Introduction to HPC Module system

Introduction to HPC Module System

Most HPC clusters have many software packages available for various needs. Most installed packages are available as environment modules. You can find out about an installed software/module using the following command:-
 
module avail 
This command will list all the installed software and modules in your cluster.

Use:
module load <module/version>        to load a module
module unload <module/version>    when done.

Generally, use as few modules as possible at a time. Once you're done using a particular piece of software, unload it before you load another one to avoid incompatibilities.

If you cannot find a piece of software on the cluster, you can request an installation for cluster-wide use. Read through the Software Installation Policy page, and send your software request through the Software Installation Request form:

Contact hpc-help@ucdavis.edu with any other software issues.

Conda

Users can install their own Conda package by loading the system-installed Conda and then creating and activating their required environments:

module load conda
conda create -n [name of the environment] -c [name of the channels] [list of packages to install]
conda activate [name of environment]

Note that you can leave off the -c bioconda, because the system-wide conda configuration already has the bioconda channel configured as well as conda-forge

You can also replace conda with mamba in the create phase, it will solve the environment much more quickly. When the environment is active, you can run the following command to see that it lives in your home directory:

echo $CONDA_PREFIX

Python
 

Python is also installed and is available in the cluster Conda; you can load it using:

module load conda
conda activate
Python

R

R is a programming language and software environment for statistical computing and graphics.  
R offers a wide variety of statistics-related libraries and provides a favorable environment for statistical computing and design. In addition, the R programming language gets used by many quantitative analysts as a programming tool since it's useful for data importing and cleaning.

In order to see different versions of R installed on the cluster, run the command:

module avail R

You can obtain R in your environment by loading the R module i.e.:

module load R

The command R --version returns the version of R you have loaded:

R --version

In order to run the loaded R module you can enter this command to work with it and get the prompt:

R

To check available libraries and packages inside R, use the following command:

library(library-name)
OR
installed.packages()

For adding a new package that is missing you can install it using the command:

install.packages("package-name")
 

RStudio Server

Rstudio server enables you to provide a browser-based interface to a version of R running on a remote Linux server, bringing the power and productivity of the RStudio IDE to server-based deployments of R.
Users can see the installed Rstudio versions by running the following commands:

module avail rstudio-server

The command output will list down all the installed versions of the module. Follow these instructions to load Rstudio:-

RStudio Server is not allowed on the head node; it must be run in an interactive Slurm
session. For example, you could run:

  srun --partition=high2 --time=9:00:00 --cpus-per-task=4 --mem=20G --pty /bin/bash -l

Adjust the --partition= argument to your high partition of choice, and adjust the --mem=
argument to be large enough to encompass your entire R session.

Once your session launches, reload this module again and follow these instructions:
module load R
rstudio-launch
You need to use SSH tunneling to allow your computer to communicate with
RStudio Server on the cluster.

Run the following command in a new terminal on your computer:

   ssh -L49159:cpu-6-66:49159 user1@farm.hpc.ucdavis.edu

Then, on your computer, navigate your browser to:

   URL: http://localhost:49159
   Username: User1
   Password: ****

What is available software in Franklin cluster?

Franklin users can read about the available software in Franklin cluster on our documentation page:
https://docs.hpc.ucdavis.edu/franklin/software/modules/ 

How do I send Software Installation Request?