On 06/08/07, David Cournapeau <[EMAIL PROTECTED]> wrote: > Well, when I proposed the SIMD extension, I was willing to implement the > proposal, and this was for a simple goal: enabling better integration > with many numeric libraries which need SIMD alignment. > > As nice as a custom allocator might be, I will certainly not implement > it myself. For SIMD, I think the weight adding complexity / benefit > worth it (since there is not much change to the API and implementation), > and I know more or less how to do it; for custom allocator, that's an > entirely different story. That's really more complex; static pools may > be useful in some cases (but that's not obvious, since only the data are > allocated with this buffer, everything else being allocated through the > python memory allocator, and numpy arrays have pretty simple memory > allocation patterns).
I have to agree. I can hardly volunteer David for anything, and I don't have time to implement this myself, but I think a custom allocator is a rather special-purpose tool; if one were to implement one, I think the way to go would be to implement a subclass of ndarray (or just a constructor) that allocated the memory. This could be done from python, since you can make an ndarray from scratch using a given memory array. Of course, making temporaries be allocated with the correct allocator will be very complicated, since it's unclear which allocator should be used. Adding SIMD alignment should be a very small modification; it can be done as simply as using ctypes to wrap posix_memalign (or a portable version, possibly written in python) and writing a simple python function that checks the beginning data address. There's really no need to make it complicated. Anne _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
