DocumentCode
2452616
Title
Parallel Approaches for SWAMP Sequence Alignment
Author
Steinfadt, Shannon ; Schaffer, Kevin
Author_Institution
Dept. of Comput. Sci., Kent State Univ., Kent, OH, USA
fYear
2009
fDate
15-17 June 2009
Firstpage
87
Lastpage
92
Abstract
This document is a summary and overview of several approaches to implement the local sequence alignment algorithms known as SWAMP and SWAMP+ on commercially available hardware. Using a Smith-Waterman style of alignment, these parallel algorithms have several innovative extensions that take advantage of the ASC associative computing model while maintaining speed, accuracy, and producing a richer set of results in an automated way that is not currently available. We consider four different hardware architectures for the realization of the ASC model. These are the ClearSpeed CSX processor, NVIDIA GPGPU graphics processors, IBM Cell Processors, and FPGAs.
Keywords
bioinformatics; parallel algorithms; ASC model realization; ClearSpeed CSX processor; FPGA; GPGPU graphics processor; IBM cell processor; NVIDIA; SWAMP sequence alignment; SWAMP+; Smith-Waterman style; associative computing; bioinformatics sequence alignment; hardware architecture; local sequence alignment algorithm; parallel algorithm; Bioinformatics; Concurrent computing; Dynamic programming; Field programmable gate arrays; Graphics; Hardware; Heuristic algorithms; Parallel algorithms; Parallel processing; Sequences; Cell Processor; FPGAs; GPGPUs; associative SIMD; parallel computing; sequence alignment;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics, 2009. OCCBIO '09. Ohio Collaborative Conference on
Conference_Location
Cleveland, OH
Print_ISBN
978-0-7695-3685-9
Type
conf
DOI
10.1109/OCCBIO.2009.12
Filename
5159168
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