【AI实战】llama.cpp量化cuBLAS编译；nvcc fatal:Value ‘native‘ is not defined for option ‘gpu-architecture‘-Toy模板网

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llama.cpp量化介绍

对于使用 LLaMA 模型来说，无论从花销还是使用体验，量化这个步骤是不可或缺的。

llama.cpp 量化部署 llama 参考这篇文章：【AI实战】llama.cpp 量化部署 llama-33B

llama.cpp 编译GPU版

1.错误描述

与 cuBLAS 一起编译时，执行：

cd /notebooks/llama.cpp
make LLAMA_CUBLAS=1

报错信息如下：

# make LLAMA_CUBLAS=1
I llama.cpp build info:
I UNAME_S:  Linux
I UNAME_P:  x86_64
I UNAME_M:  x86_64
I CFLAGS:   -I.              -O3 -std=c11   -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include
I CXXFLAGS: -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include
I LDFLAGS:   -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
I CC:       cc (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
I CXX:      g++ (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0

cc  -I.              -O3 -std=c11   -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include   -c ggml.c -o ggml.o
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include -c llama.cpp -o llama.o
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include -c examples/common.cpp -o common.o
cc -I.              -O3 -std=c11   -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include   -c -o k_quants.o k_quants.c
nvcc --forward-unknown-to-host-compiler -arch=native -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_MMV_Y=1 -DK_QUANTS_PER_ITERATION=2 -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include -Wno-pedantic -c ggml-cuda.cu -o ggml-cuda.o
nvcc fatal   : Value 'native' is not defined for option 'gpu-architecture'
make: *** [Makefile:191: ggml-cuda.o] Error 1

错误信息在倒数第二行：

nvcc fatal   : Value 'native' is not defined for option 'gpu-architecture'

2.错误排查

执行下面命令参考本机的 gpu-architecture：

nvcc --list-gpu-arch

输出：

compute_35
compute_37
compute_50
compute_52
compute_53
compute_60
compute_61
compute_62
compute_70
compute_72
compute_75
compute_80
compute_86
compute_87

可以看出 ‘native’ 不在上述列表中，我猜可能是 cuda 版本的问题。

解决方法

1. 查找 native

执行：

grep -nr native *

输出：

CMakeLists.txt:41:option(LLAMA_NATIVE                     "llama: enable -march=native flag"                      OFF)
CMakeLists.txt:387:        add_compile_options(-march=native)
CMakeLists.txt:460:    add_compile_options(-mcpu=native -mtune=native)
Makefile:107:   CFLAGS   += -march=native -mtune=native
Makefile:108:   CXXFLAGS += -march=native -mtune=native
Makefile:166:   NVCCFLAGS = --forward-unknown-to-host-compiler -arch=native
Makefile:222:   CFLAGS   += -mcpu=native
Makefile:223:   CXXFLAGS += -mcpu=native
README.md:658:Termux from F-Droid offers an alternative route to execute the project on an Android device. This method empowers you to construct the project right from within the terminal, negating the requirement for a rooted device or SD Card.
convert.py:283:    # conversion because numpy doesn't natively support int4s).
convert.py:577:                    "which is not yet natively supported by GGML. "
convert.py:734:# PyTorch can't do this natively as of time of writing:
examples/server/README.md:208:### Extending or building alternative Web Front End
examples/server/json.hpp:3069:// the following utilities are natively available in C++14
flake.nix:39:          nativeBuildInputs = with pkgs; [ cmake ];
ggml.h:79:// in advance how much memory you need for your computation. Alternatively, you can allocate a large enough memory
ggml.h:144:// Alternatively, there are helper functions, such as ggml_get_f32_1d() and ggml_set_f32_1d() that can be used.
Binary file models/ggml-vocab.bin matches
pocs/vdot/vdot.cpp:85:// Alternative version of the above. Faster on my Mac (~45 us vs ~55 us per dot product),
Binary file quantize-stats matches
Binary file server matches
spm-headers/ggml.h:79:// in advance how much memory you need for your computation. Alternatively, you can allocate a large enough memory
spm-headers/ggml.h:144:// Alternatively, there are helper functions, such as ggml_get_f32_1d() and ggml_set_f32_1d() that can be used.
Binary file zh-models/33B/ggml-model-q4_0.bin matches

我们使用 make 编译，所以只需关注 Makefile 中的 native

Makefile:107:   CFLAGS   += -march=native -mtune=native
Makefile:108:   CXXFLAGS += -march=native -mtune=native
Makefile:166:   NVCCFLAGS = --forward-unknown-to-host-compiler -arch=native
Makefile:222:   CFLAGS   += -mcpu=native
Makefile:223:   CXXFLAGS += -mcpu=native

根据错误提示，不难想到是 -march=native 这里的问题。

2.修改 Makefile 源码

vim Makefile 打开文件查看对应的源码

根据我的多次尝试：

166         NVCCFLAGS = --forward-unknown-to-host-compiler -arch=native

修改为：

166         NVCCFLAGS = --forward-unknown-to-host-compiler -arch=compute_87

【说明】compute_87 是在 nvcc --list-gpu-arch 命令中的输出结果。

3.重新编译

执行：

make clean
make LLAMA_CUBLAS=1

输出：

# make LLAMA_CUBLAS=1
I llama.cpp build info:
I UNAME_S:  Linux
I UNAME_P:  x86_64
I UNAME_M:  x86_64
I CFLAGS:   -I.              -O3 -std=c11   -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include
I CXXFLAGS: -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include
I LDFLAGS:   -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
I CC:       cc (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
I CXX:      g++ (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0

cc  -I.              -O3 -std=c11   -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include   -c ggml.c -o ggml.o
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include -c llama.cpp -o llama.o
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include -c examples/common.cpp -o common.o
cc -I.              -O3 -std=c11   -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include   -c -o k_quants.o k_quants.c
nvcc --forward-unknown-to-host-compiler -arch=compute_87 -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_MMV_Y=1 -DK_QUANTS_PER_ITERATION=2 -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include -Wno-pedantic -c ggml-cuda.cu -o ggml-cuda.o
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/main/main.cpp ggml.o llama.o common.o k_quants.o ggml-cuda.o -o main  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib

====  Run ./main -h for help.  ====

g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/quantize/quantize.cpp ggml.o llama.o k_quants.o ggml-cuda.o -o quantize  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/quantize-stats/quantize-stats.cpp ggml.o llama.o k_quants.o ggml-cuda.o -o quantize-stats  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/perplexity/perplexity.cpp ggml.o llama.o common.o k_quants.o ggml-cuda.o -o perplexity  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/embedding/embedding.cpp ggml.o llama.o common.o k_quants.o ggml-cuda.o -o embedding  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include pocs/vdot/vdot.cpp ggml.o k_quants.o ggml-cuda.o -o vdot  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/train-text-from-scratch/train-text-from-scratch.cpp ggml.o llama.o k_quants.o ggml-cuda.o -o train-text-from-scratch  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/simple/simple.cpp ggml.o llama.o common.o k_quants.o ggml-cuda.o -o simple  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include -Iexamples/server examples/server/server.cpp ggml.o llama.o common.o k_quants.o ggml-cuda.o -o server  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ --shared -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/embd-input/embd-input-lib.cpp ggml.o llama.o common.o k_quants.o ggml-cuda.o -o libembdinput.so  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib
g++ -I. -I./examples -O3 -std=c++11 -fPIC -DNDEBUG -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -pthread -march=native -mtune=native -DGGML_USE_K_QUANTS -DGGML_USE_CUBLAS -I/usr/local/cuda/include -I/opt/cuda/include -I/targets/x86_64-linux/include examples/embd-input/embd-input-test.cpp ggml.o llama.o common.o k_quants.o ggml-cuda.o -o embd-input-test  -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64 -L/opt/cuda/lib64 -L/targets/x86_64-linux/lib -L. -lembdinput

编译成功！！！

测试

【AI实战】llama.cpp量化cuBLAS编译；nvcc fatal:Value ‘native‘ is not defined for option ‘gpu-architecture‘,大语言模型,llama,llama.cpp,量化

参考

1.【AI实战】llama.cpp 量化部署 llama-33B
2.https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/llama.cpp量化部署
3.https://github.com/ggerganov/whisper.cpp/issues/876
4.https://github.com/coreylowman/dfdx/pull/564
5.https://github.com/ggerganov/llama.cpp文章来源地址https://www.toymoban.com/news/detail-655084.html

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