CUDA-Parttree: GPU中的多序列对齐并行策略

Caina Razzolini, A. Melo
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引用次数: 1

摘要

在本文中,我们提出并评估了CUDA-Parttree,这是一种并行策略,它在GPU上执行matfft Parttree多序列对齐工具的第一阶段(使用6mers进行距离矩阵计算)。与Parttree相比,CUDA-Parttree在Cyclodex gly tran(50,280个序列)集的距离矩阵计算上获得了6.10倍的加速,将执行时间从33.94s减少到5.57s。包括数据转换和GPU之间的移动,加速速度为2.59倍。将序列设置为Syn 100000(100,000个序列),可以获得4.46倍的加速,将执行时间从209.54秒减少到47.00秒。
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CUDA-Parttree: A Multiple Sequence Alignment Parallel Strategy in GPU
In this paper, we propose and evaluate CUDA-Parttree, a parallel strategy that executes the first phase of the MAFFT Parttree Multiple Sequence Alignment tool (distance matrix calculation with 6mers) on GPU. When compared to Parttree, CUDA-Parttree obtained a speedup of 6.10x on the distance matrix calculation for the Cyclodex gly tran (50, 280 sequences) set, reducing the execution time from 33.94s to 5.57s. Including data conversion and movement to/from the GPU, the speedup was 2.59x. With the sequence set Syn 100000 (100, 000 sequences), a speedup of 4.46x was attained, reducing execution time from 209.54s to 47.00s.
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