Cooley (ALCF)

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.

User installation

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.

Warning

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.

Note

To test you installation run:

./deephyper/tests/system/test_cooley.sh

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

Warning

The same .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