[Numpy-discussion] Numpy-discussion Digest, Vol 6, Issue 18

James A. Bednar jbednar@inf.ed.ac...
Fri Mar 9 05:03:42 CST 2007

|  From: Robert Kern <robert.kern@gmail.com>
|  Subject: Re: [Numpy-discussion] in place random generation
|  Daniel Mahler wrote:
|  > On 3/8/07, Charles R Harris <charlesr.harris@gmail.com> 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...


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