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 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion