XSW: Accelerating Biological Database Search on Xeon Phi

Lipeng Wang, Yuandong Chan, Xiaohui Duan, Haidong Lan, Xiangxu Meng, Weiguo Liu
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引用次数: 30

Abstract

In this paper we present XSW, a new parallel Smith-Waterman algorithm for searching protein sequence databases on the Xeon Phi coprocessor. In order to make full use of the compute power of the many-core Xeon Phi hardware, we have used a two-level parallelization scheme: the thread level coarse-grained and VPU level fine-grained parallelism to implement our algorithm. At the thread level, XSW employs multi-threading to implement the SIMD parallelism. At the VPU level, we have used the Knights Corner instructions to gain more data parallelism. We have also reorganized the database and made use of the parallel shuffling operations on Xeon Phi to achieve better I/O efficiency. Evaluations on real protein sequence databases show that XSW achieves the peak performance of 70 GCUPS on a single Intel Xeon Phi 7110 card. Compared to two other well parallelized Smith-Waterman algorithms: the multi-core CPU-based SWIPE and the GPU-based CUDASW++ 3.0, XSW achieves much better performance than SWIPE. And XSW achieves comparable performance but better accuracy than CUDASW++ 3.0. To our knowledge this is the first reported implementation of the Smith-Waterman algorithm on Xeon Phi. The executable binary code of XSW is available at http://sdu-hpcl.github.io/XSW/.
XSW:加速Xeon Phi处理器上的生物数据库检索
在Xeon Phi协处理器上,我们提出了一种新的并行Smith-Waterman算法XSW来搜索蛋白质序列数据库。为了充分利用多核Xeon Phi硬件的计算能力,我们采用了线程级粗粒度和VPU级细粒度并行两级并行方案来实现我们的算法。在线程级别,XSW使用多线程来实现SIMD并行性。在VPU级别,我们使用了Knights Corner指令来获得更多的数据并行性。我们还重新组织了数据库,并利用Xeon Phi处理器上的并行洗牌操作来实现更好的I/O效率。对真实蛋白质序列数据库的评估表明,XSW在单个Intel Xeon Phi 7110卡上达到70 GCUPS的峰值性能。与另外两种并行化良好的Smith-Waterman算法(基于多核cpu的SWIPE和基于gpu的cudasw++ 3.0)相比,XSW的性能要比SWIPE好得多。XSW达到了与cudasw++ 3.0相当的性能,但精度更高。据我们所知,这是Smith-Waterman算法在Xeon Phi上的第一个实现。XSW的可执行二进制代码可从http://sdu-hpcl.github.io/XSW/获得。
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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