Title :
Parallel Approaches for SWAMP Sequence Alignment
Author :
Steinfadt, Shannon ; Schaffer, Kevin
Author_Institution :
Dept. of Comput. Sci., Kent State Univ., Kent, OH, USA
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;
Conference_Titel :
Bioinformatics, 2009. OCCBIO '09. Ohio Collaborative Conference on
Conference_Location :
Cleveland, OH
Print_ISBN :
978-0-7695-3685-9
DOI :
10.1109/OCCBIO.2009.12