tinygemm_kernel_vnni { - static void apply(int KB, const void * RESTRICT _A, const void * RESTRICT _B, float * RESTRICT C, int ldc) { - - constexpr int COLS = BLOCK_N / 16; - const int TILE_SIZE = TILE_N * sizeof(block_q5_K) + TILE_N * 4; - - const block_q8_K * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - // a.qs: 8 groups, 32 bytes each group (m256i) - __m512i va[8]; - // a.bsum: 8 groups, 2 bytes each group (m128i) - __m512i va_bsum; - __m512 vc[COLS]; - __m512 vd1; - - // packed_B: - const int offset_qh = (QK_K / 2) * TILE_N; - const int offset_scales = (QK_K / 2) * TILE_N + (QK_K / 8) * TILE_N; - const int offset_mins = (QK_K / 2) * TILE_N + (QK_K / 8) * TILE_N + 8 * TILE_N; - const int offset_d0 = (QK_K / 2) * TILE_N + (QK_K / 8) * TILE_N + 16 * TILE_N; - const int offset_dmin = (QK_K / 2) * TILE_N + (QK_K / 8) * TILE_N + 16 * TILE_N + TILE_N * sizeof(ggml_half); - - const __m512i lowMask = _mm512_set1_epi8(0xF); - - auto loadc = [&](auto col) { - vc[col] = _mm512_setzero_ps(); - }; - Unroll{}(loadc); - - // Q5_K and Q4_K shares the same vnni formats, refer to notes above. - auto compute = [&](auto col, auto i) { - // load a - if constexpr (col == 0) { - for (int k_group = 0; k_group < QK_K / 32; ++k_group) { - va[k_group] = _mm512_castsi256_si512(_mm256_loadu_si256((const __m256i *)(A[0 * KB + i].qs + k_group * 32))); - } - const __m256i q8sums = _mm256_loadu_si256((const __m256i *)A[0 * KB + i].bsums); - const __m128i q8s = _mm_hadd_epi16(_mm256_extracti128_si256(q8sums, 0), _mm256_extracti128_si256(q8sums, 1)); - va_bsum = _mm512_castsi128_si512(q8s); - vd1 = _mm512_set1_ps(A[0 * KB + i].d); - } - - // step 1: accumultate the quants - __m512i acc = _mm512_setzero_si512(); - const char * b_ptr = B + PACKED_INDEX(col, i, KB, TILE_SIZE); - const char * b_qs = b_ptr; - const char * b_qh = b_ptr + offset_qh; - for (int k_group = 0; k_group < QK_K / 32; ++k_group) { - __m512i vsum = _mm512_setzero_si512(); - __m512i hmask0 = _mm512_set1_epi8(0x1); - __m512i hmask1 = _mm512_set1_epi8(0x2); - __m512i hbits = _mm512_loadu_si512((const __m512i *)(b_qh + k_group * 64)); - for (int k = 0; k < 8; k += 2) { - __m512i va0 = _mm512_permutexvar_epi32(_mm512_set1_epi32(k + 0), va[k_group]); - __m512i va1 = _mm512_permutexvar_epi32(_mm512_set1_epi32(k + 1), va[k_group]); - - __m512i bytes = _mm512_loadu_si512((const __m512i *)b_qs); - __m512i vb0 = _mm512_and_si512(bytes, lowMask); - __m512i vb1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - - __m512i vh0 = _mm512_slli_epi16(_mm512_srli_epi16(_mm512_and_si512(hbits, hmask0), k), 4); - __m512i vh1 = _mm512_slli_epi16(_mm512_srli_epi16(_mm512_and_si512(hbits, hmask1), k + 1), 4); - - hmask0 = _mm512_slli_epi16(hmask0, 2); - hmask1 = _mm512_slli_epi16(hmask1, 2); - vb0 = _mm512_add_epi8(vb0, vh0); - vb1 = _mm512_add_epi8(vb1, vh1); - - vsum = _mm512_dpbusd_epi32(vsum, vb0, va0); - vsum = _mm512_dpbusd_epi32(vsum, vb1, va1); - - b_qs += 64; - } - // vacc += scale * (q8 @ q5) - const __m512i vscale = _mm512_cvtepi8_epi32(_mm_loadu_si128((const __m128i *)(b_ptr + offset_scales + k_group * TILE_N))); - acc = _mm512_add_epi32(acc, _mm512_mullo_epi32(vsum, vscale)); - } - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset_d0))); - vc[col] = _mm512_fmadd_ps(_mm512_cvtepi32_ps(acc), _mm512_mul_ps(vd0, vd1), vc[col]); - - // step 2: accumulate the mins - __m512i acc_m = _mm512_setzero_si512(); - for (int k = 0; k < 4; ++k) { - __m512i vmask = _mm512_set1_epi32(k); - __m512i va = _mm512_permutexvar_epi32(vmask, va_bsum); - __m512i vb = _mm512_cvtepi8_epi16(_mm256_loadu_si256((const __m256i *)(b_ptr + offset_mins + k * 32))); - acc_m = _mm512_dpwssds_epi32(acc_m, va, vb); - } - const __m512 vdmin = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset_dmin))); - vc[col] = _mm512_fnmadd_ps(_mm512_cvtepi32_ps(acc_m), _mm512_mul_ps(vdmin, vd1), vc[col]); - }; - - for (int i = 0; i < KB; ++i) { - Unroll{}(compute, i); - } - - //store to C - auto storec = [&](auto col) { - _mm512_storeu_ps((__m512i*)(C + 0 * ldc + col * 16), vc[col]); - }; - Unroll{}(storec); - } -}; - -template -struct tinygemm_kernel_vnni { - static void apply(int KB, const void * RESTRICT _A, const void * RESTRICT _B, float * RESTRICT C, int ldc) { - - constexpr int COLS = BLOCK_N / 16; - const int TILE_SIZE = TILE_N * sizeof(block_q6_K); - - const block_q8_K * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - // load the 256 bytes from A to 4 avx512 vectors - __m512i va[4]; - __m512 vc[COLS]; - __m512 vd1; - - // packed_B: - const int offset_qh = (QK_K / 2) * TILE_N; - const int offset_scales = (QK_K / 2) * TILE_N + (QK_K / 4) * TILE_N; - const int offset_d0 = (QK_K / 2) * TILE_N + (QK_K / 4) * TILE_N + 16 * TILE_N; - - // compensation - __m512i vcomp; - - const __m512i m32s = _mm512_set1_epi32(32); - const __m512i lowMask = _mm512_set1_epi8(0xF); - - auto loadc = [&](auto col) { - vc[col] = _mm512_setzero_ps(); - }; - Unroll{}(loadc); - - auto compute = [&](auto col, auto i) { - if constexpr (col == 0) { - // load a - va[0] = _mm512_loadu_si512((const __m512i *)(A[0 * KB + i].qs + 0)); - va[1] = _mm512_loadu_si512((const __m512i *)(A[0 * KB + i].qs + 64)); - va[2] = _mm512_loadu_si512((const __m512i *)(A[0 * KB + i].qs + 128)); - va[3] = _mm512_loadu_si512((const __m512i *)(A[0 * KB + i].qs + 192)); - - const __m256i q8sums = _mm256_loadu_si256((const __m256i *)A[0 * KB + i].bsums); - vcomp = _mm512_mullo_epi32(_mm512_cvtepi16_epi32(q8sums), m32s); - vd1 = _mm512_set1_ps(A[0 * KB + i].d); - } - - // accmulate the quants - __m512i acc = _mm512_setzero_si512(); - const char * b_ptr = B + PACKED_INDEX(col, i, KB, TILE_SIZE); - const char * b_qs = b_ptr; - const char * b_qh = b_ptr + offset_qh; - int mask = 0; - for (int k_group = 0; k_group < QK_K / 16; ++k_group) { - int r = k_group >> 2; - __m512i va0 = _mm512_permutexvar_epi32(_mm512_set1_epi32(mask++), va[r]); - __m512i va1 = _mm512_permutexvar_epi32(_mm512_set1_epi32(mask++), va[r]); - - __m512i vsum = _mm512_setzero_si512(); - __m512i hmask = _mm512_set1_epi8(0x3); - - __m512i bytes = _mm512_loadu_si512(b_qs); - __m512i hbits = _mm512_loadu_si512(b_qh); - __m512i vb0 = _mm512_and_si512(bytes, lowMask); - __m512i vb1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - __m512i vh0 = _mm512_slli_epi16(_mm512_and_si512(hbits, hmask), 4); - __m512i vh1 = _mm512_slli_epi16(_mm512_and_si512(hbits, _mm512_slli_epi16(hmask, 2)), 2); - - vb0 = _mm512_add_epi8(vb0, vh0); - vb1 = _mm512_add_epi8(vb1, vh1); - vsum = _mm512_dpbusd_epi32(vsum, vb0, va0); - vsum = _mm512_dpbusd_epi32(vsum, vb1, va1); - b_qs += 64; - - va0 = _mm512_permutexvar_epi32(_mm512_set1_epi32(mask++), va[r]); - va1 = _mm512_permutexvar_epi32(_mm512_set1_epi32(mask++), va[r]); - - bytes = _mm512_loadu_si512(b_qs); - vb0 = _mm512_and_si512(bytes, lowMask); - vb1 = _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask); - vh0 = _mm512_and_si512(hbits, _mm512_slli_epi16(hmask, 4)); - vh1 = _mm512_srli_epi16(_mm512_and_si512(hbits, _mm512_slli_epi16(hmask, 6)), 2); - vb0 = _mm512_add_epi8(vb0, vh0); - vb1 = _mm512_add_epi8(vb1, vh1); - vsum = _mm512_dpbusd_epi32(vsum, vb0, va0); - vsum = _mm512_dpbusd_epi32(vsum, vb1, va1); - b_qs += 64; - b_qh += 64; - - // B * A - 32 * A - __m512i vmask = _mm512_set1_epi32(k_group); - vsum = _mm512_sub_epi32(vsum, _mm512_permutexvar_epi32(vmask, vcomp)); - - // vacc += scale * (q8 @ q6) - const __m512i vscale = _mm512_cvtepi8_epi32(_mm_loadu_si128((const __m128i *)(b_ptr + offset_scales + k_group * TILE_N))); - acc = _mm512_add_epi32(acc, _mm512_mullo_epi32(vsum, vscale)); - } - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset_d0))); - vc[col] = _mm512_fmadd_ps(_mm512_cvtepi32_ps(acc), _mm512_mul_ps(vd0, vd1), vc[col]); - }; - - for (int i = 0; i < KB; ++i) { - Unroll{}(compute, i); - } - - //store to C - auto storec = [&](int col) { - _mm512_storeu_ps((__m512i*)(C + 0 * ldc + col * 16), vc[col]); - }; - Unroll{}(storec); - } -}; - -template -struct tinygemm_kernel_vnni { - static void apply(int KB, const void * RESTRICT _A, const void * RESTRICT _B, float * RESTRICT C, int ldc) { - - constexpr int COLS = BLOCK_N / 16; - const int TILE_SIZE = TILE_N * sizeof(block_iq4_xs) + TILE_N * 2; - - const block_q8_K * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - // load the 256 bytes from A to 4 avx512 vectors - __m512i va[4]; - __m512 vc[COLS]; - __m512 vd1; - - // packed_B: - const int offset_scales = (QK_K / 2) * TILE_N ; - const int offset_d0 = (QK_K / 2) * TILE_N + 8 * TILE_N; - - // compensation - __m512i vcomp; - - const __m256i m128s = _mm256_set1_epi16(128); - const __m512i lowMask = _mm512_set1_epi8(0xF); - - const __m512i values128 = _mm512_set_epi8( - 113, 89, 69, 53, 38, 25, 13, 1, -10, -22, -35, -49, -65, -83, -104, -127, - 113, 89, 69, 53, 38, 25, 13, 1, -10, -22, -35, -49, -65, -83, -104, -127, - 113, 89, 69, 53, 38, 25, 13, 1, -10, -22, -35, -49, -65, -83, -104, -127, - 113, 89, 69, 53, 38, 25, 13, 1, -10, -22, -35, -49, -65, -83, -104, -127 - ); - const __m512i off = _mm512_set1_epi8(static_cast(0x80)); - const __m512i values256 = _mm512_add_epi8(values128, off); - - auto loadc = [&](auto col) { - vc[col] = _mm512_setzero_ps(); - }; - Unroll{}(loadc); - - auto compute = [&](auto col, auto i) { - if constexpr (col == 0) { - // load a - va[0] = _mm512_loadu_si512((const __m512i *)(A[0 * KB + i].qs + 0)); - va[1] = _mm512_loadu_si512((const __m512i *)(A[0 * KB + i].qs + 64)); - va[2] = _mm512_loadu_si512((const __m512i *)(A[0 * KB + i].qs + 128)); - va[3] = _mm512_loadu_si512((const __m512i *)(A[0 * KB + i].qs + 192)); - - // compensation: 128 * A - const __m256i q8sums = _mm256_loadu_si256((const __m256i *)A[0 * KB + i].bsums); - vcomp = _mm512_castsi256_si512(_mm256_madd_epi16(q8sums, m128s)); - vd1 = _mm512_set1_ps(A[0 * KB + i].d); - } - - // accmulate the quants - __m512i acc = _mm512_setzero_si512(); - const char * b_ptr = B + PACKED_INDEX(col, i, KB, TILE_SIZE); - const char * b_qs = b_ptr; - int mask = 0; - for (int k_group = 0; k_group < QK_K / 32; ++k_group) { - int r = k_group >> 1; - __m512i vmask = _mm512_set1_epi32(k_group); - __m512i vsum = _mm512_setzero_si512(); - for (int k = 0; k < 8; k += 2) { - __m512i va0 = _mm512_permutexvar_epi32(_mm512_set1_epi32(mask++), va[r]); - __m512i va1 = _mm512_permutexvar_epi32(_mm512_set1_epi32(mask++), va[r]); - - __m512i bytes = _mm512_loadu_si512(b_qs); - __m512i vb0 = _mm512_shuffle_epi8(values256, _mm512_and_si512(bytes, lowMask)); - __m512i vb1 = _mm512_shuffle_epi8(values256, _mm512_and_si512(_mm512_srli_epi16(bytes, 4), lowMask)); - - vsum = _mm512_dpbusd_epi32(vsum, vb0, va0); - vsum = _mm512_dpbusd_epi32(vsum, vb1, va1); - b_qs += 64; - } - // (B + 128) * A - 128 * A - vsum = _mm512_sub_epi32(vsum, _mm512_permutexvar_epi32(vmask, vcomp)); - - // vacc += scale * (q8 @ q4) - const __m512i vscale = _mm512_cvtepi8_epi32(_mm_loadu_si128((const __m128i *)(b_ptr + offset_scales + k_group * TILE_N))); - acc = _mm512_add_epi32(acc, _mm512_mullo_epi32(vsum, vscale)); - } - const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)(b_ptr + offset_d0))); - vc[col] = _mm512_fmadd_ps(_mm512_cvtepi32_ps(acc), _mm512_mul_ps(vd0, vd1), vc[col]); - }; - - for (int i = 0; i < KB; ++i) { - Unroll{}(compute, i); - } - - //store to C - auto storec = [&](auto col) { - _mm512_storeu_ps((__m512i*)(C + 0 * ldc + col * 16), vc[col]); - }; - Unroll{}(storec); - } -}; - -#define LAUNCH_TINYGEMM_KERNEL_VNNI(NB_SIZE) \ - tinygemm_kernel_vnni::apply( \ - KB, (const char *)wdata + 0 * row_size_A, \ - (const char *)src0->data + PACKED_INDEX(nb * kTilesN, 0, KB, TILE_SIZE), \ - (float *) dst->data + 0 * N + nb_start, ldc) - -template ::value, int>::type = 0> -void tinygemm_kernel_amx(int M, int N, int KB, const void * RESTRICT _A, const void * RESTRICT _B, TC * RESTRICT C, int ldc) { - using packed_B_t = packed_B_type; - const int TILE_SIZE = get_tile_size(); - const bool need_unpack = do_unpack::value; - - GGML_ASSERT(M <= 2 * TILE_M && N == 2 * TILE_N); - const TA * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - const int m0 = std::min(M, TILE_M); - const int m1 = std::max(M - TILE_M, 0); - const int lda = KB * sizeof(TA); - //const int ldb = KB * sizeof(TB); - - static thread_local packed_B_t Tile0[TILE_N * TILE_K]; - static thread_local packed_B_t Tile1[TILE_N * TILE_K]; - static thread_local int8_t Tile23[TILE_M * TILE_K]; - - static thread_local int32_t TileC0[TILE_M * TILE_N * 4]; - static thread_local int32_t TileC1[TILE_M * TILE_N * 4]; - - // double buffering C to interleave avx512 and amx - int32_t * C_cur = TileC0; - int32_t * C_pre = TileC1; - - auto Tile4 = [&](int32_t * base) { return base; }; - auto Tile5 = [&](int32_t * base) { return base + TILE_M * TILE_N; }; - auto Tile6 = [&](int32_t * base) { return base + 2 * TILE_M * TILE_N; }; - auto Tile7 = [&](int32_t * base) { return base + 3 * TILE_M * TILE_N; }; - - if (M == 2 * TILE_M) { - // i = 0 - const char * B_blk0 = B + PACKED_INDEX(0, 0, KB, TILE_SIZE); - const char * B_blk1 = B + PACKED_INDEX(1, 0, KB, TILE_SIZE); - if (need_unpack) { - unpack_B(Tile0, B_blk0); - _tile_loadd(TMM0, Tile0, TILE_N * VNNI_BLK); - } else { - _tile_loadd(TMM0, B_blk0, TILE_N * VNNI_BLK); - } - - _tile_zero(TMM4); - _tile_loadd(TMM2, A[0].qs, lda); - _tile_dpbssd(TMM4, TMM2, TMM0); - _tile_stored(TMM4, Tile4(C_pre), TILE_N * sizeof(int32_t)); - - _tile_zero(TMM5); - _tile_loadd(TMM3, A[TILE_M * KB + 0].qs, lda); - _tile_dpbssd(TMM5, TMM3, TMM0); - _tile_stored(TMM5, Tile5(C_pre), TILE_N * sizeof(int32_t)); - - if (need_unpack) { - unpack_B(Tile1, B_blk0); - _tile_loadd(TMM1, Tile1, TILE_N * VNNI_BLK); - } else { - _tile_loadd(TMM1, B_blk1, TILE_N * VNNI_BLK); - } - - _tile_zero(TMM6); - _tile_dpbssd(TMM6, TMM2, TMM1); - _tile_stored(TMM6, Tile6(C_pre), TILE_N * sizeof(int32_t)); - - _tile_zero(TMM7); - _tile_dpbssd(TMM7, TMM3, TMM1); - _tile_stored(TMM7, Tile7(C_pre), TILE_N * sizeof(int32_t)); - - for (int i = 1; i < KB; ++i) { - // index of previous iter - const int ii = i - 1; - const char * B_blk0 = B + PACKED_INDEX(0, i, KB, TILE_SIZE); - const char * B_blk1 = B + PACKED_INDEX(1, i, KB, TILE_SIZE); - GGML_DISPATCH_BOOL(ii > 0, is_acc, [&] { - if (need_unpack) { - unpack_B(Tile0, B_blk0); - _tile_loadd(TMM0, Tile0, TILE_N * VNNI_BLK); - } else { - _tile_loadd(TMM0, B_blk0, TILE_N * VNNI_BLK); - } - _tile_zero(TMM4); - _tile_loadd(TMM2, A[i].qs, lda); - acc_C::apply(C, ldc, Tile4(C_pre), &A[ii], KB, B + PACKED_INDEX(0, ii, KB, TILE_SIZE), TILE_M); - - _tile_dpbssd(TMM4, TMM2, TMM0); - _tile_stored(TMM4, Tile4(C_cur), TILE_N * sizeof(int32_t)); - - _tile_zero(TMM5); - _tile_loadd(TMM3, A[TILE_M * KB + i].qs, lda); - acc_C::apply(C + TILE_M * ldc, ldc, Tile5(C_pre), &A[TILE_M * KB + ii], KB, B + PACKED_INDEX(0, ii, KB, TILE_SIZE), TILE_M); - - _tile_dpbssd(TMM5, TMM3, TMM0); - _tile_stored(TMM5, Tile5(C_cur), TILE_N * sizeof(int32_t)); - - if (need_unpack) { - unpack_B(Tile1, B_blk1); - _tile_loadd(TMM1, Tile1, TILE_N * VNNI_BLK); - } else { - _tile_loadd(TMM1, B_blk1, TILE_N * VNNI_BLK); - } - _tile_zero(TMM6); - acc_C::apply(C + TILE_N, ldc, Tile6(C_pre), &A[ii], KB, B + PACKED_INDEX(1, ii, KB, TILE_SIZE), TILE_M); - - _tile_dpbssd(TMM6, TMM2, TMM1); - _tile_stored(TMM6, Tile6(C_cur), TILE_N * sizeof(int32_t)); - - _tile_zero(TMM7); - acc_C::apply(C + TILE_M * ldc + TILE_N, ldc, Tile7(C_pre), &A[TILE_M * KB + ii], KB, B + PACKED_INDEX(1, ii, KB, TILE_SIZE), TILE_M); - - _tile_dpbssd(TMM7, TMM3, TMM1); - _tile_stored(TMM7, Tile7(C_cur), TILE_N * sizeof(int32_t)); - - std::swap(C_cur, C_pre); - }); - } - // final accumulation - { - int ii = KB - 1; - acc_C::apply(C, ldc, Tile4(C_pre), &A[ii], KB, B + PACKED_INDEX(0, ii, KB, TILE_SIZE), TILE_M); - acc_C::apply(C + TILE_M * ldc, ldc, Tile5(C_pre), &A[TILE_M * KB + ii], KB, B + PACKED_INDEX(0, ii, KB, TILE_SIZE), TILE_M); - acc_C::apply(C + TILE_N, ldc, Tile6(C_pre), &A[ii], KB, B + PACKED_INDEX(1, ii, KB, TILE_SIZE), TILE_M); - acc_C::apply(C + TILE_M * ldc + TILE_N, ldc, Tile7(C_pre), &A[TILE_M * KB + ii], KB, B + PACKED_INDEX(1, ii, KB, TILE_SIZE), TILE_M); - } - } else { - for (int i = 0; i < KB; ++i) { - _tile_zero(TMM4); - _tile_zero(TMM6); - if (m1 != 0) { - _tile_zero(TMM5); - _tile_zero(TMM7); - } - - const char * B_blk0 = B + PACKED_INDEX(0, i, KB, TILE_SIZE); - const char * B_blk1 = B + PACKED_INDEX(1, i, KB, TILE_SIZE); - if (need_unpack) { - unpack_B(Tile0, B_blk0); - _tile_loadd(TMM0, Tile0, TILE_N * VNNI_BLK); - } else { - _tile_loadd(TMM0, B_blk0, TILE_N * VNNI_BLK); - } - - if (need_unpack) { - unpack_B(Tile1, B_blk1); - _tile_loadd(TMM1, Tile1, TILE_N * VNNI_BLK); - } else { - _tile_loadd(TMM1, B_blk1, TILE_N * VNNI_BLK); - } - - if (m0 == TILE_M) { - _tile_loadd(TMM2, A[i].qs, lda); - } else { - unpack_A(Tile23, &A[i], KB, m0); - _tile_loadd(TMM2, Tile23, TILE_K); - } - - _tile_dpbssd(TMM4, TMM2, TMM0); - _tile_dpbssd(TMM6, TMM2, TMM1); - - _tile_stored(TMM4, Tile4(C_cur), TILE_N * sizeof(int32_t)); - _tile_stored(TMM6, Tile6(C_cur), TILE_N * sizeof(int32_t)); - - GGML_DISPATCH_BOOL(i > 0, is_acc, [&] { - acc_C::apply(C, ldc, Tile4(C_cur), &A[i], KB, B + PACKED_INDEX(0, i, KB, TILE_SIZE), m0); - acc_C::apply(C + TILE_N, ldc, Tile6(C_cur), &A[i], KB, B + PACKED_INDEX(1, i, KB, TILE_SIZE), m0); - }); - - if (m1 != 0) { - unpack_A(Tile23, &A[TILE_M * KB + i], KB, m1); - _tile_loadd(TMM3, Tile23, TILE_K); - - _tile_dpbssd(TMM5, TMM3, TMM0); - _tile_dpbssd(TMM7, TMM3, TMM1); - _tile_stored(TMM5, Tile5(C_cur), TILE_N * sizeof(int32_t)); - _tile_stored(TMM7, Tile7(C_cur), TILE_N * sizeof(int32_t)); - GGML_DISPATCH_BOOL(i > 0, is_acc, [&] { - acc_C::apply(C + TILE_M * ldc, ldc, Tile5(C_cur), &A[TILE_M * KB + i], KB, B + PACKED_INDEX(0, i, KB, TILE_SIZE), m1); - acc_C::apply(C + TILE_M * ldc + TILE_N, ldc, Tile7(C_cur), &A[TILE_M * KB + i], KB, B + PACKED_INDEX(1, i, KB, TILE_SIZE), m1); - }); - } - } - } - return; -} - -template ::value, int>::type = 0> -void tinygemm_kernel_amx(int M, int N, int KB, const void * RESTRICT _A, const void * RESTRICT _B, float * RESTRICT C, int ldc) { - static_assert(std::is_same::value); - const int TILE_SIZE = get_tile_size(); - - GGML_ASSERT(M <= 2 * TILE_M && N == 2 * TILE_N); - const TA * RESTRICT A = static_cast(_A); - const char * RESTRICT B = static_cast(_B); - - const int m0 = std::min(M, TILE_M); - const int m1 = std::max(M - TILE_M, 0); - //const int lda = KB * sizeof(TA); - - static thread_local int8_t Tile0[TILE_N * TILE_K]; - static thread_local int8_t Tile1[TILE_N * TILE_K]; - static thread_local int8_t Tile23[TILE_M * TILE_K]; - - // mat mul result for each group - static thread_local int32_t Tile4[TILE_M * TILE_N]; - static thread_local int32_t Tile5[TILE_M * TILE_N]; - static thread_local int32_t Tile6[TILE_M * TILE_N]; - static thread_local int32_t Tile7[TILE_M * TILE_N]; - - // sum of each QK_K block, contains 8 groups, int32 - static thread_local int32_t Sumi4[TILE_M * TILE_N]; - static thread_local int32_t Sumi5[TILE_M * TILE_N]; - static thread_local int32_t Sumi6[TILE_M * TILE_N]; - static thread_local int32_t Sumi7[TILE_M * TILE_N]; - - const int k_group_size = std::is_same::value ? 16 : 32; - for (int i = 0; i < KB; ++i) { - // step 1: accumulate the quants across 8 groups, each group with 32 - for (int k = 0; k < QK_K / k_group_size; ++k) { - GGML_DISPATCH_BOOL(k > 0, is_acc, [&] { - _tile_zero(TMM4); - _tile_zero(TMM6); - - unpack_B(Tile0, B + PACKED_INDEX(0, i, KB, TILE_SIZE), k); - _tile_loadd(TMM0, Tile0, TILE_N * VNNI_BLK); - - unpack_B(Tile1, B + PACKED_INDEX(1, i, KB, TILE_SIZE), k); - _tile_loadd(TMM1, Tile1, TILE_N * VNNI_BLK); - - unpack_A(Tile23, &A[i], KB, k, m0); - _tile_loadd(TMM2, Tile23, TILE_K); - - _tile_dpbssd(TMM4, TMM2, TMM0); - _tile_dpbssd(TMM6, TMM2, TMM1); - - _tile_stored(TMM4, Tile4, TILE_N * sizeof(int32_t)); - _tile_stored(TMM6, Tile6, TILE_N * sizeof(int32_t)); - - scale_C(Tile4, Sumi4, B + PACKED_INDEX(0, i, KB, TILE_SIZE), k, m0); - scale_C(Tile6, Sumi6, B + PACKED_INDEX(1, i, KB, TILE_SIZE), k, m0); - - if (m1 != 0) { - _tile_zero(TMM5); - _tile_zero(TMM7); - - unpack_A(Tile23, &A[TILE_M * KB + i], KB, k, m1); - _tile_loadd(TMM3, Tile23, TILE_K); - - _tile_dpbssd(TMM5, TMM3, TMM0); - _tile_dpbssd(TMM7, TMM3, TMM1); - - _tile_stored(TMM5, Tile5, TILE_N * sizeof(int32_t)); - _tile_stored(TMM7, Tile7, TILE_N * sizeof(int32_t)); - - scale_C(Tile5, Sumi5, B + PACKED_INDEX(0, i, KB, TILE_SIZE), k, m1); - scale_C(Tile7, Sumi7, B + PACKED_INDEX(1, i, KB, TILE_SIZE), k, m1); - } - }); - } - - // step 2: accmulate the mins - GGML_DISPATCH_BOOL(i > 0, is_acc, [&] { - acc_C::apply(C, ldc, Sumi4, &A[i], KB, B + PACKED_INDEX(0, i, KB, TILE_SIZE), m0); - acc_C::apply(C + TILE_N, ldc, Sumi6, &A[i], KB, B + PACKED_INDEX(1, i, KB, TILE_SIZE), m0); - if (m1 != 0) { - acc_C::apply(C + TILE_M * ldc, ldc, Sumi5, &A[TILE_M * KB + i], KB, B + PACKED_INDEX(0, i, KB, TILE_SIZE), m1); - acc_C::apply(C + TILE_M * ldc + TILE_N, ldc, Sumi7, &A[TILE_M * KB + i], KB, B + PACKED_INDEX(1, i, KB, TILE_SIZE), m1); - } - }); - } - return; -} - -} // anonymous namespace - -// get the packed tensor size for quantized weights -size_t ggml_backend_amx_get_alloc_size(const struct ggml_tensor * tensor) { - const enum ggml_type TYPE = tensor->type; - - const int K = tensor->ne[0]; // ne0: in_features - const int N = tensor->ne[1]; // ne1: out_features - - auto get_tensor_size = [&] { - size_t row_size_B{0}; - GGML_DISPATCH_QTYPES(TYPE, [&] { - row_size_B = get_row_size(K); - }); - return N * row_size_B; - }; - - if (qtype_has_amx_kernels(TYPE)) { - return get_tensor_size(); - } else { - // for f16, bf16 we don't do packing - return ggml_nbytes(tensor); - } -} - -// pack weight to vnni format -void ggml_backend_amx_convert_weight(struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { - GGML_ASSERT(offset == 0 && size == ggml_nbytes(tensor)); // only full tensor conversion is supported for now - - const enum ggml_type TYPE = tensor->type; - - const int K = tensor->ne[0]; // ne0: in_features - const int N = tensor->ne[1]; // ne1: out_features - - GGML_DISPATCH_QTYPES(TYPE, [&] { - convert_B_packed_format((void *)((char *)tensor->data + offset), (const type *)data, N, K); - }); -} - -size_t ggml_backend_amx_desired_wsize(const struct ggml_tensor * dst) { - struct ggml_tensor * src0 = dst->src[0]; - - const enum ggml_type TYPE = src0->type; - - const bool is_floating_type = TYPE == GGML_TYPE_F16; - if (is_floating_type) { - return 0; - } - - const int M = dst->ne[1]; - const int K = src0->ne[0]; - - size_t desired_wsize = 0; - - GGML_DISPATCH_QTYPES(TYPE, [&] { - const size_t row_size_A = K / blck_size * sizeof(vec_dot_type); - desired_wsize = M * row_size_A; - }); - - return desired_wsize; -} - -// NB: mixed dtype gemm with Advanced Matrix Extensions (Intel AMX) -// -// src0: weight in shape of {N, K}, quantized -// src1: input in shape of {M, K}, float32 -// dst: output in shape of {M, N}, float32 -// -// the function performs: dst = src1 @ src0.T -// -void ggml_backend_amx_mul_mat(const ggml_compute_params * params, struct ggml_tensor * dst) { - struct ggml_tensor * src0 = dst->src[0]; - struct ggml_tensor * src1 = dst->src[1]; - - const enum ggml_type TYPE = src0->type; - - // f16 only has avx512 kernels for now, - // amx kernels will be added once 6th gen xeon is released. - const bool is_floating_type = TYPE == GGML_TYPE_F16; - - const int M = dst->ne[1]; - const int N = dst->ne[0]; - const int K = src0->ne[0]; - const int ldc = dst->nb[1] / dst->nb[0]; - - if (is_floating_type) { - constexpr int BLOCK_M = 4; - constexpr int BLOCK_N = 6; - const int MB = div_up(M, BLOCK_M); - const int NB = div_up(N, BLOCK_N); - - parallel_for_ggml(params, MB * NB, [&](int begin, int end) { - GGML_DISPATCH_FLOATING_TYPES(TYPE, [&] { - for (int i = begin; i < end; ++i) { - int mb = i / NB; - int nb = i % NB; - - int mb_start = mb * BLOCK_M; - int mb_size = std::min(BLOCK_M, M - mb_start); - int nb_start = nb * BLOCK_N; - int nb_size = std::min(BLOCK_N, N - nb_start); - - switch (mb_size << 4 | nb_size) { - case 0x12: LAUNCH_TINYGEMM_KERNEL_AVX(1, 2); break; - case 0x14: LAUNCH_TINYGEMM_KERNEL_AVX(1, 4); break; - case 0x16: LAUNCH_TINYGEMM_KERNEL_AVX(1, 6); break; - case 0x22: LAUNCH_TINYGEMM_KERNEL_AVX(2, 2); break; - case 0x24: LAUNCH_TINYGEMM_KERNEL_AVX(2, 4); break; - case 0x26: LAUNCH_TINYGEMM_KERNEL_AVX(2, 6); break; - case 0x32: LAUNCH_TINYGEMM_KERNEL_AVX(3, 2); break; - case 0x34: LAUNCH_TINYGEMM_KERNEL_AVX(3, 4); break; - case 0x36: LAUNCH_TINYGEMM_KERNEL_AVX(3, 6); break; - case 0x42: LAUNCH_TINYGEMM_KERNEL_AVX(4, 2); break; - case 0x44: LAUNCH_TINYGEMM_KERNEL_AVX(4, 4); break; - case 0x46: LAUNCH_TINYGEMM_KERNEL_AVX(4, 6); break; - default: fprintf(stderr, "Unexpected block size!\n"); - } - } - }); - }); - return; - } - - // pointer to work space, used convert A from float to quantized type - void * wdata = params->wdata; - - //TODO: performance improvement: merge quant A - if (params->ith == 0) { - GGML_DISPATCH_QTYPES(TYPE, [&] { - const size_t row_size_A = K / blck_size * sizeof(vec_dot_type); - const size_t desired_wsize = M * row_size_A; - if (params->wsize < desired_wsize) { - GGML_ABORT("insufficient work space size"); - } - - // Q4_0, Q4_1, Q8_0 handles 1 TILE_K per blck_size - // Q4_K, Q5_K, Q6_K, IQ4_XS handles 8 TILE_K per blck_size - GGML_ASSERT(TILE_K == blck_size || TILE_K * 8 == blck_size); - - const float * A_data = static_cast(src1->data); - for (int m = 0; m < M; ++m) { - from_float(A_data + m * K, (char *)wdata + m * row_size_A, K); - } - }); - } - - ggml_barrier(params->threadpool); - - if (M == 1) { - // MB = 1 and handle 8 tiles in each block - constexpr int kTilesN = 4; - constexpr int BLOCK_N = TILE_N * kTilesN; - const int NB = div_up(N, BLOCK_N); - - parallel_for_ggml(params, NB, [&](int begin, int end) { - GGML_DISPATCH_QTYPES(TYPE, [&] { - const int KB = K / blck_size; - const int TILE_SIZE = get_tile_size(); - const int row_size_A = KB * sizeof(vec_dot_type); - for (int i = begin; i < end; ++i) { - int nb = i; - int nb_start = nb * BLOCK_N; - int nb_size = std::min(BLOCK_N, N - nb_start); // 32, 64, 96 - - switch (nb_size) { - //case 160: LAUNCH_TINYGEMM_KERNEL_VNNI(160); break; - case 128: LAUNCH_TINYGEMM_KERNEL_VNNI(128); break; - case 96: LAUNCH_TINYGEMM_KERNEL_VNNI(96); break; - case 64: LAUNCH_TINYGEMM_KERNEL_VNNI(64); break; - case 32: LAUNCH_TINYGEMM_KERNEL_VNNI(32); break; - default: fprintf(stderr, "Unexpected n block size!\n"); - } - } - }); - }); - return; - } - - // handle 4 tiles at a tile - constexpr int BLOCK_M = TILE_M * 2; - constexpr int BLOCK_N = TILE_N * 2; - const int MB = div_up(M, BLOCK_M); - const int NB = div_up(N, BLOCK_N); - - parallel_for_ggml(params, MB * NB, [&](int begin, int end) { - // init tile config for each thread - ggml_tile_config_init(); - - GGML_DISPATCH_QTYPES(TYPE, [&] { - const int KB = K / blck_size; - const int TILE_SIZE = get_tile_size(); - const int row_size_A = KB * sizeof(vec_dot_type); - - for (int i = begin; i < end; ++i) { - int mb = i / NB; - int nb = i % NB; - - int mb_start = mb * BLOCK_M; - int mb_size = std::min(BLOCK_M, M - mb_start); - int nb_start = nb * BLOCK_N; - int nb_size = BLOCK_N; - - tinygemm_kernel_amx( - mb_size, nb_size, KB, - (const char *)wdata + mb_start * row_size_A, - (const char *)src0->data + PACKED_INDEX(nb * 2, 0, KB, TILE_SIZE), - (float *) dst->data + mb_start * N + nb_start, ldc); - } - }); - }); -} - -#endif // if defined(__AMX_INT8__) && defined(__AVX512VNNI__) diff --git a/ggml/src/ggml-cpu/amx/mmq.h b/ggml/src/ggml-cpu/amx/mmq.h deleted file mode 100644 index baf7684773453..0000000000000 --- a/ggml/src/ggml-cpu/amx/mmq.h +++ /dev/null @@ -1,10 +0,0 @@ -#pragma once -#include "common.h" - -size_t ggml_backend_amx_desired_wsize(const struct ggml_tensor * dst); - -size_t ggml_backend_amx_get_alloc_size(const struct ggml_tensor * tensor); - -void ggml_backend_amx_convert_weight(struct ggml_tensor * tensor, const void * data, size_t offset, size_t size); - -void ggml_backend_amx_mul_mat(const struct ggml_compute_params * params, struct ggml_tensor * dst); diff --git a/ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp b/ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp index 010fc696c4df3..84eb03d32579d 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp +++ b/ggml/src/ggml-cpu/ggml-cpu-aarch64.cpp @@ -4167,7 +4167,8 @@ static void flag_aarch_prepacked_quant(int type) static const ggml::cpu::tensor_traits * ggml_aarch64_get_optimal_repack_type(const struct ggml_tensor * cur) { if (cur->type == GGML_TYPE_Q4_0) { - if (ggml_cpu_has_avx2() || (ggml_cpu_has_sve() && ggml_cpu_has_matmul_int8() && ggml_cpu_get_sve_cnt() == QK8_0)) { + //we shall just use the regular avx2 handling, no repacking + if (/*ggml_cpu_has_avx2() ||*/ (ggml_cpu_has_sve() && ggml_cpu_has_matmul_int8() && ggml_cpu_get_sve_cnt() == QK8_0)) { if (cur->ne[1] % 8 == 0) { return &ggml::cpu::aarch64::q4_0_8x8_q8_0; } diff --git a/ggml/src/ggml-cpu/ggml-cpu.c b/ggml/src/ggml-cpu/ggml-cpu.c index a0a7778628a9c..92d60cb80090d 100644 --- a/ggml/src/ggml-cpu/ggml-cpu.c +++ b/ggml/src/ggml-cpu/ggml-cpu.c @@ -10,7 +10,7 @@ #include "ggml-quants.h" #include "ggml-cpu-quants.h" #include "ggml-threading.h" -#include "amx/amx.h" +// #include "amx/amx.h" #include "ggml.h" #if defined(_MSC_VER) || defined(__MINGW32__) diff --git a/ggml/src/ggml-cpu/ggml-cpu.cpp b/ggml/src/ggml-cpu/ggml-cpu.cpp index f11399cc628ca..e23106df9012a 100644 --- a/ggml/src/ggml-cpu/ggml-cpu.cpp +++ b/ggml/src/ggml-cpu/ggml-cpu.cpp @@ -4,7 +4,7 @@ #include "ggml-cpu-aarch64.h" #include "ggml-cpu-traits.h" #include "ggml-impl.h" -#include "amx/amx.h" +// #include "amx/amx.h" #include #include @@ -33,11 +33,11 @@ std::vector& ggml_backend_cpu_get_extra_buffers_type static std::vector bufts = []() { std::vector bufts; -#if defined(__AMX_INT8__) && defined(__AVX512VNNI__) - if (ggml_backend_amx_buffer_type()) { - bufts.push_back(ggml_backend_amx_buffer_type()); - } -#endif +// #if defined(__AMX_INT8__) && defined(__AVX512VNNI__) +// if (ggml_backend_amx_buffer_type()) { +// bufts.push_back(ggml_backend_amx_buffer_type()); +// } +// #endif #ifdef GGML_USE_CPU_AARCH64 if (ggml_backend_cpu_aarch64_buffer_type()) { diff --git a/src/llama.cpp b/src/llama.cpp index 232689cb85ef4..4d44eb94b8432 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -7825,6 +7825,7 @@ static bool llm_load_tensors( } int n_moved_tensors = 0; + int n_total_tensors = 0; ggml_tensor * first_moved_tensor = nullptr; ggml_backend_buffer_type_t first_moved_from_buft = nullptr; ggml_backend_buffer_type_t first_moved_to_buft = nullptr; @@ -7909,6 +7910,7 @@ static bool llm_load_tensors( first_moved_to_buft = buft; } } + n_total_tensors++; ggml_context * ctx = ctx_for_buft(buft); @@ -9732,12 +9734,13 @@ static bool llm_load_tensors( throw std::runtime_error("unknown architecture"); } - if (n_moved_tensors > 1) { //only warn if more than 1 moved tensor - LLAMA_LOG_DEBUG("%s: tensor '%s' (%s) (and %d others) cannot be used with preferred buffer type %s, using %s instead\n", - __func__, first_moved_tensor->name, ggml_type_name(first_moved_tensor->type), n_moved_tensors - 1, - ggml_backend_buft_name(first_moved_from_buft), ggml_backend_buft_name(first_moved_to_buft)); - LLAMA_LOG_DEBUG("(This is not an error, it just means some tensors will use CPU instead.)\n"); - } + // if (n_moved_tensors > 1) { //only warn if more than 1 moved tensor + // LLAMA_LOG_DEBUG("%s: tensor '%s' (%s) (and %d others) cannot be used with preferred buffer type %s, using %s instead\n", + // __func__, first_moved_tensor->name, ggml_type_name(first_moved_tensor->type), n_moved_tensors - 1, + // ggml_backend_buft_name(first_moved_from_buft), ggml_backend_buft_name(first_moved_to_buft)); + // LLAMA_LOG_DEBUG("(This is not an error, it just means some tensors will use CPU instead.)\n"); + // } + LLAMA_LOG_DEBUG("%s: relocated tensors: %d of %d\n", __func__, n_moved_tensors, n_total_tensors); } ml.done_getting_tensors(); diff --git a/version.txt b/version.txt index 81b4747cb96c0..84a9fa9b16088 100644 --- a/version.txt +++ b/version.txt @@ -18,7 +18,7 @@ VSVersionInfo( StringStruct(u'CompanyName', u'Your Company Name'), StringStruct(u'FileDescription', u'KoboldCpp'), StringStruct(u'InternalName', u'KoboldCpp'), - StringStruct(u'LegalCopyright', u'KoboldCppIsFreeAndOpenSource'), + StringStruct(u'LegalCopyright', u'AGPLv3'), StringStruct(u'OriginalFilename', u'koboldcpp.exe'), StringStruct(u'ProductName', u'koboldcpp'), ] diff --git a/version_template.txt b/version_template.txt index a9fbe95592122..7bf97509fc03c 100644 --- a/version_template.txt +++ b/version_template.txt @@ -18,7 +18,7 @@ VSVersionInfo( StringStruct(u'CompanyName', u'Your Company Name'), StringStruct(u'FileDescription', u'KoboldCpp'), StringStruct(u'InternalName', u'KoboldCpp'), - StringStruct(u'LegalCopyright', u'KoboldCppIsFreeAndOpenSource'), + StringStruct(u'LegalCopyright', u'AGPLv3'), StringStruct(u'OriginalFilename', u'koboldcpp.exe'), StringStruct(u'ProductName', u'koboldcpp'), ]