CUDA: Quantized matrix matrix multiplication (#2160)
* mmq implementation for non k-quants * q6_K * q2_K * q3_k * q4_K * vdr * q5_K * faster q8_1 loading * loop unrolling * add __restrict__ * q2_K sc_high * GGML_CUDA_MMQ_Y * Updated Makefile * Update Makefile * DMMV_F16 -> F16 * Updated README, CMakeLists * Fix CMakeLists.txt * Fix CMakeLists.txt * Fix multi GPU out-of-bounds
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Johannes Gäßler
GitHub
parent
9baf9ef304
commit
11f3ca06b8
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@ -67,7 +67,9 @@ endif()
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option(LLAMA_ACCELERATE "llama: enable Accelerate framework" ON)
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option(LLAMA_BLAS "llama: use BLAS" OFF)
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set(LLAMA_BLAS_VENDOR "Generic" CACHE STRING "llama: BLAS library vendor")
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option(LLAMA_CUBLAS "llama: use cuBLAS" OFF)
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option(LLAMA_CUBLAS "llama: use CUDA" OFF)
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option(LLAMA_CUDA_CUBLAS "llama: use cuBLAS for prompt processing" OFF)
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set(LLAMA_CUDA_MMQ_Y "64" CACHE STRING "llama: y tile size for mmq CUDA kernels")
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option(LLAMA_CUDA_FORCE_DMMV "llama: use dmmv instead of mmvq CUDA kernels" OFF)
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set(LLAMA_CUDA_DMMV_X "32" CACHE STRING "llama: x stride for dmmv CUDA kernels")
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set(LLAMA_CUDA_MMV_Y "1" CACHE STRING "llama: y block size for mmv CUDA kernels")
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@ -251,6 +253,10 @@ if (LLAMA_CUBLAS)
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set(GGML_SOURCES_CUDA ggml-cuda.cu ggml-cuda.h)
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add_compile_definitions(GGML_USE_CUBLAS)
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if (LLAMA_CUDA_CUBLAS)
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add_compile_definitions(GGML_CUDA_CUBLAS)
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endif()
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add_compile_definitions(GGML_CUDA_MMQ_Y=${LLAMA_CUDA_MMQ_Y})
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if (LLAMA_CUDA_FORCE_DMMV)
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add_compile_definitions(GGML_CUDA_FORCE_DMMV)
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endif()
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15
Makefile
15
Makefile
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@ -194,7 +194,7 @@ ifdef LLAMA_CUBLAS
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CXXFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I$(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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NVCCFLAGS = --forward-unknown-to-host-compiler
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NVCCFLAGS = --forward-unknown-to-host-compiler -use_fast_math
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ifdef LLAMA_CUDA_NVCC
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NVCC = $(LLAMA_CUDA_NVCC)
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else
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@ -220,14 +220,25 @@ else ifdef LLAMA_CUDA_DMMV_Y
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else
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NVCCFLAGS += -DGGML_CUDA_MMV_Y=1
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endif # LLAMA_CUDA_MMV_Y
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ifdef LLAMA_CUDA_F16
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NVCCFLAGS += -DGGML_CUDA_F16
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endif # LLAMA_CUDA_F16
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ifdef LLAMA_CUDA_DMMV_F16
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NVCCFLAGS += -DGGML_CUDA_DMMV_F16
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NVCCFLAGS += -DGGML_CUDA_F16
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endif # LLAMA_CUDA_DMMV_F16
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ifdef LLAMA_CUDA_KQUANTS_ITER
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NVCCFLAGS += -DK_QUANTS_PER_ITERATION=$(LLAMA_CUDA_KQUANTS_ITER)
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else
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NVCCFLAGS += -DK_QUANTS_PER_ITERATION=2
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endif
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ifdef LLAMA_CUDA_MMQ_Y
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NVCCFLAGS += -DGGML_CUDA_MMQ_Y=$(LLAMA_CUDA_MMQ_Y)
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else
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NVCCFLAGS += -DGGML_CUDA_MMQ_Y=64
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endif # LLAMA_CUDA_MMQ_Y
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ifdef LLAMA_CUDA_CUBLAS
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NVCCFLAGS += -DGGML_CUDA_CUBLAS
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endif # LLAMA_CUDA_CUBLAS
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ifdef LLAMA_CUDA_CCBIN
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NVCCFLAGS += -ccbin $(LLAMA_CUDA_CCBIN)
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endif
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@ -402,10 +402,12 @@ Building the program with BLAS support may lead to some performance improvements
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| Option | Legal values | Default | Description |
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|-------------------------|------------------------|---------|-------------|
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| LLAMA_CUDA_CUBLAS | Boolean | false | Use cuBLAS instead of custom CUDA kernels for prompt processing. Faster for all quantization formats except for q4_0 and q8_0, especially for k-quants. Increases VRAM usage (700 MiB for 7b, 970 MiB for 13b, 1430 MiB for 33b). |
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| LLAMA_CUDA_MMQ_Y | Positive integer >= 32 | 64 | Tile size in y direction when using the custom CUDA kernels for prompt processing. Higher values can be faster depending on the amount of shared memory available. Power of 2 heavily recommended. |
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| LLAMA_CUDA_FORCE_DMMV | Boolean | false | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. |
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| LLAMA_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. |
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| LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants. |
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| LLAMA_CUDA_DMMV_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels. Can improve performance on relatively recent GPUs. |
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| LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants. |
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| LLAMA_CUDA_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs. |
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| LLAMA_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. |
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- #### CLBlast
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1590
ggml-cuda.cu
1590
ggml-cuda.cu
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