Gnata Xavier wrote: > Well of course my goal was not to say that my simple testcase can be > copied/pasted into numpy :) > Of ourse it is one of the best case to use openmp. > Of course pragma can be more complex than that (you can tell variables > that can/cannot be shared for instance). > > The size : Using openmp will be slower on small arrays, that is clear > but the user doing very large computations is smart enough to know when > he need to split it's job into threads. The obvious solution is to > provide the user with // and non // functions.
IMHO, that's a really bad solution. It should be dynamically enabled (like in matlab, if I remember correctly). And this means having a plug subsystem to load/unload different implementation... that is one of the thing I was interested in getting done for numpy 1.1 (or above). For small arrays: how much slower ? Does it make the code slower than without open mp ? For example, what does your code says when N is 10, 100, 1000 ? > > sse : sse can help a lot but multithreading just scales where sse > mono-thread based solutions don't. It depends: it scales pretty well if you use several processus, and if you can design your application in a multi-process way. > > Build/link : It is an issue. It has to be tested. I do not know because > I haven't even tried. > > So, IMHO it would be nice to try to put some OpenMP simple pragmas into > numpy *only to see what is going on*. > > Even if it only work with gcc or even if...I do not know... It would be > a first step. step by step :) I agree about the step by step approach; I am just not sure I agree with your steps, that's all. Personally, I would first try getting a plug-in system working with numpy. But really, prove me wrong. Do it, try putting some pragma at some places in the ufunc machinery or somewhere else; as I said earlier, I would be happy to add support for open mp at the build level, at least in numscons. I would love being proven wrong and having a numpy which scales well with multi-core :) cheers, David _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
