What\'s the state of the art with regards to getting numpy
to use mutliple cores (on Intel hardware) for things like inner and outer vector products, vector-mat
You should probably start by checking whether the Atlas build that numpy is using has been built with multi-threading. You can build and run this to inspect the Atlas configuration (straight from the Atlas FAQ):
main()
/*
* Compile, link and run with something like:
* gcc -o xprint_buildinfo -L[ATLAS lib dir] -latlas ; ./xprint_buildinfo
* if link fails, you are using ATLAS version older than 3.3.6.
*/
{
void ATL_buildinfo(void);
ATL_buildinfo();
exit(0);
}
If you have don't have a multithreaded version of Atlas: "there's your problem". If it is multithreaded, then you need to exercise one of the multithreaded BLAS3 routines (probably dgemm), with a suitably large matrix-matrix product and see whether threading is used. I think I am right in saying that neither BLAS 2 and BLAS 1 routines in Atlas support multithreading (and with good reason because there is no performance advantage except at truly enormous problem sizes).