Parallel Computing with MATLAB and Scaling MATLAB Code to the HPC Cluster

This interactive EuroCC workshop delved into parallel computing using MATLAB, empowering participants to tackle computationally and data-intensive challenges leveraging multicore processors, GPUs, and computer clusters.

Tutors: Raymond Norris and Dr. Shubo Chakrabarti from MathWorks

Key Learnings:

– Accelerating MATLAB applications through parallel computing techniques
– Simulating multiple instances in Simulink simultaneously
– Harnessing the potential of GPU computing
– Handling and processing large-scale datasets efficiently
– Configuring MATLAB for HPC cluster job submissions
– Understanding the workflow of job submissions
– Fine-tuning job submissions, including GPU utilization on the HPC cluster
– Optimizing job submission strategies for performance
– Troubleshooting techniques for job submissions
– Adopting best practices for code rehosting and optimization

Join Raymond Norris and Dr. Shubo Chakrabarti from MathWorks in this comprehensive exploration of MATLAB's parallel computing capabilities and its application in high-performance computing environments.