Miniconda on the HPC

We have a centralized installation of Miniconda on the HPC, the users can either install their own Miniconda or use the centralized installation present on the HPC.

This centralized installation can also be used for creating your own local environments, in which you can install your own packages.

Moreover, You can clone the existing centralized environments (like Tensorflow, R) and add other required libraries or packages on top of it.

The conda cheat sheet gives you a list of useful commands in a glance: Conda-cheat-sheet

One Time Setup

Execute the following command for making the HPC Miniconda as your default conda environment. This is needed to be done ONLY once, just for setting up Miniconda for your account. Loading the miniconda module sets the miniconda environement for your account. You also need to source the bashrc file to activate the changes in your current shell. Once the environment is set up, you donot need to load the miniconda again in your subsequent logins.

module load miniconda
source ~/.bashrc

Application Installation

Following are the steps which need to be followed to install an application using conda.

  • Create a local conda environment using conda create (more details below)

  • Activate the local conda environment using conda activate (more details below)

  • Install the application using conda install (eg : conda install -c r r=3.6)

  • Clean/remove the residual/cache files created by conda which eat up your quota (eg: conda clean -a)

Note

The number of files quota usually gets filled up very quickly if you use conda/pip environment, as they generate a large number of residual files. The conda and pip environments don’t remove the files automatically and hence they stay in your $HOME affecting your files quota.

We recommend you to clean your conda/pip cache files (if any). This cleaning up of cache files is very easy and needs only a single command to be run.

Following commands and links can come handy:

Managing Environments

Create a Local Environment

The below command creates a conda environment in your $HOME/.conda/envs

#conda create -n <name of the env>

#example:
conda create -n myenv

Activate the Local Environment

#conda activate <name of the local env>

#example:
conda activate myenv

Deactivate an Environment

conda deactivate

Listing the Environments Available

This shows the existing local and centralized Miniconda environments available

conda env list

A sample output is shown below. The list of centralized and local installations can be seen.

                                     /home/wz22/.conda/envs/myenv
                                     /home/wz22/.conda/envs/myenv2
                                     /home/wz22/.conda/envs/myenv3
                                     /home/wz22/.conda/envs/myenv4
base                            *    /share/apps/NYUAD/miniconda/3-4.8.2
firefox                              /share/apps/NYUAD/miniconda/3-4.8.2/envs/firefox
tensorflow-1.15                      /share/apps/NYUAD/miniconda/3-4.8.2/envs/tensorflow-1.15
tensorflow-2.0                       /share/apps/NYUAD/miniconda/3-4.8.2/envs/tensorflow-2.0

Cloning an Environment

#conda create -n <name of the new env> --clone <path to existing env>
#example: Here we clone the existing Tensorflow environment.
conda create -n tf-gpu --clone tensorflow-1.15

Migrating / Sharing Environment

It is possible to migrate an environment, with exact same packages and configuration. This is the beauty of Conda. Same environment, anywhere.

  1. Activate the environment you want to migrate from.
    # Activate the environment you want to migrate from
# Example: conda activate <env-migrate-from>
conda activate myenv
  2. Export the environment to an yml file.
    # In this example, the yml file is called environment.yml
conda env export > environment.yml
  3. Share this yml file.

    The other person / machine, an identical environment could be created using this yml file.

    # In this example, the yml file is called environment.yml
conda env create -n myenv -f environment.yml

Submitting Job Scripts

The conda environment might not get activated when submitting a Job script since the slurm doesn’t source the bashrc file. Hence, in order to go about this, you can include the following line in your job submission script before activating the required environment.

source /share/apps/NYUAD5/miniconda/3-4.11.0/bin/activate

A sample job submission script is shown below:

#!/bin/bash
#SBATCH -c 10
#SBATCH -t 48:00:00
#Other SBATCH commands go here

#Activating conda
source /share/apps/NYUAD5/miniconda/3-4.11.0/bin/activate
conda activate myenv1

#Your appication commands go here
python abc.py

Tip

In order to avoid activating a long path everytime, an alias can be created in the bashrc similar to the following

alias myenv1='conda activate myenv1'

This will activate the environment just by typing myenv1.

Note

If you donot miniconda paths to mess up your bashrc, you can use ONE of the following commands

source /share/apps/NYUAD/miniconda/3-4.11.0/bin/activate
#you can also create an alias for the above command in your bashrc

module load miniconda-nobashrc
eval "$(conda shell.bash hook)"

Note

Go through the Conda 30 mins test drive to make sure you understand the basic concepts: https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html