the code i ported was originally matlab. if you can write the operations without explicit loops (using matlab's builtins) then it should be able to translate t

the code i ported was originally matlab. if you can write the operations without explicit loops (using matlab's builtins) then it should be able to translate things fairly well to multiple processors. i don't know much about matlab's gpu support (when i looked, you needed third party libs - looks like that has changed?) but again, if it's standard transforms and matrix operations they should be able to make it fairly efficient. in our case the matlab code had explicit loops (in a sense i was lucky - the inner kernel operations were messy enough to need explicit coding, but regular enough to be handled efficiently on a gpu) and that's what really kills you (because you're bouncing out of optimised c code into their interpreter). just moving from matlab to c (on the cpu) also gave us a significant speedup. what i'm saying, in a slow rambling way, is that calculating a bunch of sines should be as fast in matlab as in hand-coded c or opencl (on gpu and cpu respectively). because that can be expressed as a vector operation and matlab will have invested a lot of time and effort into making that code fast.