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.
Measure the Performance of Your Code
Use the timeit function or the stopwatch timer functions,
tic and toc, to time how long your
code takes to run.
Profile Your Code to Improve Performance
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.
Determine Code Coverage Using the Profiler
To determine how much of a file MATLAB executes when you profile it, run the Coverage Report.
Techniques to Improve Performance
To speed up the performance of your code, there are several techniques that you can consider.
Understand how MATLAB allocates memory to write code that uses memory more efficiently.
Strategies for Efficient Use of Memory
Reduce memory usage in your programs, use appropriate data storage, avoid fragmenting memory, and reclaim used memory.
Avoid Unnecessary Copies of Data
MATLAB can apply memory optimizations when passing function inputs by value.
Resolve “Out of Memory” Errors
MATLAB returns an error whenever it requests a segment of memory from the operating system that is larger than what is available.