Compiling TensorFlow-GPU on Ubuntu 16.04 with CUDA 9.1(9.2) and Python3

Gary Gong

4 minute read

INSTALL CUDA:

https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=ppc64le&target_distro=Ubuntu&target_version=1604&target_type=deblocal

  1. Here, we used “Linux” -> “ppc64le”(64-bit) -> “16.04” -> “deb(local)”, and downloaded the “Base Installer” (approx. 1.0GB)
  2. Following the guidance which given by the nVidia webpage to install the CUDA.
  3. During installation, the installation program will ask you to create a “symbolic link” of CUDA library folder; remember to create.
  4. Create the environment variable to make these work.
   export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/ local/cuda/extras/CUPTI/lib64:/usr/lib/nvidia-381
   # Remember that nvidia-381 is the driver version, if you install 390, please modifiy it to nvidia-390
   export CUDA_HOME=/usr/local/cuda
   export PATH=$PATH:/usr/local/cuda/bin
  1. Execute source ~/.bashrc (source ~/.zshrc if you use zsh instead of bash) to apply the environment variable.

INSTALL CUDNN:

https://developer.nvidia.com/rdp/cudnn-download

You need have a nVidia developer membership account (free to signup) to coutinue to download the cuDNN package.

  1. After logining to the download webpage, select the corresponding CUDA version.
  2. Select cuDNN v7.?.? Library for Linux
  3. Unzip the package and copy the file into the system folder by following command:
   tar -zxvf cudnn-9.?-linux-x64-v7.?.tgz
   sudo cp cuda/include/cudnn.h /usr/local/cuda/include/
   sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/ -d
   sudo chmod a+r /usr/local/cuda/include/cudnn.h
   sudo chmod a+r /usr/local/cuda/lib64/libcudnn*

FIRST CHECK:

  1. Check your CUDA version by following command:
   cat /usr/local/cuda/version.txt
  1. Check your cuDNN version by following command:
   cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2

PREPARING YOUR DEPENDENCY:

sudo apt-get install python3-numpy python3-dev python3-pip python3-wheel
sudo apt-get install cuda-command-line-tools 
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/extras/CUPTI/lib64

CLONE THE TENSORFLOW:

git clone https://github.com/tensorflow/tensorflow 
cd tensorflow
git checkout Branch # where Branch is the desired branch

CONFIGURE YOUR TENSORFLOW:

cd tensorflow
./configure

You have bazel 0.11.1 installed.
Please specify the location of python. [Default is /home/garygone/python-dev/dl/bin/python]:


Traceback (most recent call last):
  File "<string>", line 1, in <module>
AttributeError: module 'site' has no attribute 'getsitepackages'
Found possible Python library paths:
  /home/garygone/python-dev/dl/lib/python3.5/site-packages
Please input the desired Python library path to use.  Default is [/home/garygone/python-dev/dl/lib/python3.5/site-packages]

Do you wish to build TensorFlow with jemalloc as malloc support? [Y/n]:
jemalloc as malloc support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Google Cloud Platform support? [Y/n]: n
No Google Cloud Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Hadoop File System support? [Y/n]:
Hadoop File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Amazon S3 File System support? [Y/n]: n
No Amazon S3 File System support will be enabled for TensorFlow.

Do you wish to build TensorFlow with Apache Kafka Platform support? [y/N]:
No Apache Kafka Platform support will be enabled for TensorFlow.

Do you wish to build TensorFlow with XLA JIT support? [y/N]: Y
XLA JIT support will be enabled for TensorFlow.

Do you wish to build TensorFlow with GDR support? [y/N]:
No GDR support will be enabled for TensorFlow.

Do you wish to build TensorFlow with VERBS support? [y/N]:
No VERBS support will be enabled for TensorFlow.

Do you wish to build TensorFlow with OpenCL SYCL support? [y/N]:
No OpenCL SYCL support will be enabled for TensorFlow.

Do you wish to build TensorFlow with CUDA support? [y/N]: Y
CUDA support will be enabled for TensorFlow.

Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to default to CUDA 9.0]: 9.1


Please specify the location where CUDA 9.1 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:


Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 7.0]:


Please specify the location where cuDNN 7 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:


Do you wish to build TensorFlow with TensorRT support? [y/N]:
No TensorRT support will be enabled for TensorFlow.

Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size. [Default is: 6.1,6.1,6.1,6.1,6.1,6.1,6.1,6.1]


Do you want to use clang as CUDA compiler? [y/N]:
nvcc will be used as CUDA compiler.

Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:


Do you wish to build TensorFlow with MPI support? [y/N]:
No MPI support will be enabled for TensorFlow.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]:


Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]:
Not configuring the WORKSPACE for Android builds.

Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See tools/bazel.rc for more details.
        --config=mkl            # Build with MKL support.
        --config=monolithic     # Config for mostly static monolithic build.
Configuration finished

BUILD YOUR TENSORFLOW WITH GCC5:

bazel build --config=opt --config=cuda --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" //tensorflow/tools/pip_package:build_pip_package

If build sucessfully:

bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg

and exec.

pip3 install /tmp/tensorflow_pkg/tensorflow-1.7.0-cp35-cp35m-linux_x86_64.whl

(Please make sure you are in virtualenv if you want to install this in your virtualenv and do not use sudo.)

WHAT I HAVE SEEN:

  1. https://www.tensorflow.org/install/install_sources : Installing TF from Source
  2. How to find which version of TensorFlow is installed in my system?
  3. https://github.com/tensorflow/tensorflow/issues/15604 : ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory
  4. How to get the cuda version?
  5. [NV] How to check CUDA and cuDNN version :
  6. http://windywinter.cn/2018/03/10/ML/tensorflow-gpu版本的编译/ : tensorflow-gpu版本的编译

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