> For the complete documentation index, see [llms.txt](https://docs.ccv.brown.edu/oscar/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ccv.brown.edu/oscar/matlab/performance.md).

# Improving Performance and Memory Management

Matlab programs often suffer from poor performance and running out of memory. Among other things, you can refer the following web pages for best practices for an efficient code:

* [Techniques to Improve](http://www.mathworks.com/help/matlab/matlab_prog/techniques-for-improving-performance.html) [Performance](http://www.mathworks.com/help/matlab/matlab_prog/techniques-for-improving-performance.html)
* [Strategies for Efficient Use of Memory](http://www.mathworks.com/help/matlab/matlab_prog/strategies-for-efficient-use-of-memory.html)

The first step to speeding up Matlab applications is identifying the part which takes up most of the run time. Matlab's "Profiling" tool can be very helpful in doing that:

* [Profiling for Improving Performance](http://www.mathworks.com/help/matlab/matlab_prog/profiling-for-improving-performance.html)

Further reading from Mathworks:

* [Speeding Up MATLAB Applications](http://blogs.mathworks.com/loren/2008/06/25/speeding-up-matlab-applications/)


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