Requirements
The TensorFlow Python API supports Python 2.7 and Python 3.3+.
The GPU version works best with Cuda Toolkit 8.0 and cuDNN v5.1. Other versions are supported (Cuda toolkit >= 7.0 and cuDNN >= v3) only when installing from sources. Please see Cuda installation for details. For Mac OS X, please see Setup GPU for Mac.
本机环境
操作系统： Linux Mint 18.1 Serena
CPU： Intel® Core™ i5-3210M CPU @ 2.50GHz
GPU： GeForce GT 635M
进入刚刚下载的目录，并在终端中运行
Run sudo sh cuda_8.0.44_linux.run
Follow the command-line prompts
在安装过程中会询问是否安装显卡驱动，由于我们在第一步中已经安装，所以我们选择no（不安装）
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Do you accept the previously read EULA? (accept/decline/quit): accept You are attempting to install on an unsupported configuration. Do you wish to continue? ((y)es/(n)o) [ default is no ]: y Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 352.39? ((y)es/(n)o/(q)uit): n Install the CUDA 8.0 Toolkit? ((y)es/(n)o/(q)uit): y Enter Toolkit Location [ default is /usr/local/cuda-8.0 ]: Do you want to install a symbolic link at /usr/local/cuda? ((y)es/(n)o/(q)uit): y Install the CUDA 8.0 Samples? ((y)es/(n)o/(q)uit): y Enter CUDA Samples Location [ default is /home/kyle ]:
Installing the CUDA Toolkit in /usr/local/cuda-8.0 ... Missing recommended library: libGLU.so Missing recommended library: libX11.so Missing recommended library: libXi.so Missing recommended library: libXmu.so Missing recommended library: libGL.so
Installing the CUDA Samples in /home/kyle ... Copying samples to /home/kyle/NVIDIA_CUDA-8.0_Samples now... Finished copying samples.
=========== = Summary = ===========
Driver: Not Selected Toolkit: Installed in /usr/local/cuda-8.0 Samples: Installed in /home/kyle, but missing recommended libraries
Please make sure that - PATH includes /usr/local/cuda-8.0/bin - LD_LIBRARY_PATH includes /usr/local/cuda-8.0/lib64, or, add /usr/local/cuda-8.0/lib64 to /etc/ld.so.conf and run ldconfig as root
To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-8.0/bin
Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-8.0/doc/pdf for detailed information on setting up CUDA.
***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 361.00 is required for CUDA 8.0 functionality to work. To install the driver using this installer, run the following command, replacing <CudaInstaller> with the name of this run file: sudo <CudaInstaller>.run -silent -driver
Logfile is /tmp/cuda_install_9426.log
这几个包可以不用管他，不用这几个sample是没有问题的。
配置环境变量
打开shell运行：gedit ~/.bashrc
加入如下内容：
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# add cuda export PATH=/usr/local/cuda-8.0/bin:$PATH export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64:$LD_LIBRARY_PATH
kyle@kyle-Lenovo-M490 ~ $ nvcc -V nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2016 NVIDIA Corporation Built on Sun_Sep__4_22:14:01_CDT_2016 Cuda compilation tools, release 8.0, V8.0.44
编译 CUDA Samples
进入samples的安装目录
为了节约时间，我们选择其中一个进行编译如：
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kyle@kyle-Lenovo-M490 ~ $ cd ~/NVIDIA_CUDA-8.0_Samples/0_Simple/vectorAdd kyle@kyle-Lenovo-M490 ~/NVIDIA_CUDA-8.0_Samples/0_Simple/vectorAdd $ make "/usr/local/cuda-8.0"/bin/nvcc -ccbin g++ -I../../common/inc -m64 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o vectorAdd.o -c vectorAdd.cu nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). "/usr/local/cuda-8.0"/bin/nvcc -ccbin g++ -m64 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_60,code=compute_60 -o vectorAdd vectorAdd.o nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). mkdir -p ../../bin/x86_64/linux/release cp vectorAdd ../../bin/x86_64/linux/release kyle@kyle-Lenovo-M490 ~/NVIDIA_CUDA-8.0_Samples/0_Simple/vectorAdd $ ./vectorAdd [Vector addition of 50000 elements] Copy input data from the host memory to the CUDA device CUDA kernel launch with 196 blocks of 256 threads Copy output data from the CUDA device to the host memory Test PASSED Done
Python 3.5.2 |Anaconda custom (64-bit)| (default, Jul 2 2016, 17:53:06)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so locally
>>>
