Optimizing data intensive GPGPU computations for DNA sequence alignment

Trapnell, C., Schatz, M. C. (2009) Optimizing data intensive GPGPU computations for DNA sequence alignment. Parallel Computing, 35 (8-9). pp. 429-440. ISSN 01678191 (ISSN)

URL: http://www.ncbi.nlm.nih.gov/pubmed/20161021
DOI: 10.1016/j.parco.2009.05.002

Abstract

MUMmerGPU uses highly-parallel commodity graphics processing units (GPU) to accelerate the data-intensive computation of aligning next generation DNA sequence data to a reference sequence for use in diverse applications such as disease genotyping and personal genomics. MUMmerGPU 2.0 features a new stackless depth-first-search print kernel and is 13× faster than the serial CPU version of the alignment code and nearly 4× faster in total computation time than MUMmerGPU 1.0. We exhaustively examined 128 GPU data layout configurations to improve register footprint and running time and conclude higher occupancy has greater impact than reduced latency. MUMmerGPU is available open-source at http://www.mummergpu.sourceforge.net. © 2009 Elsevier B.V. All rights reserved.

Item Type: Paper
Uncontrolled Keywords: CUDA GPGPU Short read mapping Suffix trees Data intensive Data layouts Data-intensive computation Depth first search Diverse applications DNA sequence data Genomics Genotyping Graphics Processing Unit Open-source Running time Total computation time Alignment Computer graphics equipment DNA Genes Nucleic acids Program processors
Subjects: bioinformatics > genomics and proteomics > analysis and processing
bioinformatics > genomics and proteomics > alignment > sequence alignment
bioinformatics > genomics and proteomics > annotation > sequence annotation
bioinformatics > genomics and proteomics > analysis and processing > Sequence Data Processing
bioinformatics > genomics and proteomics > Mapping and Rendering > Sequence Rendering
bioinformatics > computational biology
bioinformatics > genomics and proteomics > computers > computer software
Investigative techniques and equipment > interface method
CSHL Authors:
Communities: CSHL labs > Schatz lab
Depositing User: CSHL Librarian
Date: 2009
Date Deposited: 16 Mar 2012 14:39
Last Modified: 15 Mar 2013 19:12
PMCID: PMC2749273
Related URLs:
URI: http://repository.cshl.edu/id/eprint/25362

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