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Re: st: GPUs and statistical computing
If GPU-like hardware was really useful for statistical and other
mathematical programming, it shouldn't be hard to produce a
double-precision version. The real question how utile GPU-like hardware
would be for general-purpose statistical/mathematical programming. The
problem is that fine-grain multiprocessing (using a lot of processors at
the same time, not just 2 or 4 like contemporary PCs) only helps for
certain kinds of problems, and it often requires a good deal
special-purpose programming -- like the programming discussed in the
article -- to accomplish anything.
The authors of the cited article say that the GPU works in a SIMD
(single instruction, multiple data) fashion, which means that all of the
processing units do the same thing to different bits of data. There are
occasions in statistical programming when doing the same thing
simultaneously to different bits of data is exactly what you want. If
you want to find out the mean or the sum of a set of numbers, for
example, you can divide your data up into N = # of processors pieces
(240 in the article's example) and have each processor sum their piece
of data. These piecewise sums would then be available to all of the
processors through shared memory (also mentioned in the article) and
then, perhaps, half of the processors would add two of the first round
sums, a quarter of the processors would add two of the second round
sums, etc., until the data were all summed. Not all problems are well
suited to this kind of approach, and my general impression is that while
SIMD works great for certain applications, it works poorly for most.
Michael
David Airey wrote:
.
In the following interesting article,
http://www.biomedcentral.com/1756-0500/2/149
the authors "...show that a single GPU machine containing three GPUs
that costs $2000 performs similarly to 150 CPUs on a compute cluster.
These CPUs, including the added infrastructure and support cost of the
cluster system, would cost approximately $82,500."
Occasionally I ask Stata Corp about the possibility of parallel
computing using graphics processing chips, for example:
http://www.stata.com/statalist/archive/2009-06/msg00329.html
The problem seems to be that GPUs do not generally support
double-precision arithmetic. I guess one question for the authors of
the above article is: fast yes, but precise?
-Dave
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--
Michael I. Lichter, Ph.D. <[email protected]>
Research Assistant Professor & NRSA Fellow
UB Department of Family Medicine / Primary Care Research Institute
UB Clinical Center, 462 Grider Street, Buffalo, NY 14215
Office: CC 126 / Phone: 716-898-4751 / FAX: 716-898-3536
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* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/