[Numpy-discussion] performance of numpy.array()

[Julian Taylor]

numpy 1.9 makes array(list) performance similar in performance to vstack
in 1.8 its very slow.

On 29.04.2015 17:40, simona bellavista wrote:
> on cluster A 1.9.0 and on cluster B 1.8.2
> 
> 2015-04-29 17:18 GMT+02:00 Nick Papior Andersen <nickpapior at gmail.com
> <mailto:nickpapior at 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 <afylot at gmail.com
>     <mailto:afylot at 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?
> 
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> 
> 
> 
>     -- 
>     Kind regards Nick
> 
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> 
> 
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