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Training

Overview

HPC Workshops

Every semester, we offer a variety of workshops including, but not limited to, Intro to HPC, Intro to Machine Learning, Intro to Parallel Computing, Intro to Containers, and Data Management Workshops. Check the Workshops and Schedule section below to see the dates of our upcoming sessions or check out the links on the right-hand side for detailed information. We announce upcoming workshops through the hpc-announce listserv so if you do not see any workshops scheduled, keep your eye on your inbox. You may also want to look through our detailed pages for course slides, video presentations, and interactive guides.

Self Guided Training

Need some help getting started with Linux, GPU programming, Singularity, OpenMP, or Matlab? Check out the Self Guided Training section below for resources to get you up and running. 

Data Center Video Tour

Have you ever wanted to see our supercomputers? Check out this guided tour through our data center!

Detailed Information on our Workshops


Workshops and Schedule

These workshops are all introductory by nature. If you want more advanced workshops, the Data Science Institute conducts a broad range that can be found on their calendar.

Introduction to HPC

Click here for more detailed information

Upcoming Workshops

Date Time Location Registration
TBD


Past Workshops

Date Time Location Registration

9:00 - 10:00am Main Library B254

9:00 - 10:00am Main Library, Data Studio CATalyst

9:00 - 10:00am Room 130A UITS Building

9:00 - 10:00am Room 130A UITS Building

9:00 - 10:00am Room 130A UITS Building

Machine Learning on HPC

Click here for more detailed information

Upcoming Workshops

Date Time Location Registration
TBD


Past Workshops

Date Time Location Registration

 

9:00 - 10:00am Main Library, Data Studio CATalyst

 

9:00 - 10:00am Main Library, Data Studio CATalyst

 

9:00 - 10:00am Room 130A UITS Building

 

9:00 - 10:00am Room 130A UITS Building

 

9:00 - 10:00am Room 130A UITS Building

Introduction to Parallel Computing

Click here for more detailed information

Upcoming Workshops

Date Time Location Registration
TBD


Past Workshops

Date Time Location Registration

 

10:30 - 11:30am Main Library, Data Studio CATalyst

 

10:30 - 11:30am Main Library, Data Studio CATalyst

Introduction to Containers on HPC

Click here for more detailed information

Upcoming Workshops

Date Time Location Registration
TBD


Past Workshops

Date Time Location Registration

 

9:00 - 10:00am Main Library, Data Studio CATalyst

 

9:00 - 10:00am Main Library, Data Studio CATalyst

Data Management Workshops

Click here for more detailed information

Upcoming Workshops

Date Time Location Registration
Data Management Part 1
TBD


Data Management Part 2
TBD


Past Workshops

Date Time Location Registration
Data Management Part 1

 

1:00 - 2:00pm Online

 


Online
Data Management Part 2

 

2:00 - 3:00pm Online

 


Online

Nvidia Workshop

Nvidia workshop taught by Nvidia staff.
Free lunch.  Pizza will be provided at Noon.
This workshop will have Nvidia staff present.  You can learn about their technologies particularly with Machine Learning and AI, ask them questions 

Subject Date Time Location Registration
Nvidia Workshop Friday September 30, 2022 12 - 3pm Main Library B252 Registration

Abstract

In this session we will cover some of the most popular and effective GPU accelerated libraries that give high performance without the requirement of writing your own custom GPU code. We will cover CUDA-X which has libraries for math, image/video processing, deep learning, and GPU tailored partner libraries. On top of CUDA-X we will cover RAPIDS which will target data science and data analytics workloads. We will conclude the session with interactive coverage of NVIDIAs profiling tools. We will conclude with a brief coverage of Python specific tools we have like CuPy and Numba for customizable GPU accelerated code. By the end of the workshop, you'll have the skills to utilize existing GPU accelerated libraries and write your own Python codes with NVIDIA GPUs!

Learning Objectives:

  • Introduce RAPIDS and CUDA-X for drop-in GPU-accelerated libraries
  • Introduce CuPy and Numba for GPU accelerated Python code 


Self Guided Training

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: http://www.ee.surrey.ac.uk/Teaching/Unix/

Or try this one:
https://www.pcwdld.com/linux-commands-cheat-sheet

Shell Computing

https://effective-shell.com/

Matlab Training

Matlab Online Training

Matlab offers a number of free tutorials including these ones:

Resources from the recent workshop:

Matlab 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

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

Singularity Training

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

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 

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.


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.

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