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Table of Contents


2021 Workshops

Data Management Part 1:  October 20

Learn about managing your data on UA's HPC cluster. Co-sponsored with University Libraries

Details and Registration

Data Management Part 2:  October 21

Tools and workflows for managing data on UA’s HPC cluster. Co-sponsored with University Libraries

Details and Registration

Deep Learning In Matlab:  October 28

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

Introduction to HPC: Wednesday  
Wednesday November 10 9am-10am.  Room 130A UITS Building
Wednesday December 1 9am-10am. Room 130A UITS Building

This training course 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.  You can stick around and use this as a consulting session.

To register just send an email to with your Name, Netid, Department / School

View file

Machine Learning on HPC:
Friday November 12. 9am-10am. Room 130A UITS Building
Friday December 3. 9am-10am. Room 130A UITS Building 

This short training class provides a brief introduction to key concepts of machine learning.  The short lecture will be followed by two hands-on examples that emphasize running a Jupyter notebook on the HPC supercomputers. You can stick around and use this as a consulting session. View filenameIntro to AI ML.pdfheight250

To register for either of these, just send an email to with your Name, Netid, Department / School

View file
nameIntro to AI ML.pdf


The building is at the corner of Mountain and Speedway.  The entrance is at the east end of the building and the room 130A is downstairs

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:

Introduction to Parallel Computing

Thanks to Lawrence Livermore Labs for this tutorial



Introduction to OpenMP

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

View file

* 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:

  • 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 

We have some local tutorials for Singularity


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)