Accelerating Genomic Analyses with Parallel Sliding Windows

Report
Authors:Kreuter, Ben, Department of Computer ScienceUniversity of Virginia Layer, Ryan, Department of Computer ScienceUniversity of Virginia McDaniel, Michelle, Department of Computer ScienceUniversity of Virginia Robins, Gabriel, Department of Computer ScienceUniversity of Virginia Skadron, Kevin, Department of Computer ScienceUniversity of Virginia
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.

Rights:
All rights reserved (no additional license for public reuse)
Language:
English
Source Citation:

Kreuter, Ben, Ryan Layer, Michelle McDaniel, Gabriel Robins, and Kevin Skadron. "Accelerating Genomic Analyses with Parallel Sliding Windows." University of Virginia Dept. of Computer Science Tech Report (2010).

Publisher:
University of Virginia, Department of Computer Science
Published Date:
2010