PSC created environments for AI applications
PSC has built some environments which provide a rich, unified, Anaconda-based environment for AI, Machine Learning, and Big Data applications. Each environment includes several popular AI/ML/BD packages, selected to work together well.
The AI environments are built for the GPU nodes on Bridges-2. Be sure to use one of the GPU partitions. See the Bridges-2 User Guide for information on Bridges-2 partitions and how to choose one to use.
- the python documentation, for a description of the ways to use python on Bridges-2
- the Anaconda modules, for information on creating, editing and storing anaconda environments on Bridges-2
Using the AI environments on Bridges-2
module spider AI/anaconda
to see the available AI environments.
For additional help, type
module help AI/anaconda-version
Note that AI/anaconda2 environments use python2, while AI/anaconda3 environments use python3.
See what the PSC defined AI environment contains
To see the full list of software included in a given environment, first load the module and activate the environment with these commands:
module load AI/anaconda-version source activate $AI_ENV
To see what is included in $AI_ENV, type
Customize the PSC defined AI environment
If you need software that is not in the pre-built environment, you can create a new environment by cloning the PSC defined one and then customizing it. First load the module and activate the PSC defined environment, as above, then clone it with
conda create --name your-new-environment-name --clone $AI_ENV
Then you can activate the new environment and proceed with your customization.
In this example, the user installs the h5py package in a new environment they are creating. Use the following commands.
conda listcommand shows what packages are currently installed. Check to see if what you need is already available. The conda list command also shows the version number of the installed packages.
conda createcommand clones $AI_ENV to create a new environment. This can take a long time, so ask for an hour of time with the
- Here, the new environment is named clone-env-1, and is stored in the user's ocean directory. The --prefix flag names the full path to the where the environment will be stored. You can name the environment anything you like and store it in any directory you like.
interact -gpu -t 01:00:00 module load AI # loads the default AI module source activate $AI_ENV conda list conda create --name clone-env-1 --clone $AI_ENV conda activate clone-env-1 conda install h5py
conda install command will install the newest version of the package. If you want to install a version of the package not available in the public installations use the --revision option to the conda install command.