Well... anything that uses matrices is welcome for CUDA. Also many of the combinatorial algorithms have parallel versions
On 9 Март, 01:20, Robert Kern <robert.k...@gmail.com> wrote: > On Mon, Mar 8, 2010 at 17:05, yavor...@mail.bg <gerund...@gmail.com> wrote: > > Hi there, I kind of wanted to participate in this year's GSOC, and I > > looked through the suggestions and I couldn't help noticing there are > > no suggestions for optimizations for a particular architecture that > > could make SymPy faster. I am speaking particularly of GPU usage (e.g. > > CUDA) and parallel distributed memory architectures. As much as I've > > seen SymPy doesn't include any optimizations for that kind of usage > > and it would be nice (particularly now that there is PyCUDA & etc.). > > So I was thinking it might be a good suggestion to participate with > > this kind of idea... or is it against the idea of portability and > > therefore not acceptable for SymPy? The way I see it it could greatly > > increase performance in many algorithms if done properly... Thanks > > I doubt that many of SymPy's algorithms are particularly amenable to > hardware acceleration. Do you have something specific in mind? > > -- > Robert Kern > > "I have come to believe that the whole world is an enigma, a harmless > enigma that is made terrible by our own mad attempt to interpret it as > though it had an underlying truth." > -- Umberto Eco -- You received this message because you are subscribed to the Google Groups "sympy" group. To post to this group, send email to sy...@googlegroups.com. To unsubscribe from this group, send email to sympy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sympy?hl=en.
