HPMA: High-performance Metagenomic Alignment Tool, on a Large-Scale GPU Cluster


SAVRAN İ., Rose J. R.

IEEE International Conference on Bioinformatics and Biomedicine - Medical Informatics and Decision Making, Washington, Kiribati, 9 - 12 November 2015, pp.629-634 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/bibm.2015.7359757
  • City: Washington
  • Country: Kiribati
  • Page Numbers: pp.629-634

Abstract

In this paper, we present HPMA, a graphics processing unit (GPU) accelerated meta-genome sequence alignment algorithm for a collection of DNA sequences. This algorithm supports all-to-all pairwise local alignment on NVIDIA GPUs. HPMA builds on an GPU alignment algorithm that we developed earlier with the addition of a filter module. We designed and developed this new kernel function based on the suffix array data structure. The filter module improves performance by identifying a subset of sequences which meet a user-defined similarity threshold and should be considered for alignment. HPMA has the ability to balance the workload between CPU and GPU. HPMA allows us to preprocess massively large metagenomes in a reasonable amount of time in response to increasing speed of NGS sequencers. The performance of HPMA has been evaluated on a cluster of Kepler-based Tesla K20 GPUs using a variety of short DNA sequence datasets.