Write your code to be simple and readable, especially for the first implementation. Code that is prematurely optimized can be unnecessarily complex without providing a significant gain in performance. Then, if speed is an issue, you can measure how long your code takes to run and profile your code to identify bottlenecks. If necessary, you can take steps to improve performance.
MATLAB® handles data storage for you automatically. However, if memory is an issue, you can identify memory requirements and apply techniques to use memory more efficiently.
timeit function or the stopwatch timer functions,
toc, to time how long your
code takes to run.
Use the Profiler to measure the time it takes to run your code and identify which lines of code consume the most time or which lines do not run.
To determine how much of a file MATLAB executes when you profile it, run the Coverage Report.
Write more memory-efficient code by understanding how MATLAB allocates memory.
Reduce memory usage in your programs, use appropriate data storage, avoid fragmenting memory, and reclaim used memory.
MATLAB can apply memory optimizations when passing function inputs by value.
MATLAB returns an error whenever it requests a segment of memory from the operating system that is larger than what is available.