Patience Deep Learning Setup

gpu_setup.md

Patience Deep Learning Setup

• Ubuntu 18.04.2
• NVIDIA Titan Xp

$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 18.04.2 LTS
Release:        18.04
Codename:       bionic

$ lspci -vnn | grep VGA
41:00.0 VGA compatible controller [0300]: NVIDIA Corporation GP102 [TITAN Xp] [10de:1b02] (rev a1) (prog-if 00 [VGA controller])

$ bazel version
Build label: 0.19.2
Build target: bazel-out/k8-opt/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar
Build time: Mon Nov 19 16:25:09 2018 (1542644709)
Build timestamp: 1542644709
Build timestamp as int: 1542644709

Install Steps

1. Install nvidia driver (ver 418.56) https://www.nvidia.com/Download/driverResults.aspx/145182/en-us

$ sudo sh ./NVIDIA-Linux-x86_64-418.56.run
# reboot
$ sudo reboot now

2. Install CUDA (ver 10.0.130)

$ wget wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64
$ sudo dpkg -i ./cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64
$ sudo apt-key add /var/cuda-repo-10-0-local-10.0.130-410.48/7fa2af80.pub 
$ sudo apt update
$ sudo apt install cuda
$ echo 'export PATH=/usr/local/cuda/bin:$PATH' >> ~/.bashrc
$ echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc
$ source ~/.bashrc
# reboot
$ sudo reboot now

3. Install cuDNN (7.5.0 for CUDA 10.0) https://developer.nvidia.com/rdp/cudnn-download

$ tar xvf cudnn-10.0-linux-x64-v7.5.0.56.tgz
$ cd cuda
$ sudo cp include/* /usr/local/cuda/include/
$ sudo cp lib64/* /usr/local/cuda/lib64/
$ sudo chmod a+r /usr/local/cuda/lib64/libcudnn*

4. Install OpenBLAS

$ git clone https://github.com/xianyi/OpenBLAS.git
$ cd OpenBLAS
$ make FC=gfortran -j16
$ sudo make PREFIX=/usr/local install

5. Install Tensorflow

$ git clone https://github.com/tensorflow/tensorflow.git
$ cd tensorflow
$ git checkout r1.13

• Configuration

WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
You have bazel 0.19.2 installed.
Please specify the location of python. [Default is /home/alexander/sandbox/src/github.com/tensorflow/tensorflow/venv/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/alexander/sandbox/src/github.com/tensorflow/tensorflow/venv/lib/python3.6/site-packages
Please input the desired Python library path to use.  Default is [/home/alexander/sandbox/src/github.com/tensorflow/tensorflow/venv/lib/python3.6/site-packages]

Do you wish to build TensorFlow with XLA JIT support? [Y/n]:
XLA JIT 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 ROCm support? [y/N]:
No ROCm 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. [Leave empty to default to CUDA 10.0]:


Please specify the location where CUDA 10.0 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]:


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 the locally installed NCCL version you want to use. [Default is to use https://github.com/nvidia/nccl]:


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]:


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 -Wno-sign-compare]:


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 .bazelrc for more details.
        --config=mkl            # Build with MKL support.
        --config=monolithic     # Config for mostly static monolithic build.
        --config=gdr            # Build with GDR support.
        --config=verbs          # Build with libverbs support.
        --config=ngraph         # Build with Intel nGraph support.
        --config=dynamic_kernels        # (Experimental) Build kernels into separate shared objects.
Preconfigured Bazel build configs to DISABLE default on features:
        --config=noaws          # Disable AWS S3 filesystem support.
        --config=nogcp          # Disable GCP support.
        --config=nohdfs         # Disable HDFS support.
        --config=noignite       # Disable Apacha Ignite support.
        --config=nokafka        # Disable Apache Kafka support.
        --config=nonccl         # Disable NVIDIA NCCL support.
Configuration finished

• Build

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

$ ./bazel-bin/tensorflow/tools/pip_package/build_pip_package ~/sandbox/build/

do you mean git checkout r1.13?

@hazelybell yep, updated