mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-25 22:08:46 +01:00
Improve cuBLAS performance by dequantizing on the GPU (#1065)
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slaren
GitHub
parent
834695fe3a
commit
02d6988121
@ -110,6 +110,7 @@ if (APPLE AND LLAMA_ACCELERATE)
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message(WARNING "Accelerate framework not found")
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endif()
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endif()
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if (LLAMA_OPENBLAS)
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if (LLAMA_STATIC)
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set(BLA_STATIC ON)
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@ -150,6 +151,10 @@ if (LLAMA_CUBLAS)
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if (CUDAToolkit_FOUND)
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message(STATUS "cuBLAS found")
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enable_language(CUDA)
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set(GGML_CUDA_SOURCES ggml-cuda.cu ggml-cuda.h)
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add_compile_definitions(GGML_USE_CUBLAS)
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if (LLAMA_STATIC)
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@ -241,21 +246,26 @@ elseif (${CMAKE_SYSTEM_PROCESSOR} MATCHES "^(x86_64|i686|AMD64)$")
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message(STATUS "x86 detected")
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if (MSVC)
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if (LLAMA_AVX512)
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add_compile_options(/arch:AVX512)
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add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX512>)
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add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX512>)
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# MSVC has no compile-time flags enabling specific
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# AVX512 extensions, neither it defines the
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# macros corresponding to the extensions.
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# Do it manually.
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if (LLAMA_AVX512_VBMI)
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add_compile_definitions(__AVX512VBMI__)
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add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512VBMI__>)
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add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512VBMI__>)
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endif()
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if (LLAMA_AVX512_VNNI)
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add_compile_definitions(__AVX512VNNI__)
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add_compile_definitions($<$<COMPILE_LANGUAGE:C>:__AVX512VNNI__>)
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add_compile_definitions($<$<COMPILE_LANGUAGE:CXX>:__AVX512VNNI__>)
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endif()
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elseif (LLAMA_AVX2)
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add_compile_options(/arch:AVX2)
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add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX2>)
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add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX2>)
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elseif (LLAMA_AVX)
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add_compile_options(/arch:AVX)
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add_compile_options($<$<COMPILE_LANGUAGE:C>:/arch:AVX>)
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add_compile_options($<$<COMPILE_LANGUAGE:CXX>:/arch:AVX>)
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endif()
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else()
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if (LLAMA_F16C)
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@ -292,7 +302,8 @@ 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.h
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${GGML_CUDA_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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@ -314,6 +325,14 @@ if (BUILD_SHARED_LIBS)
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target_compile_definitions(llama PRIVATE LLAMA_SHARED LLAMA_BUILD)
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endif()
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if (GGML_CUDA_SOURCES)
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message(STATUS "GGML CUDA sources found, configuring CUDA architecture")
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set_property(TARGET ggml PROPERTY CUDA_ARCHITECTURES OFF)
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set_property(TARGET ggml PROPERTY CUDA_SELECT_NVCC_ARCH_FLAGS "Auto")
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set_property(TARGET llama PROPERTY CUDA_ARCHITECTURES OFF)
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endif()
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#
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# programs, examples and tests
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#
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24
Makefile
24
Makefile
@ -1,3 +1,6 @@
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# Define the default target now so that it is always the first target
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default: main quantize quantize-stats perplexity embedding vdot
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ifndef UNAME_S
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UNAME_S := $(shell uname -s)
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endif
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@ -100,6 +103,9 @@ endif
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ifdef LLAMA_CUBLAS
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CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include
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LDFLAGS += -lcublas_static -lculibos -lcudart_static -lcublasLt_static -lpthread -ldl -L/usr/local/cuda/lib64
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OBJS += ggml-cuda.o
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ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
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nvcc -arch=native -c -o $@ $<
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endif
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ifdef LLAMA_GPROF
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CFLAGS += -pg
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@ -137,8 +143,6 @@ $(info I CC: $(CCV))
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$(info I CXX: $(CXXV))
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$(info )
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default: main quantize quantize-stats perplexity embedding vdot
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#
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# Build library
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#
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@ -155,35 +159,35 @@ common.o: examples/common.cpp examples/common.h
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clean:
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rm -vf *.o main quantize quantize-stats perplexity embedding benchmark-q4_0-matmult
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main: examples/main/main.cpp ggml.o llama.o common.o
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main: examples/main/main.cpp ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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@echo
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@echo '==== Run ./main -h for help. ===='
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@echo
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quantize: examples/quantize/quantize.cpp ggml.o llama.o
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quantize: examples/quantize/quantize.cpp ggml.o llama.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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quantize-stats: examples/quantize-stats/quantize-stats.cpp ggml.o llama.o
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quantize-stats: examples/quantize-stats/quantize-stats.cpp ggml.o llama.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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perplexity: examples/perplexity/perplexity.cpp ggml.o llama.o common.o
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perplexity: examples/perplexity/perplexity.cpp ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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embedding: examples/embedding/embedding.cpp ggml.o llama.o common.o
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embedding: examples/embedding/embedding.cpp ggml.o llama.o common.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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vdot: pocs/vdot/vdot.cpp ggml.o
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vdot: pocs/vdot/vdot.cpp ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)
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libllama.so: llama.o ggml.o
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libllama.so: llama.o ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) -shared -fPIC -o $@ $^ $(LDFLAGS)
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#
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# Tests
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#
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benchmark: examples/benchmark/benchmark-q4_0-matmult.c ggml.o
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benchmark: examples/benchmark/benchmark-q4_0-matmult.c ggml.o $(OBJS)
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$(CXX) $(CXXFLAGS) $^ -o benchmark-q4_0-matmult $(LDFLAGS)
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./benchmark-q4_0-matmult
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116
ggml-cuda.cu
Normal file
116
ggml-cuda.cu
Normal file
@ -0,0 +1,116 @@
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#include <stdint.h>
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#include <cuda_fp16.h>
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#include "ggml-cuda.h"
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typedef uint16_t ggml_fp16_t;
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static_assert(sizeof(__half) == sizeof(ggml_fp16_t), "wrong fp16 size");
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#define QK4_0 32
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typedef struct {
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float d; // delta
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uint8_t qs[QK4_0 / 2]; // nibbles / quants
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} block_q4_0;
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static_assert(sizeof(block_q4_0) == sizeof(float) + QK4_0 / 2, "wrong q4_0 block size/padding");
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#define QK4_1 32
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typedef struct {
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float d; // delta
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float m; // min
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uint8_t qs[QK4_1 / 2]; // nibbles / quants
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} block_q4_1;
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static_assert(sizeof(block_q4_1) == sizeof(float) * 2 + QK4_1 / 2, "wrong q4_1 block size/padding");
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#define QK4_2 16
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typedef struct {
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__half d; // delta
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uint8_t qs[QK4_2 / 2]; // nibbles / quants
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} block_q4_2;
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static_assert(sizeof(block_q4_2) == sizeof(ggml_fp16_t) + QK4_2 / 2, "wrong q4_2 block size/padding");
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static __global__ void dequantize_block_q4_0(const void * vx, float * y) {
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const block_q4_0 * x = (const block_q4_0 *) vx;
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const int i = blockIdx.x;
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const float d = x[i].d;
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const uint8_t * pp = x[i].qs;
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for (int l = 0; l < QK4_0; l += 2) {
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const uint8_t vi = pp[l/2];
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const int8_t vi0 = vi & 0xf;
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const int8_t vi1 = vi >> 4;
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const float v0 = (vi0 - 8)*d;
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const float v1 = (vi1 - 8)*d;
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y[i*QK4_0 + l + 0] = v0;
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y[i*QK4_0 + l + 1] = v1;
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}
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}
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static __global__ void dequantize_block_q4_1(const void * vx, float * y) {
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const block_q4_1 * x = (const block_q4_1 *) vx;
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const int i = blockIdx.x;
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const float d = x[i].d;
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const float m = x[i].m;
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const uint8_t * pp = x[i].qs;
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for (int l = 0; l < QK4_1; l += 2) {
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const uint8_t vi = pp[l/2];
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const int8_t vi0 = vi & 0xf;
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const int8_t vi1 = vi >> 4;
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const float v0 = vi0*d + m;
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const float v1 = vi1*d + m;
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y[i*QK4_1 + l + 0] = v0;
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y[i*QK4_1 + l + 1] = v1;
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}
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}
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static __global__ void dequantize_block_q4_2(const void * vx, float * y) {
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const block_q4_2 * x = (const block_q4_2 *) vx;
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const int i = blockIdx.x;
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const float d = x[i].d;
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const uint8_t * pp = x[i].qs;
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for (int l = 0; l < QK4_2; l += 2) {
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const uint8_t vi = pp[l/2];
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const int8_t vi0 = vi & 0xf;
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const int8_t vi1 = vi >> 4;
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const float v0 = (vi0 - 8)*d;
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const float v1 = (vi1 - 8)*d;
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y[i*QK4_2 + l + 0] = v0;
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y[i*QK4_2 + l + 1] = v1;
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}
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}
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extern "C" {
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__host__ void dequantize_row_q4_0_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
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const int nb = k / QK4_0;
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dequantize_block_q4_0<<<nb, 1, 0, stream>>>(vx, y);
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}
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__host__ void dequantize_row_q4_1_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
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const int nb = k / QK4_1;
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dequantize_block_q4_1<<<nb, 1, 0, stream>>>(vx, y);
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}
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__host__ void dequantize_row_q4_2_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
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const int nb = k / QK4_2;
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dequantize_block_q4_2<<<nb, 1, 0, stream>>>(vx, y);
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}
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}
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11
ggml-cuda.h
Normal file
11
ggml-cuda.h
Normal file
@ -0,0 +1,11 @@
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#ifdef __cplusplus
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extern "C" {
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#endif
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void dequantize_row_q4_0_cuda(const void * vx, float * y, int k, cudaStream_t stream);
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void dequantize_row_q4_1_cuda(const void * vx, float * y, int k, cudaStream_t stream);
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void dequantize_row_q4_2_cuda(const void * vx, float * y, int k, cudaStream_t stream);
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#ifdef __cplusplus
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}
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#endif
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80
ggml.c
80
ggml.c
@ -150,23 +150,25 @@ inline static void* ggml_aligned_malloc(size_t size) {
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#elif defined(GGML_USE_CUBLAS)
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#include <cublas_v2.h>
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#include <cuda_runtime.h>
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#define CUDA_CHECK(err) \
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do { \
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cudaError_t err_ = (err); \
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if (err_ != cudaSuccess) { \
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printf("CUDA error %d at %s:%d: %s\n", err_, __FILE__, __LINE__, \
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cudaGetErrorString(err_)); \
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exit(1); \
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} \
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#include "ggml-cuda.h"
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#define CUDA_CHECK(err) \
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do { \
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cudaError_t err_ = (err); \
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if (err_ != cudaSuccess) { \
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printf("CUDA error %d at %s:%d: %s\n", err_, __FILE__, __LINE__, \
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cudaGetErrorString(err_)); \
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exit(1); \
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} \
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} while (0)
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#define CUBLAS_CHECK(err) \
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do { \
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cublasStatus_t err_ = (err); \
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if (err_ != CUBLAS_STATUS_SUCCESS) { \
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printf("cuBLAS error %d at %s:%d\n", err_, __FILE__, __LINE__); \
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exit(1); \
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} \
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#define CUBLAS_CHECK(err) \
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do { \
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cublasStatus_t err_ = (err); \
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if (err_ != CUBLAS_STATUS_SUCCESS) { \
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printf("cuBLAS error %d at %s:%d\n", err_, __FILE__, __LINE__); \
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exit(1); \
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} \
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} while (0)
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static cublasHandle_t cublasH = NULL;
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@ -177,6 +179,7 @@ static void init_cublas(void) {
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CUBLAS_CHECK(cublasCreate(&cublasH));
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CUDA_CHECK(cudaStreamCreateWithFlags(&cudaStream, cudaStreamNonBlocking));
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CUBLAS_CHECK(cublasSetStream(cublasH, cudaStream));
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// configure logging to stdout
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@ -7311,7 +7314,6 @@ static void ggml_compute_forward_mul_mat_f32(
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// copy data to host
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CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, cudaStream));
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CUDA_CHECK(cudaStreamSynchronize(cudaStream));
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#else
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// zT = y * xT
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cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasTrans,
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@ -7323,6 +7325,7 @@ static void ggml_compute_forward_mul_mat_f32(
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}
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}
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#if defined(GGML_USE_CUBLAS)
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CUDA_CHECK(cudaStreamSynchronize(cudaStream));
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CUDA_CHECK(cudaFree(d_X));
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CUDA_CHECK(cudaFree(d_Y));
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CUDA_CHECK(cudaFree(d_D));
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@ -7535,7 +7538,6 @@ static void ggml_compute_forward_mul_mat_f16_f32(
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// copy data to host
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CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, cudaStream));
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CUDA_CHECK(cudaStreamSynchronize(cudaStream));
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#else
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const float * x = wdata;
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const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
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@ -7553,6 +7555,7 @@ static void ggml_compute_forward_mul_mat_f16_f32(
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}
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#if defined(GGML_USE_CUBLAS)
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CUDA_CHECK(cudaStreamSynchronize(cudaStream));
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CUDA_CHECK(cudaFree(d_X));
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CUDA_CHECK(cudaFree(d_Y));
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CUDA_CHECK(cudaFree(d_D));
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@ -7722,13 +7725,11 @@ static void ggml_compute_forward_mul_mat_q_f32(
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return;
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}
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float * const wdata = params->wdata;
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dequantize_row_q_t const dequantize_row_q = quantize_fns[type].dequantize_row_q;
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#if defined(GGML_USE_CUBLAS)
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float *d_X = NULL;
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float *d_Y = NULL;
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float *d_D = NULL;
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float *d_Q = NULL;
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const float alpha = 1.0f;
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const float beta = 0.0f;
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const int x_ne = ne01 * ne10;
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@ -7738,10 +7739,41 @@ static void ggml_compute_forward_mul_mat_q_f32(
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CUDA_CHECK(cudaMalloc((void **)(&d_X), sizeof(float) * x_ne));
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CUDA_CHECK(cudaMalloc((void **)(&d_Y), sizeof(float) * y_ne));
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CUDA_CHECK(cudaMalloc((void **)(&d_D), sizeof(float) * d_ne));
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CUDA_CHECK(cudaMalloc((void **)(&d_Q), GGML_TYPE_SIZE[type] * x_ne / GGML_BLCK_SIZE[type]));
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void (*dequantize_row_q_cuda)(const void * x, float * y, int k, cudaStream_t stream) = NULL;
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if (type == GGML_TYPE_Q4_0) {
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dequantize_row_q_cuda = dequantize_row_q4_0_cuda;
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}
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else if (type == GGML_TYPE_Q4_1) {
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dequantize_row_q_cuda = dequantize_row_q4_1_cuda;
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}
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else if (type == GGML_TYPE_Q4_2) {
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dequantize_row_q_cuda = dequantize_row_q4_2_cuda;
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}
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else {
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GGML_ASSERT(false);
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}
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#else
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float * const wdata = params->wdata;
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dequantize_row_q_t const dequantize_row_q = quantize_fns[type].dequantize_row_q;
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#endif
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for (int64_t i03 = 0; i03 < ne03; i03++) {
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for (int64_t i02 = 0; i02 < ne02; i02++) {
|
||||
const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
|
||||
|
||||
float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
|
||||
|
||||
#if defined(GGML_USE_CUBLAS)
|
||||
// copy and dequantize on device
|
||||
CUDA_CHECK(
|
||||
cudaMemcpyAsync(d_Q, (char *) src0->data + i03*nb03 + i02*nb02,
|
||||
GGML_TYPE_SIZE[type] * x_ne / GGML_BLCK_SIZE[type], cudaMemcpyHostToDevice, cudaStream));
|
||||
|
||||
dequantize_row_q_cuda(d_Q, d_X, ne01 * ne00, cudaStream);
|
||||
CUDA_CHECK(cudaGetLastError());
|
||||
#else
|
||||
{
|
||||
size_t id = 0;
|
||||
for (int64_t i01 = 0; i01 < ne01; ++i01) {
|
||||
@ -7749,15 +7781,12 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
id += ne00;
|
||||
}
|
||||
}
|
||||
|
||||
const float * x = wdata;
|
||||
const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
|
||||
#endif
|
||||
|
||||
float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
|
||||
|
||||
#if defined(GGML_USE_CUBLAS)
|
||||
// copy data to device
|
||||
CUDA_CHECK(cudaMemcpyAsync(d_X, x, sizeof(float) * x_ne, cudaMemcpyHostToDevice, cudaStream));
|
||||
CUDA_CHECK(cudaMemcpyAsync(d_Y, y, sizeof(float) * y_ne, cudaMemcpyHostToDevice, cudaStream));
|
||||
|
||||
// compute
|
||||
@ -7770,7 +7799,6 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
|
||||
// copy data to host
|
||||
CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, cudaStream));
|
||||
CUDA_CHECK(cudaStreamSynchronize(cudaStream));
|
||||
#else
|
||||
// zT = y * xT
|
||||
cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasTrans,
|
||||
@ -7783,9 +7811,11 @@ static void ggml_compute_forward_mul_mat_q_f32(
|
||||
}
|
||||
|
||||
#if defined(GGML_USE_CUBLAS)
|
||||
CUDA_CHECK(cudaStreamSynchronize(cudaStream));
|
||||
CUDA_CHECK(cudaFree(d_X));
|
||||
CUDA_CHECK(cudaFree(d_Y));
|
||||
CUDA_CHECK(cudaFree(d_D));
|
||||
CUDA_CHECK(cudaFree(d_Q));
|
||||
#endif
|
||||
//printf("CBLAS = %f ms, %d x %d x %d x %d\n", (ggml_perf_time_us() - t0)/1000.0, ne0, ne1, ne2, ne3);
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user