On Sat, 31 Dec 2022 23:45:54 -0800 Bill Ross <bross_phobr...@sonic.net> wrote:
> How best to write a 1D ndarray as a block of doubles, for reading in > java as double[] or a stream of double? > > Maybe the performance of simple looping over doubles in python.write() > and java.read() is fine, but maybe there are representational diffs? > Maybe there's a better solution for the use case? Java is known to be big-endian ... but your CPU is probably little-endian. Numpy has the tools to represent an array of double BE. > Use case: I get the ndarray from keras, and it represents a 2D distance > matrix. I want to find the top-50 matches for each item, per row and > column. I'm looking at moving the top-50 task to java for its superior > parallel threading. (Java doesn't fork processes with a copy of the > array, which is ~5% of memory; rather one gets 1 process with e.g. 1475% > CPU.) What about numba or cython then ? Happy new year Jerome _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
