Data Management Workshops


Learn about managing your data on UA's HPC cluster. Co-sponsored with University Libraries. Virtual only.
The link below has PDF and mp4 versions of the workshop, so watch these if the timing is better for you

Find more information here


Introduction to HPC


We encourage you to take training course. It will help you get started on using HPC resources.  If you have recently started, you might learn there is a better way, or there are capabilities you are not taking advantage of.
The link below has PDF and mp4 versions of the workshop, so watch these if the timing is better for you

Find more information here

Training Materials

Hands-on exercises from the workshop appear here: Intro to HPC Exercises

Introduction to Machine Learning on HPC


We see a lot of growth in the use of Machine Learning and Deep Learning across many domains.  These two workshops provide some basic ML information and some hands-on exercises.  Once you have an HPC account you can use our Jupyter notebooks or RStudio. You can also do the exercises on your laptop.

We plan to schedule each of these in the Fall for a presence workshop

Find more information here 

Hands-on exercises for the Python workshop appear here: Intro to ML Exercises

Introduction to Parallel Computing on HPC


The best way to take advantage of our clusters is to use the parallel capabilities.  This can mean using all the cores on each compute node or combining several nodes with MPI.  This workshop will give you a quick view of the concepts and how we implement them.

We plan to schedule this in the Fall for a presence workshop

Find more information here 

Introduction to Containers on HPC

This short training class provides a brief introduction to the use of containers on HPC.  There are several simple examples you can try as you decide which method works for you.

We plan to schedule this in the Fall for a presence workshop.


Matlab offers a number of free tutorials including these ones:

Training Overview

Machine Learning Onramp

Deep Learning Onramp

Resources from the recent workshop:

  1. Slides and Exercises from today’s workshop can be downloaded at -
  2. Free online training - Introduction to MATLAB - MATLAB Onramp
  3. Free in-depth MATLAB training – MATLAB Fundamentals
  4. Free online training - Introduction to Deep Learning – Deep Learning Onramp
  5. Free in-depth Deep Learning training  - Deep Learning with MATLAB
  6. More Resources (e-books, videos) and Examples (to help you get started with your projects)
  7. University of Arizona MATLAB Portal Page (Access and download MATLAB, MATLAB Online, Self-paced trainings, Technical Support and other resources)

Workshops at UArizona

Deep Learning In Matlab

October 28, 2021

Learn how you can use MATLAB to apply deep learning techniques to your work whether you’re designing algorithms, preparing and labeling data, or generating code and deploying to embedded systems.  For resources shared at the workshop see the bottom of this page.

Details and Registration

Tackling Big Data with Matlab

April 5, 2022

In this seminar you will learn strategies and techniques for handling large amounts of data in Matlab. New big data capabilities in Matlab will be highlighted including tall arrays.

Details and Registration

Data Center Video Tour

You may not get to see the actual supercomputers where you work is done, but you can watch this tour.  Note how loud it is in the room.  The video does not convey the temperature of the room, but there are no warm areas. As you will hear explained, the cooling is done with chilled water.

Linux Self Guided 

We run RHEL/CentOS 7 Linux on our high-performance systems. If you have never used Linux before or have had very limited use, read this useful guide:

Or try this one:

GPU/Nvidia Training

Nvidia offers AI, Data Science and accelerated computing curriculum with access to GPU's and course material.  You can use our Nvidia GPUs also.

Nvidia Deep Learning Institute

See their web site for more information on the University Ambassador Program, Teaching Kits and Certifications

Introduction to OpenMP

This PDF file is a presentation from a series called Xsede * HPC Workshop.

* XSEDE, the Extreme Science and Engineering Discovery Environment, is the most advanced, powerful, and robust collection of integrated digital resources and services in the world. It is a single virtual system that scientists and researchers can use to interactively share computing resources, data, and expertise. XSEDE integrates the resources and services, makes them easier to use, and helps more people use them.



Singularity containers let users run applications in a Linux environment of their choosing.  This is different from Docker which is not appropriate for HPC due to security concerns.  Singularity is like a container for Docker images, but is not just for Docker.  

The most important thing to know is that you create the singularity container called an image on a workstation where you have root privileges, and then transfer the image to HPC where you can execute the image. If root authority is an issue then the answer might be a virtual environmen t on your laptop, like Vagrant for MacOS

For an overview and more detailed information refer to:
Singularity Quick Start

Here are some of the use cases we support using Singularity:

  • Portability and reproducibility
  • You already use Docker and want to run your jobs on HPC
  • You want to preserve your environment so that a system change will not affect your work
  • You need newer or different libraries than are offered on HPC systems
  • Someone else developed the workflow using a different version of linux
  • You prefer to use something other than Red Hat / CentOS, like Ubuntu 

Singularity is now called Apptainer but it is functionally the same.