Speeding up subset seed algorithm for intensive protein sequence comparison

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.

• Type: Conference
• Year: 2008
• Where: RIVF
• Authors: Van Hoa Nguyen, Dominique Lavenier
• Keywords: Fine Grained Parallelism, Intensive Protein Sequence, Internet Technology, RIVF 2008, Subset Seed Algorithm