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Old 01-02-2009, 04:39 PM   #1
PlatinumX
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Question Why are GPU so much used for mass computing ?


Hi all,

More and more, you can hear about projects using GPU (especially those from nvidia) to process massive computing:
- MIT supercalculator
- french GENCI supercalculator
- password cracking (Elcomsoft company even put a patent)

I am just curious...

Thanks for info
 
Old 01-02-2009, 11:06 PM   #2
nigelc
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Maybe they have more power.
http://en.wikipedia.org/wiki/Graphics_processing_unit
 
Old 01-03-2009, 04:28 AM   #3
knudfl
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Just google .. gpu computing ..
Example
http://74.125.77.132/search?q=cache:...lnk&cd=7&gl=dk
Quote:
A current GPU has up to 16 pixel processors and 6
vertex processors that execute 4-dimensional vector
floating point instructions in parallel
....
 
Old 01-03-2009, 10:45 AM   #4
PlatinumX
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Thanks.
GPU computing is the keyword i missed.

I found this:

Quote:
"...allows you to benefit from the enormous potential that graphic cards available for the past four years possess. A standard GPU like ATI’s HD 2900 XT gives 500 Gflops power whereas a classic CPU gives only 8 Gflops."
http://www.gpucomputing.eu/index2.php?lang=en&id=1
 
Old 01-03-2009, 10:55 AM   #5
onebuck
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Hi,

You do get more power per bit for the money!
 
Old 01-04-2009, 04:49 PM   #6
Oxagast
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Probably the vector processor.
 
Old 01-04-2009, 07:42 PM   #7
nigelc
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Can we run SETI on them?
 
Old 01-05-2009, 12:01 AM   #8
nigelc
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How do we run seti on the GPU?
 
Old 01-06-2009, 07:16 AM   #9
knudfl
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nigelc # 8
Suggest : Please use your question as keyword for

Google .. run seti on the GPU ..

http://www.google.dk/search?hl=da&q=...meta=&aq=f&oq=
....

Last edited by knudfl; 01-06-2009 at 07:45 AM.
 
Old 01-06-2009, 04:11 PM   #10
sniff
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GPGPU

I work on GPGPU stuff, currently using it for computational biology, simulations of cells, and for pattern matching (neural networks).

The department got 6 9800GX2 from nvidia and I got a 4800x2 from ATI to work on. They are really good if you need to do the same thing lots of times. Both ATI and nvidia make hardware purely for GPGPU, ATI FireStream and Nvidia Tesla, we have a Tesla 8 somewhere.

There are IBM cell co-processors in existence too, but I think they are about Ł3K which is a fair number of GPUS.

There not suitable for all tasks and writing the programs can be a pain, easy to do it badly and not get any performance increase.
 
  


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