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Accelerating Genomic Analyses With Parallel Sliding Windows

Kreuter, Ben; Layer, Ryan; McDaniel, Michelle; Robins, Gabriel; Skadron, Kevin
Format
Report
Author
Kreuter, Ben
Layer, Ryan
McDaniel, Michelle
Robins, Gabriel
Skadron, Kevin
Abstract
In recent years biology has become an information science, where an avalanche of newly sequenced genomic data has overwhelmed our existing analysis and mining tools. This paper addresses this challenge by developing a systematic way of speeding up a broad class of bioinformatics algorithms using commodity graphics pro- cessing hardware. Using the example problem of analyzing DNA structural variations, we demonstrate how such computations can be significantly accelerated in various parallel architectures, yield- ing over two orders of magnitude speedups at low cost and with rel- atively modest programming effort. Our implementation of a slid- ing window -based technique on the GPU and Cell architectures seems promising in its generality and extensibility to other prob- lems and domains.
Language
English
Date Received
2012-10-29
Published
University of Virginia, Department of Computer Science, 2010
Published Date
2010
Collection
Libra Open Repository
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