On May 12, learn how to start using a supercomputer with MATLAB

Does your project involve large computations or training Machine Learning and Deep Learning models? Are you interested in speeding up your code by harnessing a High-Performance Computing (HPC) resource near you?

We’re inviting you to apply for online training on “Parallel Computing with MATLAB” which will take place on May 12 from 15:00 to 18:00.

MathWorks is partnering with NAISS Sweden, DTU Denmark, CSC Finland, Sigma2 Norway, IHPC Iceland and RTU HPC, Latvia to bring you a three series workshop on parallel computing and AI using large compute resources – including hands-on exercises where you will learn how to effectively use MATLAB and MATLAB Parallel Server to speed up your computations.

Overview

During this hands-on workshop, you will be introduced to parallel and distributed computing in MATLAB for speeding up your application by leveraging multiple cores on your computer. By working through common scenarios and workflows, you will gain an understanding of the parallel constructs in MATLAB, their capabilities, and some of the typical issues that arise when using them. You will also learn how to leverage GPUs for your AI needs. Finally, you will have an opportunity to get help from MathWorks experts on your projects.

Highlights

  • MATLAB parallel language constructs: Speeding up programs with parallel computing
  • GPU computing with MATLAB
  • Working with large datasets

Who Should Attend

This workshop is for students and researchers interested in Parallel Computing with MATLAB. If you are exploring parallel and high-performance computing with MATLAB, join this workshop to help you understand the concepts and capabilities of MATLAB parallel language.

About the Presenter

Dr. Mihaela Jarema is part of the Academia Group at MathWorks in Munich/Germany. She partners with research institutes in Germany to accelerate their discovery and learning. Mihaela holds a PhD degree in computer science from Technische Universität München. During her PhD, she has used MATLAB to model ensemble data, evaluate, and visualize the associated variability.

Register>>

This event is part of a series of related topics. View the full list of events in this series.