基于FPGA的系统发育树重构的最大简约算法硬件加速

Henry Block, T. Maruyama
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引用次数: 5

摘要

本文提出了一种基于FPGA的系统发育树重构的硬件加速方法。该算法基于渐进树邻域的随机局部搜索。硬件架构被划分为不同的单元,每个单元执行算法的特定任务,以利用FPGA的并行处理能力。我们展示了四个真实世界生物数据集的结果,并将它们与两个程序的结果进行了比较:我们的c++实现和TNT(一个系统发育分析程序)。在我们的c++实现中获得了很高的加速速率,但在TNT上没有,TNT在某些情况下甚至表现得更快。我们以讨论这个问题来结束我们的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A hardware acceleration of a phylogenetic tree reconstruction with maximum parsimony algorithm using FPGA
In this paper, we present a hardware acceleration approach for a phylogenetic tree reconstruction with maximum parsimony algorithm using FPGA. The algorithm is based on a stochastic local search with the progressive tree neighborhood. The hardware architecture is divided in different units, each of which performs a specific task of the algorithm, to take advantage of the parallel processing capabilities of the FPGA. We show results for four real-world biological datasets, and compare them against results from two programs: our C++ implementation and TNT (a program for phylogenetic analysis). High acceleration rates are obtained against our C++ implementation, but not against TNT, which even shows to be faster in some cases. We conclude our work with a discussion on this issue.
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