Current Bioinformatics

Yi-Ping Phoebe Chen
Department of Computer Science and Information Technology
La Trobe University
Melbourne
Australia

Back

Advanced Acceleration Technologies for Biological Sequence Analyses

Author(s): Xiandong Meng, Yanqing Ji, Hai Jiang.

Abstract:

There has been substantial evidence that functional and structural analyses of genes and proteins can help develop new drugs, diagnose medical conditions and find cures for diseases. However, these biological sequence analyses require large-scale computational power due to the exponential growth of genomic information. During the past two decades considerable efforts have been expended in trying to accelerate the biological sequence database search process which is the fundamental step for further analyses. Various software approaches including SIMD (Single Instruction Multiple Data) instruction, multithreading, message passing programming paradigm and I/O optimization have been employed to speed up the process on different computing platforms at different levels. Hardware techniques such as FPGA (Field Programmable Gate Arrays), GPU (Graphics Processing Unit), IBM CELL BE, DSP (Digital Signal Processors) and ASIC (Applications Specific Integrated Circuit) have also been widely used. This paper reviews relevant computing platforms, various software and hardware approaches as well as the performances they achieved in high throughput sequence database search. It demonstrates that parallelism can be exploited at different phases, granularity levels, types, software/ hardware levels and scopes. This would help researchers understand current development strategies and possible future trends such as aggregate heterogeneous systems in high performance biological sequence analysis.

Keywords: Smith-waterman algorithm, SIMD, FPGA, GPU, DSP, heterogeneous computing, biological sequence analysis

Order Reprints Order Eprints Rights & PermissionsPrintExport

Article Details

VOLUME: 5
ISSUE: 3
Year: 2010
Page: [176 - 194]
Pages: 19
DOI: 10.2174/157489310792006738
Price: $58