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Parallel Computing with MATLAB Workshop 2023

The Division of Information Technology (DIT) at the University of Maryland is pleased to announce the following virtual workshop for members of the University community.

There are only a limited number of seats available. Registration will remain open until 16 July 2023 or until all seats are filled. Although there is no charge associated with the workshop, we do require registration and we ask that you do not register unless you really intend to attend. Also, if you register and later discover you will not be able to attend, please contact us to cancel your registration as soon as possible so that we can invite someone from the wait list. It would be a shame if someone was prevented from attending due to an empty seat reserved for you.

NOTE: DIT reserves the right to cancel the workshop for any reason with little notice.

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Parallel Computing with MATLAB Workshop
LocationBrendan Iribe Center, Room 1116
Date18 July 2023
9:00 AM - 12:00 PMParallelizing MATLAB code
(introduction to MATLAB Parallel Server)
2:00 PM - 5:00 PMUsing MATLAB Parallel Server on HPC
(remotely submitting MATLAB jobs on HPC)
InstructorRaymond Norris
Parallel Computing Pilot & Engineer, The MathWorks Inc.
Costfree, registration required
Registration Formlink to registration form
Application
Deadline
16 July 2023
or when registration is full

Register Here

During this hands-on workshop, a MathWorks engineer will introduce parallel and distributed computing in MATLAB with a focus on speeding up application codes and offloading compute. By working through common scenarios and workflows using hands-on demos, you will gain a detailed understanding of the parallel constructs in MATLAB, their capabilities, and some of the common hurdles that you'll encounter when using them. In the afternoon session you will learn how to run your MATLAB code on local High Performance Computing (HPC) resources and how to submit jobs remotely from your laptop to run on Zaratan and/or Juggernaut.

The morning session is open to all MATLAB users on campus and will discuss the parallel constructs in MATLAB in general, which can be of use on multicore workstations and laptops. Practical exercises during this session will be performed using the MathWorks Cloud Center.

The afternoon session is aimed at users of the University's HPC clusters and will include instructions on using MATLAB Parallel Server to offload compute to the HPC cluster. For practical exercises during this session you will use the interactive MATLAB application on Zaratan using the onDemand Web Portal as well as your own laptop to remotely submit MATLAB jobs on Zaratan. Please have MATLAB version R2022b installed on your laptop!

Notes for this workshop can be downloaded from this site: Parallel Computing Workshop notes.

Prerequisites

Some basic familiarity with MATLAB is assumed. If you are not familiar with MATLAB or want a refresher, you might wish to take the free self-paced MATLAB Onramp course from MathWorks (about 2 hours).

System Requirements

This is a bring-your-own-laptop style event. As part of the workshop, you will be configuring your laptop to be able to offload MATLAB compute worker tasks to the UMD Zaratan HPC cluster, and it is better to do this on your own system than on a lab system.

So please bring a laptop with the following installed on it:
MATLAB R2022b including the Parallel Computing Toolbox. This is available at no charge to members of the University of Maryland community on Terpware via the campus Total Academic Headcount license;
an ssh client (on Windows preferably PuTTY).

All registered participants will get access to the Zaratan HPC cluster (for the duration of the workshop).

Resources

In case Terpware encounters issues, you may download MATLAB R2022b from the UMD MATLAB portal.

You may also check out the MATLAB Parallel Computing Fundamentals docs and links.

Notes for this workshop can be downloaded from this site: Parallel Computing Workshop notes.

For Part 2 of this workshop the following resources are available (needs to be updated):






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