techniques for accelerating matlab algorithms and applications
there are several ways to accelerate matlab algorithms and applications. the optimal approach depends on your programming expertise, the type of algorithms you wish to accelerate, and the hardware available to you.
top 5 matlab acceleration techniques
adopt efficient (serial) programming practices
leverage existing optimized algorithms
use parallel computing including gpus
use parallel computing
generate c code from matlab code
all of the above
examples and how to
- speeding up matlab applications (58:16) - webinar
- parallel computing with matlab (53:27) - webinar
- matlab to c/c made easy (47:38) - webinar
- - example
- - example
- - example
- - example
- - article
- code performance and reliability - mathworks consulting
software reference
- - documentation
- techniques for improving performance - documentation
- - documentation
- dsp system toolbox system objects - documentation
- - documentation
- best practices for generating c-code and mex-files using matlab coder - quick start guide
see also: matlab parallel server, matlab coder, dsp system toolbox, communications toolbox, matlab multicore, matlab gpu computing, parallel computing, parallel computing on the cloud with matlab