I would be curious to have some examples. Number crunching is almost always parallelizable. Computing is not always calculation. As long as you can simplify yo

I would be curious to have some examples. Number crunching is almost always parallelizable. Computing is not always calculation. As long as you can simplify your program as a set of input/output models, OpenCL/CUDA will help a lot. Of course it's not a silver bullet, so often one might have to reorganize the problem to have a better performing solution. The more you can tweak an algorithm to fit inside a set of stricter constraint, the better it will perform on a GPU. Of course, if you have a hard problem, it's always better to be able to build hardware which targets a particular problem for optimal performance. Maybe I'd be more interested in multithreading when CPU will have at least 16 or 32 cores. 4 or 8 cores is not a lot.