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Speeding up Subset Seed Algorithm for Intensive Protein Sequence Comparison

van Hoa Nguyen 1, * Dominique Lavenier 1
* Corresponding author
1 SYMBIOSE - Biological systems and models, bioinformatics and sequences
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Sequence similarity search is a common and repeated task in molecular biology. The rapid growth of genomic databases leads to the need of speeding up the treatment of this task. In this paper, we present a subset seed algorithm for intensive protein sequence comparison. We have accelerated this algorithm by using indexing technique and fine grained parallelism of GPU and SIMD instructions. We have implemented two programs: iBLASTP, iTBLASTN. The GPU (SIMD) implementation of the two programs achieves a speed up ranging from 5.5 to 10 (4 to 5.6) compared to the BLASTP and TBLASTN of the BLAST program family, with comparable sensitivity.
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Submitted on : Monday, September 15, 2008 - 1:07:56 AM
Last modification on : Tuesday, June 15, 2021 - 4:26:13 PM
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  • HAL Id : inria-00321457, version 1


van Hoa Nguyen, Dominique Lavenier. Speeding up Subset Seed Algorithm for Intensive Protein Sequence Comparison. 6th IEEE International Conference on research, innovation & vision for the future, Jul 2008, Ho Chi Minh Ville, Vietnam. ⟨inria-00321457⟩



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