Parallel and GPU Computing with MATLAB

Presented on February 20 , 2020, by Matlab Tech Staff

In this training session you will learn how to solve and accelerate computationally- and data-intensive problems that are becoming common in the areas of machine learning and deep learning using multicore processors, GPUs, and computer clusters. We will introduce you to high-level programming constructs that allow you to parallelize MATLAB applications and run them on multiple processors. We will also discuss how to take advantage of GPUs to speed up computations without low-level programming.

Highlights include:

  • Toolboxes with built-in support for parallel computing
  • Creating parallel applications to speed up independent tasks
  • Scaling up to computer clusters, grid environments or clouds
  • Employing GPUs to speed up your computations

Due to copyright restrictions, slides and recording will not be made available for this seminar. 


About the Instructor:

Sumit Tandon, MS, EE (MathWorks | Senior Customer Success Manager)

Sumit Tandon is a Senior Customer Success Manager at MathWorks. He has a BE in Electrical Engineering from Jadavpur University, India and an MS in Electrical Engineering from the University of Texas at Arlington. He has been at MathWorks for almost 13 years, advising MATLAB users in the industry and academia in the domains of image processing, computer vision, physical system modeling and simulation, embedded systems, data analytics and high-performance computing. In his current role he manages the technical relationship of MathWorks with key academic institutions and systems in western US and Canada. Here, he partners with faculty, researchers and research centers in the exploration and effective use of MathWorks products, and programs, for curriculum and research. To bring the industry perspective and facilitate exchange of ideas he also serves on several industry advisory boards in the University of California and California State University system schools – including UC Irvine, CSULB, CSULA and also engineering education focused organizations like ECEDHA.