Streaming Algorithms for Biological Sequence Alignment on GPUs

• Published in: IEEE transactions on parallel and distributed systems Vol. 18; no. 9; pp. 1270 - 1281
• Main Authors: Liu Weiguo, Schmidt, B., Voss, G., Muller-Wittig, W.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2007; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Algorithms; Alignment; Analogies; Bioinformatics; Biological; Biology computing; Central Processing Unit; Computer architecture; Computer graphics; dynamic programming; GPGPU; graphics hardware; Hardware; High performance computing; Molecular biology; multiple sequence alignment; pairwise sequence alignment; Personal computers; Runtime; Sequences; Streaming architectures; Studies; Tasks
• ISSN: 1045-9219; 1558-2183
• DOI: 10.1109/TPDS.2007.1069

Sequence alignment is a common and often repeated task in molecular biology. Typical alignment operations consist of finding similarities between a pair of sequences (pairwise sequence alignment) or a family of sequences (multiple sequence alignment). The need for speeding up this treatment comes from the rapid growth rate of biological sequence databases: every year their size increases by a factor of 1.5 to 2. In this paper, we present a new approach to high-performance biological sequence alignment based on commodity PC graphics hardware. Using modern graphics processing units (GPUs) for high-performance computing is facilitated by their enhanced programmability and motivated by their attractive price/performance ratio and incredible growth in speed. To derive an efficient mapping onto this type of architecture, we have reformulated dynamic-programming-based alignment algorithms as streaming algorithms in terms of computer graphics primitives. Our experimental results show that the GPU-based approach allows speedups of more than one order of magnitude with respect to optimized CPU implementations.