Bio-sequence database scanning on a GPU

Protein sequences with unknown functionality are often compared to a set of known sequences to detect functional similarities. Efficient dynamic programming algorithms exist for this problem, however current solutions still require significant scan times. These scan time requirements are likely to b...

Full description

Saved in:
Bibliographic Details
Main Authors: Weiguo Liu, Schmidt, B., Voss, G., Schroder, A., Muller-Wittig, W.
Format: Conference Proceeding
Language:English
Subjects:
Application software
Computer architecture
Computer graphics
Dynamic programming
Hardware
Heuristic algorithms
High performance computing
Protein engineering
Sequences
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Protein sequences with unknown functionality are often compared to a set of known sequences to detect functional similarities. Efficient dynamic programming algorithms exist for this problem, however current solutions still require significant scan times. These scan time requirements are likely to become even more severe due to the rapid growth in the size of these databases. In this paper, we present a new approach to bio-sequence database scanning using computer graphics hardware to gain high performance at low cost. To derive an efficient mapping onto this type of architecture, we have reformulated the Smith-Waterman dynamic programming algorithm in terms of computer graphics primitives. Our OpenGL implementation achieves a speedup of approximately sixteen on a high-end graphics card over available straightforward and optimized CPU Smith-Waterman implementations
ISSN:1530-2075
DOI:10.1109/IPDPS.2006.1639531