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Re: large matrix operations [message #62900 is a reply to message #62889] Mon, 13 October 2008 10:39 Go to previous messageGo to previous message
David Fanning is currently offline  David Fanning
Messages: 11724
Registered: August 2001
Senior Member
Vince Hradil writes:

> So much for that theory...
>
> Hardware:
> IDL> print, !version
> { x86 Win32 Windows Microsoft Windows 7.0 Oct 25 2007 32 64}
>
> Results:
> % TEST: Allocating A array
> % TEST: took 0.14000010 sec
> % TEST: Allocating B array
> % TEST: took 0.21899986 sec
> % TEST: A#B
> % TEST: took 40.878000 sec
> % TEST: matrix_multipy(A,B)
> % TEST: took 42.284000 sec
> % TEST: transpose(A)#B
> % TEST: took 42.645000 sec
> % TEST: matrix_multipy(A,B,/atranspose)
> % TEST: took 43.449000 sec
> % TEST: transpose(temporary(A))#B
> % TEST: took 43.387000 sec
> % TEST: matrix_multipy(temporary(A),B,/atranspose)
> % TEST: took 50.029000 sec

I'm glad to hear this, because I always thought that theory
leaned a little toward the bogus side. In my experience, slow
matrix operations are always due to memory paging problems.
According to a VERY interesting program on the History Channel
last night, shamanic rituals are sometimes effective in these
situations where we are up against demonic forces.

Cheers,

David

--
David Fanning, Ph.D.
Fanning Software Consulting, Inc.
Coyote's Guide to IDL Programming: http://www.dfanning.com/
Sepore ma de ni thui. ("Perhaps thou speakest truth.")
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