MATLAB is a programming and numeric computing platform used to analyze data, develop algorithms and create models. This roadmap includes topics that provide a basic introduction to MATLAB, discuss how to write MATLAB code that can be compiled for speed, and offer tips on getting the best performance out of MATLAB.

The example code in these topics was run and verified using MATLAB 2017a through 2021a. Most of it (outside of Mex and other FFI examples) should also work with slight modifications in GNU Octave.

Objectives

After you complete this workshop, you should be able to:

  • Write compiled "mex" functions in MATLAB.
  • Describe the steps to use MATLAB on a computing resource at the Texas Advanced Computing Center (TACC).
  • Improve the performance and usefulness of your MATLAB code by applying numerous tips.
Prerequisites
  • This tutorial assumes the reader has some prior experience using MATLAB and familiarity with general programming concepts. Introductory MATLAB materials can be found many places online, including those from Kelly Black, Kermit Sigmon, and MathWorks.
  • Many of the examples will also benefit from having some knowledge of the C programming language.
Requirements

In order to try the examples presented in these topics, you must have access to a computer with MATLAB installed. A MATLAB license is required for the software to run, but trial licenses are available. MATLAB is also often installed and licensed on high performance computing (HPC) systems, such as those at the Texas Advanced Computing Center (TACC).

©  |   Cornell University    |   Center for Advanced Computing    |   Copyright Statement    |   Inclusivity Statement