Department of Engineering

IT Services

Matlab for CUED IIB project students, Easter term

Having worked for months on their project, some IIB students have a matlab program that seems to be working. In May, they decide it's time to throw some real data at it. The result is that Matlab runs slowly and/or runs out of memory. Fortunately all is not lost. Matlab makes it easy to write inefficient code and speeding it up may be easy. Here are some resources

  • Faster Programs - Matlab - faster scripts has a few simple things to check. Mathworks' Avoiding 'Out of Memory' Errors page has more detailed memory management tips.
  • Parallelisation - Matlab and parallel computing might have info that's useful when you run on multi-CPU, multi-core machines. maxNumCompThreads can make a difference without you having to do any extra work. Other modification might require more thought
  • Overnight/weekend batch jobs - our Running Long Programs page describes how you can queue up dozens of jobs to run outside office hours on our faster machines. We have about 10 4-cpu machines available, so you can get a lot done over-night. To fully exploit the facility you need to break up long processes into smaller chunks that can be run simultaneously. Often the machines are barely used until a week or so before project deadlines.