There are four ways how Matlab code gets sped up:
-
JIT: compiling at runtime helps with loops but seems to speed up (or at least interact with) other parts of the code as well, according to my anecdotal observations.
-
Implementing functions in C/C++: There’s a bunch of Matlab/Octave functions that are implemented in Matlab/Octave. At every release, there’s a bunch more of them that get made into built-ins.
-
Multithreading: There’s a list of functions that have multithreaded implementations, which will speed up function calls.
-
Generally more efficient implementations. For example the median filter got a massive speed boost for integer inputs a few releases ago.
All of these approaches need developers dedicated to make code faster. As far as I know, a major concern of Octave developers is to make sure (Matlab) functionality is there at all, whereas performance increase seems to have been a focus of Matlab development in the last few years.