-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I am working on two programs using NumPy for the OLPC project. In both cases the performance is limited by the FFT. The OLPC machine uses a AMD Geode CPU, which is generally slow, but especially bad at double-precision floating point. It would be a major improvement if we could compile NumPy to use complex64 for FFTs instead of complex128, and might even increase the probability of NumPy being provided as a learning tool to millions of children.
I know that FFTW can be compiled to run in single precision. What would it take to make NumPy use a single-precision FFT library? If absolutely necessary, it might be possible to ship a patched version of NumPy, but any other solution would be preferable. A compile-time configuration option in NumPy would be ideal. - --Ben Schwartz -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.6 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org iD8DBQFGVdIlUJT6e6HFtqQRAlCIAJ9o6DFMasm/ZABr8WMdRlmy/bTTMACZAXYn dCxeFPJtMbd/2YuYt9+4hDM= =aRQL -----END PGP SIGNATURE----- _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
