In an effort to speed up computations for research proposes academics and other scientific elites have turned to the processing power of graphics cards. GPUs may not hold the frequency speed records but they certainly have more math processing power than any single CPU today.
Organizations such as
www.GPGPU.org have devoted their efforts and resources to speed things up in the fields of physics simulations, medical imaging, speech recognition, and matrix/vector operations like Fast Fourier Transform (FFT) and Ray Tracing. It has been shown that the Intel Pentium 4 3.0 GHz processors can produce 12 GFLOPs / 5.96 GByte per second. Interestingly, by using graphics cards they can produce much higher throughput. The ATI X1800XT can produce almost 7 times as much throughput with 83 GFLOPs / 42 GByte per second.
In a paper by Daniel Reiter Horn, Mike Houston, and Pat Hanrahan at Stanford University, they show results of CPUs as well as video cards using hidden Markov models (HMMs) to solve fuzzy protein sequence matching calculations. The paper states "...unlike the ATI hardware, the Nvdia hardware cannot directly use previous outputs as inputs for future iterations without a copy."
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