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A hardware acceleration of a phylogenetic tree reconstruction with maximum parsimony algorithm using FPGA

机译:使用FPGA的最大定义算法的系统发育树重建硬件加速度

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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.
机译:本文介绍了使用FPGA的最大定义算法的系统发育树重建的硬件加速方法。该算法基于与渐进式树邻居的随机本地搜索。硬件架构以不同的单位划分,每个单元执行算法的特定任务,以利用FPGA的并行处理能力。我们向4个现实世界生物数据集显示结果,并将它们与两个程序的结果进行比较:我们的C ++实现和TNT(系统发育分析程序)。在我们的C ++实施中获得高加速率,但不能反对TNT,甚至在某些情况下表现得更快。我们在关于这个问题的讨论中得出结论。

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