2015-01-27 0:16 GMT+01:00 Sturla Molden <[email protected]>: > On 26/01/15 16:30, Carl Kleffner wrote: > > > Thanks for all your ideas. The next version will contain an augumented > > libopenblas.dll in both numpy and scipy. On the long term I would > > prefer an external openblas wheel package, if there is an agreement > > about this among numpy-dev. > > > Thanks for all your great work on this. > > An OpenBLAS wheel might be a good idea. Probably we should have some > sort of instruction on the website how to install the binary wheel. And > then we could include the OpenBLAS wheel in the instruction. Or we could > have the OpenBLAS wheel as a part of the scipy stack. > > But make the bloated SciPy and NumPy wheels work first, then we can > worry about a dedicated OpenBLAS wheel later :-) > > > > Another idea for the future is to conditionally load a debug version of > > libopenblas instead. Together with the backtrace.dll (part of > > mingwstatic, but undocumentated right now) a meaningfull stacktrace in > > case of segfaults inside the code comiled with mingwstatic will be given. > > An OpenBLAS wheel could also include multiple architectures. We can > compile OpenBLAS for any kind of CPUs and and install the one that fits > best with the computer. >
OpenBLAS in the test wheels is build with DYNAMIC_ARCH, that is all assembler based kernels are included and are choosen at runtime. Non optimized parts of Lapack have been build with -march=sse2. > > Also note that an OpenBLAS wheel could be useful on Linux. It is clearly > superior to the ATLAS libraries that most distros ship. If we make a > binary wheel that works for Windows, we are almost there for Linux too :-) > I have in mind, that binary wheels are not supported for Linux. Maybe this could be done as conda package for Anaconda/Miniconda as an OSS alternative to MKL. > > For Apple we don't need OpenBLAS anymore. On OSX 10.9 and 10.10 > Accelerate Framework is actually faster than MKL under many > circumstances. DGEMM is about the same, but e.g. DAXPY and DDOT are > faster in Accelerate. > > > Sturla > > > > > > > > > > > > > > > > > > > > > > > > > > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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