On 02/06/2012 06:03 PM, Torsten Bronger wrote:
Robert Cimrman writes:
On 02/06/2012 10:24 AM, Torsten Bronger wrote:
Does anybody have a howto for getting multicore support for SfePy? Something tested on Ubuntu would be ideal but is not necessary. I use umfpack, which needs a BLAS implementation. I suspect the BLAS determines whether all cores are used or only one.
I am quite a new user of kubuntu, so cannot tell... It would be nice to be able to use multiple cores - maybe ask at the scipy mailing list? All we need is to make scipy/numpy use parallel blas.
Before I ask on the scipy mailing list I must understand what you mean. So far, my SfePy uses its own version of umfpack, correct? So I must use another solver, namely a solver which uses some module in scipy/numpy. And then, my scipy/numpy installation must be made muticode-ready. ??
No, sfepy uses umfpack via 'ls.scipy_direct' solver ('ls.umfpack' is its alias)
- it's just a wrapper setting up arguments and calling scipy.sparse.linalg.dsolve.spsolve().
Now scipy itself uses either the umfpack wrappers bundled with it (deprecated) or the umfpack scikit. In my kubuntu, the wrappers in scipy.sparse.linalg.dsolve.umfpack. Then the wrappers in turn use the /usr/lib/libumfpack.so from libsuitesparse-dev.
I hope it's clear(er) now :)