MATLAB and Simulink Seminars

Accelerate and Parallelize MATLAB Code

Overview

This event is organized with the collaboration of Universidade de Coimbra and it is part of EuroCC2 activities.

Using the Parallel Computing capabilities in MATLAB allows users to take advantage of additional hardware resources that may be available either locally on their desktop or on clusters, clouds, and grids. By using more hardware, you can reduce the cycle time for your workflow and solve computationally and data-intensive problems faster.

In this session, you will be introduced to parallel, distributed and GPU computing in MATLAB for speeding up your application and offloading work.  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.

Highlights

  • Leveraging multiple cores or CPUs
  • Working with high-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms.
  • Scaling up to utilize clusters, grids and clouds
  • Utilizing tall and distributed arrays to work with large data sets
  • GPU Computing with MATLAB

Who Should Attend

The event is open to researchers, PhD students, students and professors of universities and research institutes, interested in advancing the pace of their research by using parallel computing strategies.

About the Presenter

Miguel Alonso is a member of the application engineering team at MathWorks. His role in the company is to provide technical support to customers in the fields of Data Analytics and Artificial Intelligence. Before joining MathWorks, Miguel gained work experience in various industry sectors, focusing on the development of autonomous navigation systems, computer vision, and mechatronic models. His skills and knowledge come from his education in industrial engineering, which he studied at the Polytechnic University of Madrid, and his specialization in Robotics and Mechatronics at the University of Twente in the Netherlands.

Agenda

1.     Utilizing multiple cores on desktop computers

2.     Parallel Computing with Simulink

3.     Accelerate applications with NVIDIA GPUs

4.     Scaling with MATLAB Parallel Server

5.     Tackling challenges of Big Data

Product Focus

Accelerate and Parallelize MATLAB Code

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