David Cournapeau wrote: > Hi, > > numpy 1.0.5 is on the way, and I was wondering about numpy's future. I > myself have some ideas about what could be done; has there been any > discussion behind what is on 1.1 trac's roadmap ? Some of the things I > would like to see myself: > - a framework for plug-in architecture, that is the ability for numpy > to load/unload some libraries at runtime, plus a common api to access > the functions. Example: instead of calling directly atlas/etc..., it > would load the dll at runtime, so that other libraries can be loaded > instead (numpy itself could load different runtimes depending on the > CPU, for example: SSE vs SSE2 vs SSE3, multi-thread vs non > multi-thread). That would require the ability to build loadable > libraries (numscons, or a new numpy.distutils command). > - a pure C core library for some common operations. For example, I > myself would really like to be able to use the fft in some C extensions. > Numpy has a fft, but I cannot access it from C (well, I could access the > python fft from C, but that would be... awkward); same for blas/lapack. > I really like the idea of a numpy "split" into a core C library reusable > by many C extensions, and python wrappers (in C, cython, ctypes, > whatever). That would be a huge work, of course, but hopefully can be > done gradually and smoothly. Only having fft + some basic blas/lapack > (dot, inv, det, etc...) and some basic functions (beta, gamma, digamma) > would be great, for example. > - a highly optimized core library for memory copy, simple addition, > etc... basically, everything which can see huge improvements when using > MMX/SSE and co. This is somewhat linked to point 1. This would also > require more sophisticated memory allocator (aligned, etc...). > > What do people think about this ? Is that a direction numpy developers > are interested in ? > > cheers, > > David > > Looks great :) Something like http://idlastro.gsfc.nasa.gov/idl_html_help/TOTAL.html (Thread Pool Keywords) would be nice. A "total like" function could be a great pathfinder a put threads into numpy keeping the things as simple as they should remain. Not sure we need that is numpy in 1.1 but IMHO we need that in a near future (because every "array oriented" libs are now threaded).
Xavier _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion