From khansen at stat.berkeley.edu  Wed Mar 18 16:53:33 2009
From: khansen at stat.berkeley.edu (Kasper Daniel Hansen)
Date: Wed, 18 Mar 2009 08:53:33 -0700
Subject: [Rd] R thread safe
In-Reply-To: <4f1819890903180711pcdd2bdbuc4eb15f7af8575f4@mail.gmail.com>
References: <49C0F021.8000108@health.sdu.dk>
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	<4f1819890903180711pcdd2bdbuc4eb15f7af8575f4@mail.gmail.com>
Message-ID: <9EED5E6C-DC10-4DCC-B840-FB352FDE00A9@stat.berkeley.edu>

On Mar 18, 2009, at 7:11 , Ted Byers wrote:

>  of thing I did when writing
> code to run on a supercomputer supporting vector algebra decades ago).
> With ITT, if Lapack was rewritten to take advantage of it, much of
> the code would look quite different from what it does today.  Of
> course, if you're already using it, I might as well shut up and go
> away.  ;-)  I am just learning to use it, as I am just learning to use
> R, so I am afraid I can't offer much more info than this, though.

For the purpose of matrix computations with BLAS/Lapack, use an  
optimized, multithreaded BLAS implementation. That way you use the  
multiple cores for "free" when you do matrix algebra, which is often  
(but not always) the heavy part of a computation. People have been  
doing this for a long time on OS X where it is default to use an  
implementation provided by Apple. I don't know exactly how to set this  
up for Linux or Windows.

Kasper



[Rd] R thread safe
Kasper Daniel Hansen