基于NVIDIA CUDA和MPI的Aho-Corasick和Wu-Manber算法的混合并行实现
A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database
摘要：
多个匹配算法被用来从一个有限的模式集在一个大的输入字符串中定位模式的出现。Aho-Corasick和Wu-Manber是两种最著名的多重匹配算法，它们需要更高的计算能力，特别是在必须处理大规模数据集的情况下，这在计算生物学应用中很常见。在过去的几年里，图形处理单元（GPU）已经发展成为强大的并行处理器，在科学计算中优于中央处理单元（CPU）。此外，可以并行使用多个GPU，形成混合计算机集群配置，以实现更高的处理吞吐量。本文评估的Aho-Corasick和Wu-Manber算法在混合GPU集群上的并行实现的加速比，当用于处理人类基因组的表达序列标签的快照和不同的问题参数。
英文摘要：
Multiple matching algorithms are used to locate the occurrences of patterns from a finite pattern set in a large input string. Aho-Corasick and Wu-Manber, two of the most well known algorithms for multiple matching require an increased computing power, particularly in cases where large-size datasets must be processed, as is common in computational biology applications. Over the past years, Graphics Processing Units (GPUs) have evolved to powerful parallel processors outperforming Central Processing Units (CPUs) in scientific calculations. Moreover, multiple GPUs can be used in parallel, forming hybrid computer cluster configurations to achieve an even higher processing throughput. This paper evaluates the speedup of the parallel implementation of the Aho-Corasick and Wu-Manber algorithms on a hybrid GPU cluster, when used to process a snapshot of the Expressed Sequence Tags of the human genome and for different problem parameters.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
