Mini Course: Speeding up MATLAB (by MathWorks)

MATLAB is a programming language focusing on making numerical computation and data visualiation easy. Many units in OIST are using this language for their research and simulations.

This Mini Course will be taught by engineers from MathWorks, the company developping MATLAB. The focus will be on accelerating MATLAB code, using different approaches: better general coding practices, using the Parallel Computing Toolbox, and using Deigo's resources.

Target audience

This course is suitable for people with some experience with MATLAB. Ideally, the participants will already have some code that they are interested in speeding up.

Teachers

The teacher will be Megumi Fukuda, from MathWork teaching remotely. Kang-Yu Chu  and Alexey Martyushev will be helping students locally.

Program

The program will be as follows:

Date Time Topic
Friday, Dec. 17 10AM - 12PM Basics for parallel computing - speeding up MATLAB with your desktop machine. Better coding practice, how to use parfor, etc. 
Friday, Jan. 14 10AM - 12PM  Scaling up MATLAB with cluster machines / HPC.

There will be hands-on experience.

The material will be adapted from this source.

More information

  • Location: B701, Computer Lab, Lab 3.
  • What to bring:
    • the latest version of MATLAB installed on it. IT instructions here.
    • The Parallel Computing Toolbox installed.
  • Zoom link: if you prefer joining remotely, or if B701 exceeds 50% capacity, you can join using this link. Unfortunately, we won't be able to provide much help with the hands-on part via Zoom. 
  • Video Recording: this course might be recorded and uploaded online, only the teacher will be recorded. Contact Jeremie Gillet if you have reservations about this.
  • Drinks: There will be free coffee and tea, bring your cup!

If you are interested in the course but cannot participate to this particular event, let us know and we will contact you for any later occurrence of this course.

Thank you very much for your interest.

 
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Have you a MATLAB user? How comfortable are you with it? Do you use it in your research?
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