Design and Implementation of a CUDA-Compatible GPU-based Core for Gapped BLAST Algorithm

Cheng Ling, Khaled Benkrid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents the first ever reported implementation of the Gapped Basic Local Alignment Search Tool (Gapped BLAST) for biological sequence alignment, with the Two-Hit method, on CUDA (compute unified device architecture)-compatible Graphic Processing Units (GPUs). The latter have recently emerged as relatively low cost and easy to program high performance platforms for general purpose computing. Our Gapped BLAST implementation on an NVIDIA Geforce 8800 GTX GPU is up to 2.7x quicker than the most optimized CPU-based implementation, namely NCBI BLAST, running on a Pentium4 3.4 GHz desktop computer with 2GB RAM. (C) 2010 Published by Elsevier Ltd.

Original languageEnglish
Title of host publicationICCS 2010 - INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, PROCEEDINGS
Place of PublicationAMSTERDAM
PublisherElsevier B.V.
Pages495-504
Number of pages10
ISBN (Print)*****************
DOIs
Publication statusPublished - 2010
EventInternational Conference on Computational Science(ICCS) - Amsterdam
Duration: 31 May 20102 Jun 2010

Conference

ConferenceInternational Conference on Computational Science(ICCS)
CityAmsterdam
Period31/05/102/06/10

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