Toward High Utilization of Heterogeneous Computing Resources in SNP Detection

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As the amount of re-sequencing genome data grows, minimizing the execution time of an analysis is required. For this purpose, recent computing systems have been adopting both high-performance coprocessors and host processors. However, there are few applications that efficiently utilize these heterogeneous computing resources. This problem equally refers to the work of single nucleotide polymorphism (SNP) detection, which is one of the bottlenecks in genome data processing. In this paper, we propose a method for speeding up an SNP detection by enhancing the utilization of heterogeneous computing resources often used in recent high-performance computing systems. Through the measurement of workload in the detection procedure, we divide the SNP detection into several task groups suitable for each computing resource. These task groups are scheduled using a window overlapping method. As a result, we improved upon the speedup achieved by previous open source applications by a magnitude of 10.
Publisher
ELECTRONICS TELECOMMUNICATIONS RESEARCH INST
Issue Date
2015-04
Language
English
Article Type
Article
Keywords

GENOME; MAPREDUCE; ALIGNMENT; SEQUENCE; FORMAT

Citation

ETRI JOURNAL, v.37, no.2, pp.212 - 221

ISSN
1225-6463
DOI
10.4218/etrij.15.2314.0144
URI
http://hdl.handle.net/10203/208911
Appears in Collection
EE-Journal Papers(저널논문)
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