Cooley is a GPU cluster at Argonne Leadership Computing Facility (ALCF). It has a total of 126 compute nodes; each node has 12 CPU cores and one NVIDIA Tesla K80 dual-GPU card.
Before installating DeepHyper, go to your project folder:
cd /lus/theta-fs0/projects/PROJECTNAME mkdir cooley && cd cooley/
DeepHyper can be installed on Theta by following these commands:
git clone https://github.com/deephyper/deephyper.git --depth 1 ./deephyper/install/cooley.sh
Then, restart your session.
You will note that a new file
~/.bashrc_cooley was created and sourced in the
~/.bashrc. This is to avoid conflicting installations between the different systems available at the ALCF.
To test you installation run:
A manual installation can also be performed with the following set of commands:
# Install Miniconda wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.9.2-Linux-x86_64.sh -O miniconda.sh bash $PWD/miniconda.sh -b -p $PWD/miniconda rm -f miniconda.sh # Install Postgresql wget http://get.enterprisedb.com/postgresql/postgresql-9.6.13-4-linux-x64-binaries.tar.gz -O postgresql.tar.gz tar -xf postgresql.tar.gz rm -f postgresql.tar.gz # adding Cuda echo "+cuda-10.2" >> ~/.soft.cooley resoft source $PWD/miniconda/bin/activate # Create conda env for DeepHyper conda create -p dh-cooley python=3.8 -y conda activate dh-cooley/ conda install gxx_linux-64 gcc_linux-64 -y # DeepHyper + Analytics Tools (Parsing logs, Plots, Notebooks) pip install deephyper[analytics,balsam] conda install tensorflow-gpu
.bashrc is used both on Theta and Cooley. Hence adding a
module load instruction to the
.bashrc will not work on Cooley. In order to solve this issue you can add a specific statement to your
.bashrc file and create separate bashrc files for Theta and Cooley and use them as follows.
# Theta Specific if [[ $HOSTNAME = *"theta"* ]]; then source ~/.bashrc_theta # Cooley Specific else source ~/.bashrc_cooley fi