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Parallel Approaches for SWAMP Sequence Alignment

Shannon Steinfadt, Kevin Schaffer
Dept. of Comput. Sci., Kent State Univ., Kent, OH, USA
2009 Ohio Collaborative Conference on Bioinformatics, OCCBIO ’09, 2009

@conference{steinfadt2009parallel,

   title={Parallel approaches for swamp sequence alignment},

   author={Steinfadt, S. and Schaffer, K.},

   booktitle={2009 Ohio Collaborative Conference on Bioinformatics},

   pages={87–92},

   year={2009},

   organization={IEEE}

}

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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.
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