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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  the Bridges-2 User  Guide for information on  Bridges-2 partitions and how to choose one to use.

See also:

  • 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 enviroments on Bridges-2

Type

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

conda list

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.

Example

In this example, the user installs the h5py package in a new environment they are creating. Use the following commands.  Note:

The conda list command 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.

The conda create command clones $AI_ENV to create a new environment.  This can take a long time, so ask for an hour of time with the interact command.

Here, the new environment is named clone-env-1, and is stored in the user's pylon5 or 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 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.