You could try and install your own numpy to check whether that resolves the problem.
2015-04-29 17:40 GMT+02:00 simona bellavista <afy...@gmail.com>: > on cluster A 1.9.0 and on cluster B 1.8.2 > > 2015-04-29 17:18 GMT+02:00 Nick Papior Andersen <nickpap...@gmail.com>: > >> Compile it yourself to know the limitations/benefits of the dependency >> libraries. >> >> Otherwise, have you checked which versions of numpy they are, i.e. are >> they the same version? >> >> 2015-04-29 17:05 GMT+02:00 simona bellavista <afy...@gmail.com>: >> >>> I work on two distinct scientific clusters. I have run the same python >>> code on the two clusters and I have noticed that one is faster by an order >>> of magnitude than the other (1min vs 10min, this is important because I run >>> this function many times). >>> >>> I have investigated with a profiler and I have found that the cause of >>> this is that (same code and same data) is the function numpy.array that is >>> being called 10^5 times. On cluster A it takes 2 s in total, whereas on >>> cluster B it takes ~6 min. For what regards the other functions, they are >>> generally faster on cluster A. I understand that the clusters are quite >>> different, both as hardware and installed libraries. It strikes me that on >>> this particular function the performance is so different. I would have >>> though that this is due to a difference in the available memory, but >>> actually by looking with `top` the memory seems to be used only at 0.1% on >>> cluster B. In theory numpy is compiled with atlas on cluster B, and on >>> cluster A it is not clear, because numpy.__config__.show() returns NOT >>> AVAILABLE for anything. >>> >>> Does anybody has any insight on that, and if I can improve the >>> performance on cluster B? >>> >>> _______________________________________________ >>> NumPy-Discussion mailing list >>> NumPy-Discussion@scipy.org >>> http://mail.scipy.org/mailman/listinfo/numpy-discussion >>> >>> >> >> >> -- >> Kind regards Nick >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > -- Kind regards Nick
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