-
Notifications
You must be signed in to change notification settings - Fork 40
Installing MaTEx TensorFlow GPU
Vinay Amatya edited this page Jul 16, 2018
·
13 revisions
We have provided a set of scripts for easy installation on GPU clusters. We expect that minimal changes would be required to the script for installation.
For using GPU enabled TensorFlow, you would need to set up the CUDNN_HOME, CUDA_HOME, MPI_HOME and ANACONDA_HOME environment variables to point where the CUDNN library, the CUDA SDK, MPI home directory and ANACONDA home directory should be found.
As an example, for bash shells:
$ export ANACONDA_HOME=/whre/anaconda/home/resides
$ export CUDA_HOME=/where/nvcc/resides
$ export CUDNN_HOME=/where/cudnn/resides
$ export MPI_HOME=/where/mpi_library/resides
Once the environment variables have been setup:
Installation for bash shells
$ cd matex/src/deeplearning/tensorflow/gpu/py3.x
$ source ./install_tf_matex_0.7.0_cu9.1.sh
Installation for C-shells
Deactivating the virtual environment:
source deactivate_mtx.sh
Activating the virtual environment (if MaTEx has already been installed):
source activate_mtx.sh
Getting Started on MaTEx-TensorFlow
- Required Software
- Installing MaTEx-TensorFlow on CPU Clusters
- Installing MaTEx-TensorFlow on GPU Clusters
- MaTEx-TensorFlow on Older glibc(v<2.19)
- DataSet Reader
- Testing Scripts
- Performance
- Running on PNNL Systems
- Running on NERSC Systems
- Restarting the MaTEx TensorFlow environment