On 11/19/2012 06:12 PM, Sturla Molden wrote: > I think NumPy and SciPy should consider to use OpenBLAS (a fork of > GotoBLAS2) instead of ATLAS or f2c'd Netlib BLAS for the binary releases. > > Here are its virtues: > > * Very easy to build: Just a makefile, no configuration script or > special build tools. > > * Building ATLAS can be a PITA. So why bother? > > * Faster than ATLAS, sometimes faster than MKL. > > * Multithreaded BLAS kernels: OpenMP on Unix, Windows threads on Windows. > > * The quality of its ancestor GotoBLAS is undisputed. I was the BLAS > implementation of choice for major HPC projects around the World. > > * Free as in BSD licensed. > > * Funded and developed for use in major Chinese HPC projects. Actively > maintained. (GotoBLAS2 is abandonware.) > > * Open source. The C sources are a pleasure to read, and very easy to > verify. > > * No OpenMP on Windows means no dependency on pthreads-win32 (an LGPL > library) when building with MinGW. > > * Builds on Windows with MinGW and MSYS, and perhaps even without MSYS. > > * Cygwin is not needed on Windows (this is just BS from the GotoBLAS > documentation). Thus, 64-buit builds are possible (I've built it using > TDM-GCC for Win64 and 32-bit MSYS).
+1. Even on CPUs that are not directly supported, this is at least better than reference BLAS. (On our AMD CPUs, which are too new to have a separate OpenBLAS implementation, the implementations for older AMD CPUs still outperform at least Intel MKL, because MKL does so poorly on these -- although ACML beats them both by a factor 2. And of course on supported CPUs (everything Intel and older AMD) OpenBLAS is wonderful. Dag Sverre _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
