* Peak memory is the maximal amount of allocated memory during the execution of the profiled line/function.
* Allocated memory is the total amount of memory allocated during the execution. Note that it is a cumulative amount, meaning that if you have an allocation of 1KB in a loop that runs 50 times, you’ll see a 50KB value.
* Freed memory is the total amount of memory de-allocated during the execution. This too is a cumulative amount.
* Self memory is the memory used by the profiled line/function, which is not deallocated (and therefore not included in the “Freed memory” value).

Note that these are speculations: The exact definition of what is reported under which category is internal to Matlab and is currently unknown.

You could also use non-Matlab tools (e.g., Process Explorer for memory leaks or GDIView for GDI handle leaks — both of them for Windows).

Note in advance that hunting down memory leaks in Matlab is very difficult, due to the lack of good monitoring tools (AFAIK).

If you or anyone else find any leaks, please report them here or directly to me. I know for a fact that MathWorks’ dev team are very interested in such inputs — whatever will be reported to me I will pass on to them for fixing.

I got a nonsensical memory value for a mex function (10^16 kB). It is using its own memory allocation internally, though…

This is unfortunate, because lack of memory profiling is one of Matlab’s biggest performance gaps. As someone who works with massive neuroimaging data sets every day, good memory use is more important to me than CPU performance. Shaving an hour or two off an analysis is nice, but using too much memory means my analysis won’t even finish.

As an ex-professional programmer, I’d seriously considered making and selling something like this as an add-on if I wasn’t in grad school.

Maybe in that far-off utopia of infinite funding, I can convince my advisors to buy all the necessary copies of later matlab versions.