Protein Structure Prediction with Parallel Algorithms Orthogonal to Parallel Platforms

M. Saldanha, P. L. D. Souza
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引用次数: 0

Abstract

The problem of Protein Structure Prediction (PSP) is known to be computationally expensive, which calls for the application of high performance techniques. In this project, parallel PSP algorithms found in the literature are being accelerated and ported to different parallel platforms, producing a set of algorithms that it is diverse in terms of the parallel architectures and parallel programming models used. The algorithms are intended to help other research projects and they have also been made publicly available so as to support the development of more elaborate prediction algorithms. We have thus far produced a set of 16 algorithms (mixing CUDA, OpenMP, MPI and/or complexity reduction optimizations); during its development, two algorithms that promote high performance were proposed, and they have been written in an article that was accepted in the International Conference on Computational Science (ICCS).
蛋白质结构预测的平行算法与平行平台
众所周知,蛋白质结构预测(PSP)问题的计算成本很高,这需要高性能技术的应用。在这个项目中,在文献中发现的并行PSP算法正在被加速并移植到不同的并行平台上,产生了一组在并行架构和并行编程模型方面不同的算法。这些算法旨在帮助其他研究项目,它们也已公开,以支持更复杂的预测算法的发展。到目前为止,我们已经产生了一组16算法(混合CUDA, OpenMP, MPI和/或复杂性降低优化);在其开发过程中,提出了两种促进高性能的算法,并将其写在一篇文章中,该文章被国际计算科学会议(ICCS)接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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