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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)
"...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."
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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