Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers
Recongurable computing technology has progressed to a stage where it is now possible to achieve orders of magnitude performance and power eciency gains over conventional computer architectures for a subset of high performance computing applications. In this thesis, we investigate the potential of re...
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ndltd-netd.ac.za-oai-union.ndltd.org-uctcs-oai-techreports.cs.uct.ac.za-5712014-02-08T03:46:11Z Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers McMahon, Peter D.1 PROGRAMMING TECHNIQUES Recongurable computing technology has progressed to a stage where it is now possible to achieve orders of magnitude performance and power eciency gains over conventional computer architectures for a subset of high performance computing applications. In this thesis, we investigate the potential of recongurable computers to accelerate genomic sequence alignment specically for genome sequencing applications. We present a highly optimized implementation of a parallel sequence alignment algorithm for the Berkeley Emulation Engine (BEE2) recongurable computer, allowing a single BEE2 to align simultaneously hundreds of sequences. For each recongurable processor (FPGA), we demonstrate a 61X speedup versus a state-of-the-art implementation on a modern conventional CPU core, and a 56X improvement in performance-per-Watt. We also show that our implementation is highly scalable and we provide performance results from a cluster implementation using 32 FPGAs. We conclude that reconfigurable computers provide an excellent platform on which to run sequence alignment, and that clusters of recongurable computers will be able to cope far more easily with the vast quantities of data produced by new ultra-high-throughput sequencers. 2009-01-01 Electronic Thesis or Dissertation http://pubs.cs.uct.ac.za/archive/00000571/ pdf http://pubs.cs.uct.ac.za/archive/00000571/01/McMahon_-_Sequence_Alignment_Thesis_-_Final_Version_20-Dec-2008.pdf |
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D.1 PROGRAMMING TECHNIQUES |
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D.1 PROGRAMMING TECHNIQUES McMahon, Peter Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers |
description |
Recongurable computing technology has progressed to a stage where it is now possible to achieve orders of magnitude performance and power eciency gains over conventional computer architectures for a subset of high performance computing applications. In this thesis, we investigate the potential of recongurable computers to accelerate genomic sequence alignment specically for genome sequencing applications.
We present a highly optimized implementation of a parallel sequence alignment algorithm for the Berkeley Emulation Engine (BEE2) recongurable computer, allowing a single BEE2 to align simultaneously hundreds of sequences. For each recongurable processor (FPGA), we demonstrate a 61X speedup versus a state-of-the-art implementation on a modern conventional CPU core, and a 56X improvement in performance-per-Watt. We also show that our implementation is highly scalable and we provide performance results from a cluster implementation using 32 FPGAs.
We conclude that reconfigurable computers provide an excellent platform on which to run sequence alignment, and that clusters of recongurable computers will be able to cope far more easily with the vast quantities of data produced by new ultra-high-throughput sequencers.
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author |
McMahon, Peter |
author_facet |
McMahon, Peter |
author_sort |
McMahon, Peter |
title |
Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers |
title_short |
Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers |
title_full |
Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers |
title_fullStr |
Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers |
title_full_unstemmed |
Accelerating Genomic Sequence Alignment using High Performance Reconfigurable Computers |
title_sort |
accelerating genomic sequence alignment using high performance reconfigurable computers |
publishDate |
2009 |
url |
http://pubs.cs.uct.ac.za/archive/00000571/ |
work_keys_str_mv |
AT mcmahonpeter acceleratinggenomicsequencealignmentusinghighperformancereconfigurablecomputers |
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1716633789237559296 |