Skip to content

Latest commit

 

History

History

Optimized_TF

README.md

Install instructions for GPU use

  1. Navigate to your Eagle home directory or scratch directory using
cd ~/

or

cd /scratch/$USER/
  1. Clone the github repo into the directory you chose
git clone https://github.com/NREL/HPC
  1. Navigate to the repo
cd ./HPC/general/Optimized_TF/
  1. To install TensorFlow 2.4.0 with Python 3.8 for GPUS run the following
  • a) load the appropriate modules 
    module purge
module use /nopt/nrel/apps/modules/test/modulefiles/
module load conda
module load gcc/7.4.0
module load cudnn/8.0.5/cuda-10.2
  • b) build a predefined conda environment 
    conda env create -f py38tf24.yml
  • c) Active the conda environment 
    source activate py38tf24
  • d) Install the precompiled TensorFlow installation from a wheel 
    pip install --upgrade --no-deps --force-reinstall /nopt/nrel/apps/wheels/tensorflow-2.4.0-cp38-cp38-linux_x86_64.whl
  • e) If you are on an allocated or interactive node you can test the install by running 
    python3 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
  1. To install TensorFlow 2.3.2 with Python 3.8 for GPUS run the following
  • a) load the appropriate modules 
    module purge
module use /nopt/nrel/apps/modules/centos74/modulefiles/
module load gcc/7.4.0
module load cuda/10.0.130
module load cudnn/7.4.2/cuda-10.0
module load conda
  • b) build a predefined conda environment 
    conda env create -f py38tf23.yml
  • c) Activate the conda environment 
    source activate py38tf23
  • d) Install the precompiled TensorFlow installation from a wheel 
    pip install --upgrade --no-deps --force-reinstall /nopt/nrel/apps/wheels/tensorflow-2.3.2-cp38-cp38-linux_x86_64.whl
  • e) If you are on an allocated or interactive node you can test the install by running 
    python3 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
  1. To install TensorFlow 2.2.x with Python 3.7 for GPUs run the following
  • a) load the appropriate modules 
    module purge
module use /nopt/nrel/apps/modules/centos74/modulefiles/
module load gcc/7.4.0
module load cuda/10.0.130
module load cudnn/7.4.2/cuda-10.0
module load conda
  • b) build a predefined conda environment 
    conda env create -f py37tf22.yml
  • c) Active the conda environment 
    source activate py37tf22
  • d) Install the precompiled TensorFlow installation from a wheel 
    pip install --upgrade --no-deps --force-reinstall /nopt/nrel/apps/wheels/tensorflow-2.2.1-cp37-cp37m-linux_x86_64.whl
    or 
    pip install --upgrade --no-deps --force-reinstall /nopt/nrel/apps/wheels/tensorflow-2.2.1-cp37-cp37m-linux_x86_64.whl
  • e) If you are on an allocated or interactive node you can test the install by running 
    python3 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
  1. To install TensorFlow 2.0.0 with Python 3.7 for GPUs run the following

  • a) load the appropriate modules

    module purge
module use /nopt/nrel/apps/modules/centos74/modulefiles/
module load gcc/7.3.0
module load cuda/10.0.130
module load cudnn/7.4.2/cuda-10.0
module load conda

  • b) build a predefined conda environment

    conda env create -f py37tf20.yml

  • c) Active the conda environment

    source activate py37tf20

  • d) Install the precompiled TensorFlow installation from a wheel

    pip install --upgrade --no-deps --force-reinstall /nopt/nrel/apps/wheels/tensorflow-2.0.0-cp37-cp37m-linux_x86_64.whl

  • e) If you are on an allocated or interactive node you can test the install by running

    python3 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"