Abstract
Graphics processing units (GPUs) have evolved to become powerful, programmable vector processing units. Furthermore, the maximum processing power of current generation GPUs is technically superior to that of current generation CPUs (central processing units), and that power is doubling approximately every nine months, about twice the rate of Moore’s law. This research represents the first successful application of GPU vector processing to an existing scientific computing software package, specifically an application for computing the tertiary (3D) geometric structures of protein molecules from x-ray crystallography data. A framework for applying GPU parallel processing to other computational tasks is developed and discussed, and an example of the benefits of taking advantage of the visualization potential of newer GPUs in scientific computing is presented.
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Payne, B.R., Owen, G.S., Weber, I. (2005). Accelerating Protein Structure Recovery Using Graphics Processing Units. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428831_56
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DOI: https://doi.org/10.1007/11428831_56
Publisher Name: Springer, Berlin, Heidelberg
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