MATLAB-Seminar-at-UTSA-Hosted-by-Research-Computing-Support-Group

August 22, 2016



by Rosalind Ong De Trevino at 1:58 PM in Campus CommunityProductivity

MATLAB seminars held at UTSA

UTSA faculty, staff, researchers, and students had the opportunity to attend MATLAB seminars at UTSA organized by the Office of Information Technology's (OIT) Research Computing Support Group. More than 60 attendees showed up for the sessions presented by a MathWorks engineer. The sessions were held on August 18 in the North Paseo Building on the Main Campus. These sessions were an opportunity for the UTSA community to ask questions and learn more about how MATLAB can be used to enhance their research.

The MATLAB platform is optimized for solving engineering and scientific problems. It is used in a wide array of industries including automotive active safety systems, heath monitoring devices, and LTE cellular networks. "It is used for machine learning, signal processing, image processing, computer vision, communications, computational finance, control design, robotics, and much more.- www.mathworks.com/products/matlab/." Two technical sessions were offered for UTSA faculty, staff, researchers, and students to learn more about MATLAB.

Programming with MATLAB

During this session participants learned about the programming capabilities in MATLAB, ways to be more productive working with MATLAB, and how to share your algorithms and applications with others who do not have MATLAB.

Highlights included:

  • Exploring the fundamentals of the MATLAB programming language
  • Automating with scripts
  • Writing programs to automate your workflow
  • Leveraging tools for efficient program development
  • Developing and maintaining complex applications

Parallel Computing with MATLAB

During this session participants learned to solve computationally and data-intensive problems, were introduced to high-level programming constructs, and were showed how to overcome the desktop computer memory limits and solve problems that require manipulating very large matrices by distributing your data. They also learned how users can run the same application on a single machine (Parallel Computing Toolbox) and on a large scale computing resource such as a cluster (MATLAB Distributed Computing Server.)

Highlights included:

  • Distributing long-running calculations
  • Processing large amounts of data by distributing it
  • Leveraging multiple cores or CPUs
  • Using high-level constructs—parallel for-loops, special array types, and parallelized numerical algorithms
  • Using MATLAB for GPU computing
  • Scaling up to utilize clusters, grids and clouds


MATLAB seminars held at UTSA