Ralf Gommers <ralf.gomm...@gmail.com> wrote: > Thanks Sturla, interesting details as always. You didn't state your > preference by the way, do you have one?
I use Accelerate because it is the easier for me to use when building SciPy. But that is from a developer's perspective. As you know, Accelerate breaks a common (ab)use of multiprocessing on POSIX systems. While the bug is strictly speaking in multiprocessing (but partially fixed in Python 3.4 and later), it is still a nasty surprise to many users. E.g. a call to np.dot never returns, and there is no error message indicating why. That speaks against using it in the wheels. Accelerate, like MKL and FFTW, has nifty FFTs. If we start to use MKL and Accelerate for numpy.fft (which I sometimes have fantacies about), that would shift the balance the other way, in favour of Accelerate. Speed wise Accelerate wins for things like dot product of two vectors or multiplication of a vector and a matrix. For general matrix multiplication the performance is about the same, except when matrices are very small and Accelerate can benefit from the tiny GCD overhead. But then the Python overhead probably dominates, so they are going to be about equal anyway. I am going to vote ± 0. I am really not sure which will be the better for the binary wheels. They seem about equal to me right now. There are pros and cons with either. Sturla _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion