Eliot Moss <moss <at> cs.umass.edu> writes: > True ... it also made me think of Python, which is designed to use > parallelized numpy (etc.) libraries, optimized for your platform. > Can use all the hardware threads on your machine, as well as make > good use of vector extensions such as AVX. A 64-bit (x86-64) > version will give best use of vector processing, in my > experience. > > Regards -- Eliot Moss
numpy is only as parallel as the underlying BLAS/LAPACK library that it uses is. So if you're using Cygwin's openblas then you're in decent shape. But I don't think cv_adams spends much time (if any?) in BLAS/LAPACK dense linear algebra functions, I think it's mostly dominated by function evaluation time. -Tony -- Problem reports: http://cygwin.com/problems.html FAQ: http://cygwin.com/faq/ Documentation: http://cygwin.com/docs.html Unsubscribe info: http://cygwin.com/ml/#unsubscribe-simple
