>> Are there libraries to help with this? > > First of all, since it's a thorny (and unsolved) problem, PyCUDA doesn't try > to get involved in it. Support it--yes, involved--no. That said, I'm not aware > of libraries that make autotunig significantly easier. Nicolas mentioned that > he's eyeing some machine learning techniques like the ones in Milepost gcc. > Nicolas, care to comment? Aside from that, Cray's "grouped, attributed > orthogonal search" [1] sounds useful.
The ideas I have are too immature (and I don't have much time to explore them, sadly). However, my first step would be to integrate more information about a given kernel execution (e.g. profiling counters). I need to see if there is a way to make that fit nicely in PyCUDA (e.g. regex on the profile log) to help the iterative "machine learning" approach to auto-tuning find a good answer, quickly. Hopefully I'll have more to say soon. Best, -- Nicolas Pinto Ph.D. Candidate, Brain & Computer Sciences Massachusetts Institute of Technology, USA http://web.mit.edu/pinto _______________________________________________ PyCUDA mailing list [email protected] http://tiker.net/mailman/listinfo/pycuda_tiker.net
