mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-25 02:44:36 +00:00
ggml : add CLBlast support (#1164)
* Allow use of OpenCL GPU-based BLAS using ClBlast instead of OpenBLAS for context processing * Improve ClBlast implementation, avoid recreating buffers, remove redundant transfers * Finish merge of ClBlast support * Move CLBlast implementation to separate file Add buffer reuse code (adapted from slaren's cuda implementation) * Add q4_2 and q4_3 CLBlast support, improve code * Double CLBlast speed by disabling OpenBLAS thread workaround Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com> Co-authored-by: slaren <2141330+slaren@users.noreply.github.com> * Fix device selection env variable names * Fix cast in opencl kernels * Add CLBlast to CMakeLists.txt * Replace buffer pool with static buffers a, b, qb, c Fix compile warnings * Fix typos, use GGML_TYPE defines, improve code * Improve btype dequant kernel selection code, add error if type is unsupported * Improve code quality * Move internal stuff out of header * Use internal enums instead of CLBlast enums * Remove leftover C++ includes and defines * Make event use easier to read Co-authored-by: Henri Vasserman <henv@hot.ee> * Use c compiler for opencl files * Simplify code, fix include * First check error, then release event * Make globals static, fix indentation * Rename dequant kernels file to conform with other file names * Fix import cl file name --------- Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com> Co-authored-by: slaren <2141330+slaren@users.noreply.github.com> Co-authored-by: Henri Vasserman <henv@hot.ee> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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@ -67,6 +67,7 @@ endif()
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option(LLAMA_ACCELERATE "llama: enable Accelerate framework" ON)
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option(LLAMA_OPENBLAS "llama: use OpenBLAS" OFF)
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option(LLAMA_CUBLAS "llama: use cuBLAS" OFF)
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option(LLAMA_CLBLAST "llama: use CLBlast" OFF)
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option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE})
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option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE})
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@ -168,6 +169,21 @@ if (LLAMA_CUBLAS)
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endif()
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endif()
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if (LLAMA_CLBLAST)
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find_package(CLBlast)
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if (CLBlast_FOUND)
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message(STATUS "CLBlast found")
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set(GGML_OPENCL_SOURCES ggml-opencl.c ggml-opencl.h)
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add_compile_definitions(GGML_USE_CLBLAST)
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set(LLAMA_EXTRA_LIBS ${LLAMA_EXTRA_LIBS} clblast)
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else()
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message(WARNING "CLBlast not found")
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endif()
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endif()
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if (LLAMA_ALL_WARNINGS)
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if (NOT MSVC)
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set(c_flags
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@ -307,7 +323,8 @@ endif()
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add_library(ggml OBJECT
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ggml.c
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ggml.h
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${GGML_CUDA_SOURCES})
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${GGML_CUDA_SOURCES}
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${GGML_OPENCL_SOURCES})
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target_include_directories(ggml PUBLIC .)
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target_compile_features(ggml PUBLIC c_std_11) # don't bump
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11
Makefile
11
Makefile
@ -105,14 +105,21 @@ ifdef LLAMA_OPENBLAS
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LDFLAGS += -lopenblas
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endif
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ifdef LLAMA_CUBLAS
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CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include
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LDFLAGS += -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L$(CUDA_PATH)/targets/x86_64-linux/lib
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CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(CUDA_PATH)/targets/x86_64-linux/include
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LDFLAGS += -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L$(CUDA_PATH)/targets/x86_64-linux/lib
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OBJS += ggml-cuda.o
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NVCC = nvcc
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NVCCFLAGS = --forward-unknown-to-host-compiler -arch=native
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ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
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$(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -Wno-pedantic -c $< -o $@
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endif
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ifdef LLAMA_CLBLAST
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CFLAGS += -DGGML_USE_CLBLAST
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LDFLAGS += -lclblast -lOpenCL
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OBJS += ggml-opencl.o
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ggml-opencl.o: ggml-opencl.c ggml-opencl.h
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$(CC) $(CFLAGS) -c $< -o $@
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endif
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ifdef LLAMA_GPROF
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CFLAGS += -pg
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CXXFLAGS += -pg
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84
ggml-opencl-dequant.cl
Normal file
84
ggml-opencl-dequant.cl
Normal file
@ -0,0 +1,84 @@
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#define MULTILINE_QUOTE(...) #__VA_ARGS__
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const char * clblast_dequant = MULTILINE_QUOTE(
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struct block_q4_0
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{
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float d;
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uchar qs[16];
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};
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__kernel void dequantize_row_q4_0(__global struct block_q4_0* blocks, __global float* result) {
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const uint i = get_global_id(0) / 32;
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const uint l = get_local_id(0);
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const float d = blocks[i].d;
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const uchar vi = blocks[i].qs[l];
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const uint index = i*32 + l*2;
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result[index + 0] = ((vi & 0xf) - 8)*d;
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result[index + 1] = ((vi >> 4) - 8)*d;
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}
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struct block_q4_1
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{
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float d;
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float m;
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uchar qs[16];
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};
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__kernel void dequantize_row_q4_1(__global struct block_q4_1* blocks, __global float* result) {
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const uint i = get_global_id(0) / 32;
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const uint l = get_local_id(0);
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const float d = blocks[i].d;
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const float m = blocks[i].m;
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const uchar vi = blocks[i].qs[l];
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const uint index = i*32 + l*2;
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result[index + 0] = (vi & 0xf) * d + m;
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result[index + 1] = (vi >> 4) * d + m;
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}
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struct block_q4_2
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{
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ushort d;
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uchar qs[8];
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};
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__kernel void dequantize_row_q4_2(__global struct block_q4_2* blocks, __global float* result) {
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const uint i = get_global_id(0) / 16;
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const uint l = get_local_id(0);
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const float d = vload_half(0, (__global half*) &blocks[i].d);;
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const uchar vi = blocks[i].qs[l];
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const uint index = i*16 + l*2;
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result[index + 0] = ((vi & 0xf) - 8)*d;
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result[index + 1] = ((vi >> 4) - 8)*d;
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}
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struct block_q4_3
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{
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ushort d;
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ushort m;
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uchar qs[8];
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};
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__kernel void dequantize_row_q4_3(__global struct block_q4_3* blocks, __global float* result) {
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const uint i = get_global_id(0) / 16;
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const uint l = get_local_id(0);
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const float d = vload_half(0, (__global half*) &(blocks[i].d));
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const float m = vload_half(0, (__global half*) &(blocks[i].m));
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const uchar vi = blocks[i].qs[l];
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const uint index = i*16 + l*2;
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result[index + 0] = (vi & 0xf) * d + m;
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result[index + 1] = (vi >> 4) * d + m;
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}
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);
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216
ggml-opencl.c
Normal file
216
ggml-opencl.c
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@ -0,0 +1,216 @@
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#include "ggml-opencl.h"
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#define CL_TARGET_OPENCL_VERSION 110
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#include <clblast_c.h>
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#include <stdio.h>
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#include <string.h>
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#include "ggml.h"
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#include "ggml-opencl-dequant.cl"
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#define CL_CHECK(err, name) \
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do { \
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cl_int err_ = (err); \
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if (err_ != CL_SUCCESS) { \
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fprintf(stderr, "OpenCL %s error %d at %s:%d\n", name, err_, __FILE__, __LINE__); \
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exit(1); \
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} \
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} while (0)
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static cl_platform_id platform;
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static cl_device_id device;
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static cl_context context;
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static cl_command_queue queue;
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static cl_program program;
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static cl_kernel kernel_q4_0, kernel_q4_1, kernel_q4_2, kernel_q4_3;
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static cl_mem cl_buffer_a, cl_buffer_qb, cl_buffer_b, cl_buffer_c;
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static size_t cl_size_a = 0, cl_size_qb = 0, cl_size_b = 0, cl_size_c = 0;
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static cl_program build_program_from_source(cl_context ctx, cl_device_id dev, const char* program_buffer) {
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cl_program p;
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char *program_log;
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size_t program_size, log_size;
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int err;
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program_size = strlen(program_buffer);
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p = clCreateProgramWithSource(ctx, 1, (const char**)&program_buffer, &program_size, &err);
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if(err < 0) {
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fprintf(stderr, "OpenCL error creating program");
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exit(1);
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}
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err = clBuildProgram(p, 0, NULL, NULL, NULL, NULL);
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if(err < 0) {
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clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size);
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program_log = (char*) malloc(log_size + 1);
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program_log[log_size] = '\0';
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clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, log_size + 1, program_log, NULL);
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printf("%s\n", program_log);
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free(program_log);
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exit(1);
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}
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return p;
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}
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void ggml_cl_init(void) {
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cl_int err = 0;
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char * GGML_CLBLAST_PLATFORM = getenv("GGML_CLBLAST_PLATFORM");
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char * GGML_CLBLAST_DEVICE = getenv("GGML_CLBLAST_DEVICE");
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int plat_num = (GGML_CLBLAST_PLATFORM == NULL ? 0 : atoi(GGML_CLBLAST_PLATFORM));
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int dev_num = (GGML_CLBLAST_DEVICE == NULL ? 0 : atoi(GGML_CLBLAST_DEVICE));
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printf("\nInitializing CLBlast (First Run)...");
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printf("\nAttempting to use: Platform=%d, Device=%d (If invalid, program will crash)\n",plat_num,dev_num);
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cl_uint num_platforms;
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clGetPlatformIDs(0, NULL, &num_platforms);
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cl_platform_id* platforms = (cl_platform_id*)malloc(num_platforms*sizeof(cl_platform_id));
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clGetPlatformIDs(num_platforms, platforms, NULL);
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platform = platforms[plat_num];
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char platform_buffer[1024];
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clGetPlatformInfo(platform, CL_PLATFORM_NAME, sizeof(platform_buffer), &platform_buffer, NULL);
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cl_uint num_devices;
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clGetDeviceIDs(platform, CL_DEVICE_TYPE_ALL, 0, NULL, &num_devices);
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cl_device_id* devices = (cl_device_id*)malloc(num_devices*sizeof(cl_device_id));
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clGetDeviceIDs(platform, CL_DEVICE_TYPE_ALL, num_devices, devices, NULL);
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device = devices[dev_num];
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char device_buffer[1024];
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clGetDeviceInfo(device, CL_DEVICE_NAME, sizeof(device_buffer), &device_buffer, NULL);
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printf("Using Platform: %s Device: %s\n", platform_buffer, device_buffer);
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context = clCreateContext(NULL, 1, &device, NULL, NULL, &err);
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CL_CHECK(err, "clCreateContext");
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queue = clCreateCommandQueue(context, device, CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE, &err);
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CL_CHECK(err, "clCreateCommandQueue");
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free(platforms);
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free(devices);
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program = build_program_from_source(context, device, clblast_dequant);
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// Prepare dequantize kernels
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kernel_q4_0 = clCreateKernel(program, "dequantize_row_q4_0", &err);
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CL_CHECK(err, "clCreateKernel");
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kernel_q4_1 = clCreateKernel(program, "dequantize_row_q4_1", &err);
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CL_CHECK(err, "clCreateKernel");
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kernel_q4_2 = clCreateKernel(program, "dequantize_row_q4_2", &err);
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CL_CHECK(err, "clCreateKernel");
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kernel_q4_3 = clCreateKernel(program, "dequantize_row_q4_3", &err);
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CL_CHECK(err, "clCreateKernel");
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}
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static void ggml_cl_malloc(size_t req_size, size_t* cur_size, cl_mem_flags flags, cl_mem* buf) {
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if (req_size <= *cur_size) {
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return;
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}
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// Reallocate buffer with enough space
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if (*cur_size > 0) {
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clReleaseMemObject(*buf);
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}
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cl_int err;
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*buf = clCreateBuffer(context, flags, req_size, NULL, &err);
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*cur_size = req_size;
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CL_CHECK(err, "clCreateBuffer");
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}
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void ggml_cl_sgemm_wrapper(
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const enum ggml_blas_order order, const enum ggml_blas_op trans_a, const enum ggml_blas_op trans_b,
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const int m, const int n, const int k,
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const float alpha, const void *host_a, const int lda,
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const float *host_b, const int ldb, const float beta,
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float *host_c, const int ldc, const int btype) {
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cl_int err = 0;
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cl_kernel kernel;
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size_t global = n * k, local, size_qb;
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bool dequant;
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switch (btype) {
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case GGML_TYPE_F32:
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dequant = false;
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break;
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case GGML_TYPE_Q4_0:
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dequant = true;
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kernel = kernel_q4_0;
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local = 16;
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size_qb = global * (sizeof(float) + local) / 32;
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break;
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case GGML_TYPE_Q4_1:
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dequant = true;
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kernel = kernel_q4_1;
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local = 16;
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size_qb = global * (sizeof(float) * 2 + local) / 32;
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break;
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case GGML_TYPE_Q4_2:
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dequant = true;
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kernel = kernel_q4_2;
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local = 8;
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size_qb = global * (sizeof(short) + local) / 16;
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break;
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case GGML_TYPE_Q4_3:
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dequant = true;
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kernel = kernel_q4_3;
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local = 8;
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size_qb = global * (sizeof(short) * 2 + local) / 16;
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break;
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default:
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fprintf(stderr, "Error: Unsupported OpenCL btype %d\n", btype);
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abort();
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}
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const size_t size_a = m * k * sizeof(float);
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const size_t size_b = n * k * sizeof(float);
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const size_t size_c = m * n * sizeof(float);
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// Prepare buffers
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ggml_cl_malloc(size_a, &cl_size_a, CL_MEM_READ_ONLY, &cl_buffer_a);
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if (dequant) {
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ggml_cl_malloc(size_qb, &cl_size_qb, CL_MEM_READ_ONLY, &cl_buffer_qb);
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}
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ggml_cl_malloc(size_b, &cl_size_b, CL_MEM_READ_WRITE, &cl_buffer_b);
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ggml_cl_malloc(size_c, &cl_size_c, CL_MEM_WRITE_ONLY, &cl_buffer_c);
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cl_event ev_a, ev_qb, ev_b;
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if (dequant) {
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err = clSetKernelArg(kernel, 0, sizeof(cl_mem), &cl_buffer_qb);
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err |= clSetKernelArg(kernel, 1, sizeof(cl_mem), &cl_buffer_b);
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CL_CHECK(err, "clSetKernelArg");
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clEnqueueWriteBuffer(queue, cl_buffer_qb, CL_FALSE, 0, size_qb, host_b, 0, NULL, &ev_qb);
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} else {
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clEnqueueWriteBuffer(queue, cl_buffer_b, CL_FALSE, 0, size_b, host_b, 0, NULL, &ev_b);
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}
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clEnqueueWriteBuffer(queue, cl_buffer_a, CL_FALSE, 0, size_a, host_a, 0, NULL, &ev_a);
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if (dequant) {
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err = clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &global, &local, 1, &ev_qb, &ev_b);
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CL_CHECK(err, "clEnqueueNDRangeKernel");
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clReleaseEvent(ev_qb);
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}
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clWaitForEvents(1, &ev_a);
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clWaitForEvents(1, &ev_b);
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clReleaseEvent(ev_a);
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clReleaseEvent(ev_b);
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cl_event ev_sgemm;
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CLBlastSgemm((CLBlastLayout)order,
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(CLBlastTranspose)trans_a, (CLBlastTranspose)trans_b,
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m, n, k,
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alpha,
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cl_buffer_a, 0, lda,
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cl_buffer_b, 0, ldb,
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beta,
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cl_buffer_c, 0, ldc,
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&queue, &ev_sgemm);
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cl_event ev_c;
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clEnqueueReadBuffer(queue, cl_buffer_c, CL_TRUE, 0, size_c, host_c, 1, &ev_sgemm, &ev_c);
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// Wait for completion
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clWaitForEvents(1, &ev_c);
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clReleaseEvent(ev_sgemm);
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clReleaseEvent(ev_c);
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}
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24
ggml-opencl.h
Normal file
24
ggml-opencl.h
Normal file
@ -0,0 +1,24 @@
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#pragma once
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#ifdef __cplusplus
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extern "C" {
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#endif
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void ggml_cl_init(void);
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enum ggml_blas_order {
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GGML_BLAS_ORDER_ROW_MAJOR = 101,
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GGML_BLAS_ORDER_COLUMN_MAJOR = 102,
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};
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enum ggml_blas_op {
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GGML_BLAS_OP_N = 111,
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GGML_BLAS_OP_T = 112,
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GGML_BLAS_OP_C = 113,
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};
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|
||||
void ggml_cl_sgemm_wrapper(const enum ggml_blas_order order, const enum ggml_blas_op trans_a, const enum ggml_blas_op trans_b, const int m, const int n, const int k, const float alpha, const void *host_a, const int lda, const float *host_b, const int ldb, const float beta, float *host_c, const int ldc, const int btype);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
#endif
|
||||
68
ggml.c
68
ggml.c
@ -149,6 +149,8 @@ inline static void* ggml_aligned_malloc(size_t size) {
|
||||
#include <cblas.h>
|
||||
#elif defined(GGML_USE_CUBLAS)
|
||||
#include "ggml-cuda.h"
|
||||
#elif defined(GGML_USE_CLBLAST)
|
||||
#include "ggml-opencl.h"
|
||||
#endif
|
||||
|
||||
#undef MIN
|
||||
@ -4363,6 +4365,8 @@ struct ggml_context * ggml_init(struct ggml_init_params params) {
|
||||
// initialize cuBLAS
|
||||
#if defined(GGML_USE_CUBLAS)
|
||||
ggml_init_cublas();
|
||||
#elif defined(GGML_USE_CLBLAST)
|
||||
ggml_cl_init();
|
||||
#endif
|
||||
|
||||
is_first_call = false;
|
||||
@ -8104,7 +8108,7 @@ static void ggml_compute_forward_rms_norm(
|
||||
|
||||
// ggml_compute_forward_mul_mat
|
||||
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
|
||||
// helper function to determine if it is better to use BLAS or not
|
||||
// for large matrices, BLAS is faster
|
||||
static bool ggml_compute_forward_mul_mat_use_blas(
|
||||
@ -8129,6 +8133,7 @@ static bool ggml_compute_forward_mul_mat_use_blas(
|
||||
|
||||
return false;
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
static void ggml_compute_forward_mul_mat_f32(
|
||||
@ -8144,7 +8149,7 @@ static void ggml_compute_forward_mul_mat_f32(
|
||||
const int64_t ne02 = src0->ne[2];
|
||||
const int64_t ne03 = src0->ne[3];
|
||||
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
|
||||
const int64_t ne10 = src1->ne[0];
|
||||
#endif
|
||||
const int64_t ne11 = src1->ne[1];
|
||||
@ -8201,7 +8206,7 @@ static void ggml_compute_forward_mul_mat_f32(
|
||||
// nb01 >= nb00 - src0 is not transposed
|
||||
// compute by src0 rows
|
||||
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
|
||||
if (ggml_compute_forward_mul_mat_use_blas(src0, src1, dst)) {
|
||||
if (params->ith != 0) {
|
||||
return;
|
||||
@ -8250,8 +8255,15 @@ static void ggml_compute_forward_mul_mat_f32(
|
||||
|
||||
// copy data to host
|
||||
CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, g_cudaStream));
|
||||
#else
|
||||
#elif defined(GGML_USE_CLBLAST)
|
||||
// zT = y * xT
|
||||
ggml_cl_sgemm_wrapper(GGML_BLAS_ORDER_ROW_MAJOR, GGML_BLAS_OP_N, GGML_BLAS_OP_T,
|
||||
ne11, ne01, ne10,
|
||||
1.0f, y, ne10,
|
||||
x, ne10,
|
||||
0.0f, d, ne01,
|
||||
GGML_TYPE_F32);
|
||||
#else
|
||||
cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasTrans,
|
||||
ne11, ne01, ne10,
|
||||
1.0f, y, ne10,
|
||||
@ -8395,7 +8407,7 @@ static void ggml_compute_forward_mul_mat_f16_f32(
|
||||
// nb01 >= nb00 - src0 is not transposed
|
||||
// compute by src0 rows
|
||||
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
|
||||
if (ggml_compute_forward_mul_mat_use_blas(src0, src1, dst)) {
|
||||
GGML_ASSERT(nb10 == sizeof(float));
|
||||
|
||||
@ -8472,6 +8484,19 @@ static void ggml_compute_forward_mul_mat_f16_f32(
|
||||
|
||||
// copy data to host
|
||||
CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, g_cudaStream));
|
||||
#elif defined(GGML_USE_CLBLAST)
|
||||
const float * x = wdata;
|
||||
const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
|
||||
|
||||
float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
|
||||
|
||||
// zT = y * xT
|
||||
ggml_cl_sgemm_wrapper(GGML_BLAS_ORDER_ROW_MAJOR, GGML_BLAS_OP_N, GGML_BLAS_OP_T,
|
||||
ne11, ne01, ne10,
|
||||
1.0f, y, ne10,
|
||||
x, ne10,
|
||||
0.0f, d, ne01,
|
||||
GGML_TYPE_F32);
|
||||
#else
|
||||
const float * x = wdata;
|
||||
const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
|
||||
@ -8646,7 +8671,7 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
// nb01 >= nb00 - src0 is not transposed
|
||||
// compute by src0 rows
|
||||
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
|
||||
if (ggml_compute_forward_mul_mat_use_blas(src0, src1, dst)) {
|
||||
if (params->ith != 0) {
|
||||
return;
|
||||
@ -8698,7 +8723,7 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
else {
|
||||
GGML_ASSERT(false);
|
||||
}
|
||||
#else
|
||||
#elif !defined(GGML_USE_CLBLAST)
|
||||
float * const wdata = params->wdata;
|
||||
dequantize_row_q_t const dequantize_row_q = quantize_fns[type].dequantize_row_q;
|
||||
#endif
|
||||
@ -8717,6 +8742,8 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
|
||||
dequantize_row_q_cuda(d_Q, d_X, ne01 * ne00, g_cudaStream);
|
||||
CUDA_CHECK(cudaGetLastError());
|
||||
#elif defined(GGML_USE_CLBLAST)
|
||||
const void* x = (char *) src0->data + i03*nb03 + i02*nb02;
|
||||
#else
|
||||
{
|
||||
size_t id = 0;
|
||||
@ -8743,8 +8770,15 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
|
||||
// copy data to host
|
||||
CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, g_cudaStream));
|
||||
#else
|
||||
#elif defined(GGML_USE_CLBLAST)
|
||||
// zT = y * xT
|
||||
ggml_cl_sgemm_wrapper(GGML_BLAS_ORDER_ROW_MAJOR, GGML_BLAS_OP_N, GGML_BLAS_OP_T,
|
||||
ne11, ne01, ne10,
|
||||
1.0f, y, ne10,
|
||||
x, ne10,
|
||||
0.0f, d, ne01,
|
||||
type);
|
||||
#else
|
||||
cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasTrans,
|
||||
ne11, ne01, ne10,
|
||||
1.0f, y, ne10,
|
||||
@ -11583,7 +11617,7 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
|
||||
size_t cur = 0;
|
||||
|
||||
if (node->src0->type == GGML_TYPE_F16 && node->src1->type == GGML_TYPE_F32) {
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
|
||||
if (ggml_compute_forward_mul_mat_use_blas(node->src0, node->src1, node)) {
|
||||
node->n_tasks = 1; // TODO: this actually is doing nothing
|
||||
// the threads are still spinning
|
||||
@ -11600,7 +11634,7 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
|
||||
} else if (node->src0->type == GGML_TYPE_F32 && node->src1->type == GGML_TYPE_F32) {
|
||||
cur = 0;
|
||||
} else if (ggml_is_quantized(node->src0->type) && node->src1->type == GGML_TYPE_F32) {
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
|
||||
if (ggml_compute_forward_mul_mat_use_blas(node->src0, node->src1, node)) {
|
||||
node->n_tasks = 1;
|
||||
cur = GGML_TYPE_SIZE[GGML_TYPE_F32]*(node->src0->ne[0]*node->src0->ne[1]);
|
||||
@ -13100,7 +13134,7 @@ int ggml_cpu_has_wasm_simd(void) {
|
||||
}
|
||||
|
||||
int ggml_cpu_has_blas(void) {
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS)
|
||||
#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
|
||||
return 1;
|
||||
#else
|
||||
return 0;
|
||||
@ -13115,6 +13149,18 @@ int ggml_cpu_has_cublas(void) {
|
||||
#endif
|
||||
}
|
||||
|
||||
int ggml_cpu_has_clblast(void) {
|
||||
#if defined(GGML_USE_CLBLAST)
|
||||
return 1;
|
||||
#else
|
||||
return 0;
|
||||
#endif
|
||||
}
|
||||
|
||||
int ggml_cpu_has_gpublas(void) {
|
||||
return ggml_cpu_has_cublas() || ggml_cpu_has_clblast();
|
||||
}
|
||||
|
||||
int ggml_cpu_has_sse3(void) {
|
||||
#if defined(__SSE3__)
|
||||
return 1;
|
||||
|
||||
3
ggml.h
3
ggml.h
@ -858,10 +858,11 @@ extern "C" {
|
||||
GGML_API int ggml_cpu_has_wasm_simd (void);
|
||||
GGML_API int ggml_cpu_has_blas (void);
|
||||
GGML_API int ggml_cpu_has_cublas (void);
|
||||
GGML_API int ggml_cpu_has_clblast (void);
|
||||
GGML_API int ggml_cpu_has_gpublas (void);
|
||||
GGML_API int ggml_cpu_has_sse3 (void);
|
||||
GGML_API int ggml_cpu_has_vsx (void);
|
||||
|
||||
|
||||
//
|
||||
// Internal types and functions exposed for tests and benchmarks
|
||||
//
|
||||
|
||||
@ -1085,7 +1085,7 @@ static bool llama_eval_internal(
|
||||
// for big prompts, if BLAS is enabled, it is better to use only one thread
|
||||
// otherwise, the threads are spin-lock waiting for the BLAS calls and are degrading the performance
|
||||
ggml_cgraph gf = {};
|
||||
gf.n_threads = N >= 32 && ggml_cpu_has_blas() && !ggml_cpu_has_cublas() ? 1 : n_threads;
|
||||
gf.n_threads = N >= 32 && ggml_cpu_has_blas() && !ggml_cpu_has_gpublas() ? 1 : n_threads;
|
||||
|
||||
struct ggml_tensor * embd = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, N);
|
||||
memcpy(embd->data, tokens, N*ggml_element_size(embd));
|
||||
|
||||
Loading…
Reference in New Issue
Block a user