> > I am making heavy uses of OpenBlas which also uses OpenMP. > > Using the same queue manager prevents lots of CPU provisioning problem. > > Using multiple queue managers in the same code does not work as well > > because they are not aware of what the other one is doing. > > Normally OpenBLAS is built without OpenMP. Also, OpenMP is not fork safe > (cf. multiprocessing) but OpenBLAS' own threadpool is. So it is recommended > to build OpenBLAS without OpenMP dependency. > > That is: If you build OpenBLAS with OpenMP, numpy.dot will hang if used > together with multiprocessing.
I am effectively using a version of openblas built with openmp because Debian used to compile openblas this way. They seem to have reverted now. Note than I cannot use python multiprocessing because my threads work on a very large state vector. My current solution is to use python threading and nogil cython compiled routines but this sometimes lead to weird effects provisioning threads. This is why I wanted to try the pure openmp solution and found the aforementioned bug in cython.parallel. Is there somebody actively trying to make cython.parallel work correctly? - If yes, then my bug report should be of interest to this person. - If no, then one should avoid (and possibly deprecate) cython.parallel and find other ways to do things. Thanks to the replies. - L. _______________________________________________ cython-devel mailing list cython-devel@python.org https://mail.python.org/mailman/listinfo/cython-devel
