Technical Computing with MATLAB at Rutgers (9-10:45am & 1:00-4:00pm Mar 30; NB)

You are invited to attend a free MATLAB seminar on Wednesday, March 30th in the Alampi room at the Institute of Marine and Coastal Sciences Building on Cook Campus.

To learn more or to register for this seminar, please visit:

http://www.mathworks.com/seminars/rut2011

Session 1: 9:00am – 10:45am Mathematical Modeling with MATLAB
Presenter: Abhishek Gupta, Applications Engineer

Mathematical models are critical to understanding and accurately simulating the behavior of complex systems. They enable important tasks such as forecasting system behavior, characterizing system response, and designing control systems. Attend this free seminar to find out how you can use MATLAB and add-on products for your mathematical modeling tasks.

This session will show how you can use MATLAB products for mathematical modeling tasks, including:

  • Fitting surface on to data using parametric modeling approach
  • Predicting responses using regression trees
  • Generating reports to document and share results

Session 2: 1:00pm – 4:00pm Speeding Up Applications and Parallel Computing with MATLAB
Presenter: Abhishek Gupta, Applications Engineer

Speeding Up MATLAB Applications: Serial Best Practices

This session will focus on good serial MATLAB programming practices. We will discuss and demonstrate simple ways to improve and optimize your code that can boost the execution speed of your application. We will also address common pitfalls in writing MATLAB code and explore the use of the MATLAB Profiler to find bottlenecks.

Highlights include:

  • Understand memory usage and vectorization in MATLAB
  • Address bottlenecks in your programs
  • Optimize file I/O to streamline your code

Parallel Computing with MATLAB

In the second part of this session, you will learn how to solve computationally and data-intensive problems using multicore processors and computer clusters. We will introduce you to high-level programming constructs that allow you to parallelize your applications to boost execution speed. We will show you how to overcome the memory limits of your desktop computer and solve problems that require manipulating very large matrices by distributing your data. We will also illustrate how you can run the same application on a single machine using the Parallel Computing Toolbox and on a large scale computing resource such as a cluster, using the MATLAB Distributed Computing Server.

This session will cover:

  • Toolboxes with built-in support for parallel computing
  • Creating parallel applications to speed up independent tasks
  • Programming with distributed arrays to work with large data sets
  • Scaling up to computer clusters, grid environments or clouds.
  • Tips on developing parallel algorithms

Interactive Tutorials for Students and Faculty