| From: Robert Kern <[EMAIL PROTECTED]> | Subject: Re: [Numpy-discussion] in place random generation | | Daniel Mahler wrote: | > On 3/8/07, Charles R Harris <[EMAIL PROTECTED]> wrote: | | >> Robert thought this might relate to Travis' changes adding | >> broadcasting to the random number generator. It does seem | >> certain that generating small arrays of random numbers has a | >> very high overhead. | > | > Does that mean someone is working on fixing this? | | It's not on the top of my list, no.
I just wanted to put in a vote saying that generating a large quantity of small arrays of random numbers is quite important in my field, and is something that is definitely slowing us down right now. We often simulate neural networks whose many, many small weight matrices need to be initialized with random numbers, and we are seeing quite slow startup times (on the order of minutes, even though reloading a pickled snapshot of the same simulation once it has been initialized takes only a few seconds). The quality of these particular random numbers doesn't matter very much for us, so we are looking for some cheaper way to fill a bunch of small matrices with at least passably random values. But it would of course be better if the regular high-quality random number support in Numpy were speedy under these conditions... Jim _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
