ggml : move AMX to the CPU backend (#10570)
* ggml : move AMX to the CPU backend --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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Diego Devesa
GitHub
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7cc2d2c889
64 changed files with 514 additions and 801 deletions
196
ggml/src/ggml-cpu/amx/amx.cpp
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196
ggml/src/ggml-cpu/amx/amx.cpp
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#include "amx.h"
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#include "common.h"
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#include "mmq.h"
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#include "ggml-backend-impl.h"
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#include "ggml-backend.h"
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#include "ggml-impl.h"
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#include "ggml-cpu.h"
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#if defined(__gnu_linux__)
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#include <sys/syscall.h>
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#include <unistd.h>
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#endif
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#include <cstdlib>
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#include <cstring>
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#include <memory>
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#if defined(__AMX_INT8__) && defined(__AVX512VNNI__)
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// AMX buffer interface
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static void ggml_backend_amx_buffer_free_buffer(ggml_backend_buffer_t buffer) {
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free(buffer->context);
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}
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static void * ggml_backend_amx_buffer_get_base(ggml_backend_buffer_t buffer) {
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return (void *)(buffer->context);
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}
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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) {
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memset((char *)tensor->data + offset, value, size);
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GGML_UNUSED(buffer);
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}
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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) {
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if (qtype_has_amx_kernels(tensor->type)) {
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ggml_backend_amx_convert_weight(tensor, data, offset, size);
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} else {
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memcpy((char *)tensor->data + offset, data, size);
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}
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GGML_UNUSED(buffer);
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}
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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) {
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GGML_ASSERT(!qtype_has_amx_kernels(tensor->type));
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memcpy(data, (const char *)tensor->data + offset, size);
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GGML_UNUSED(buffer);
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}
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static bool ggml_backend_amx_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) {
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if (ggml_backend_buffer_is_host(src->buffer)) {
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if (qtype_has_amx_kernels(src->type)) {
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ggml_backend_amx_convert_weight(dst, src->data, 0, ggml_nbytes(dst));
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} else {
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memcpy(dst->data, src->data, ggml_nbytes(src));
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}
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return true;
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}
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return false;
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GGML_UNUSED(buffer);
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}
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static void ggml_backend_amx_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
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memset(buffer->context, value, buffer->size);
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}
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static ggml_backend_buffer_i ggml_backend_amx_buffer_interface = {
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/* .free_buffer = */ ggml_backend_amx_buffer_free_buffer,
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/* .get_base = */ ggml_backend_amx_buffer_get_base,
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/* .init_tensor = */ NULL, // no initialization required
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/* .memset_tensor = */ ggml_backend_amx_buffer_memset_tensor,
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/* .set_tensor = */ ggml_backend_amx_buffer_set_tensor,
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/* .get_tensor = */ ggml_backend_amx_buffer_get_tensor,
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/* .cpy_tensor = */ ggml_backend_amx_buffer_cpy_tensor,
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/* .clear = */ ggml_backend_amx_buffer_clear,
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/* .reset = */ NULL,
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};
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static const char * ggml_backend_amx_buffer_type_get_name(ggml_backend_buffer_type_t buft) {
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return "AMX";
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GGML_UNUSED(buft);
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}
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static ggml_backend_buffer_t ggml_backend_amx_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) {
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void * data = aligned_alloc(TENSOR_ALIGNMENT, size);
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if (data == NULL) {
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fprintf(stderr, "%s: failed to allocate buffer of size %zu\n", __func__, size);
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return NULL;
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}
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return ggml_backend_buffer_init(buft, ggml_backend_amx_buffer_interface, data, size);
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}
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static size_t ggml_backend_amx_buffer_type_get_alignment(ggml_backend_buffer_type_t buft) {
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return TENSOR_ALIGNMENT;
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GGML_UNUSED(buft);
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}
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static size_t ggml_backend_amx_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor* tensor) {
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return ggml_backend_amx_get_alloc_size(tensor);
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GGML_UNUSED(buft);
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}
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static bool ggml_backend_amx_buffer_type_is_host(ggml_backend_buffer_type_t buft) {
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return false;
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GGML_UNUSED(buft);
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}
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#define ARCH_GET_XCOMP_PERM 0x1022
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#define ARCH_REQ_XCOMP_PERM 0x1023
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#define XFEATURE_XTILECFG 17
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#define XFEATURE_XTILEDATA 18
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static bool ggml_amx_init() {
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#if defined(__gnu_linux__)
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if (syscall(SYS_arch_prctl, ARCH_REQ_XCOMP_PERM, XFEATURE_XTILEDATA)) {
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fprintf(stderr, "AMX is not ready to be used!\n");
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return false;
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}
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return true;
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#elif defined(_WIN32)
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return true;
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#endif
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}
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ggml_backend_buffer_type_t ggml_backend_amx_buffer_type() {
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static struct ggml_backend_buffer_type ggml_backend_buffer_type_amx = {
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/* .iface = */ {
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/* .get_name = */ ggml_backend_amx_buffer_type_get_name,
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/* .alloc_buffer = */ ggml_backend_amx_buffer_type_alloc_buffer,
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/* .get_alignment = */ ggml_backend_amx_buffer_type_get_alignment,
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/* .get_max_size = */ NULL, // defaults to SIZE_MAX
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/* .get_alloc_size = */ ggml_backend_amx_buffer_type_get_alloc_size,
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/* .is_host = */ ggml_backend_amx_buffer_type_is_host,
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},
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/* .device = */ ggml_backend_reg_dev_get(ggml_backend_cpu_reg(), 0),
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/* .context = */ NULL,
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};
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if (!ggml_amx_init()) {
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return NULL;
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}
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return &ggml_backend_buffer_type_amx;
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}
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bool ggml_backend_amx_buft_is_amx(ggml_backend_buffer_type_t buft) {
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return buft->iface.get_name == ggml_backend_amx_buffer_type_get_name;
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}
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bool ggml_backend_amx_device_supports_op(const struct ggml_tensor * op) {
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// handle only 2d gemm for now
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auto is_contiguous_2d = [](const struct ggml_tensor * t) {
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return ggml_is_contiguous(t) && t->ne[3] == 1 && t->ne[2] == 1;
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};
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switch (op->op) {
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case GGML_OP_NONE:
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case GGML_OP_RESHAPE:
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case GGML_OP_VIEW:
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case GGML_OP_PERMUTE:
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case GGML_OP_TRANSPOSE:
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return true;
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case GGML_OP_MUL_MAT: {
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const struct ggml_tensor * src0 = op->src[0];
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const struct ggml_tensor * src1 = op->src[1];
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const enum ggml_type type = src0->type;
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const int64_t ne0 = op->ne[0];
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// amx kernels enables for Q4_0, Q4_1, Q8_0, F16
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// Q4_K, Q5_K, Q6_K, IQ4_XS enabled for QK_K = 256
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bool has_amx_kernels = qtype_has_amx_kernels(type) || (type == GGML_TYPE_F16);
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bool can_use_amx =
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is_contiguous_2d(src0) && // src0 must be contiguous
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is_contiguous_2d(src1) && // src1 must be contiguous
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src1->type == GGML_TYPE_F32 && // src1 must be float32
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has_amx_kernels && // with amx kernel impls
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ne0 % (TILE_N * 2) == 0; // out_features is 32x
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return can_use_amx;
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}
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default:
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return false;
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}
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}
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#endif // defined(__AMX_INT8__) && defined(__AVX512VNNI__)
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