Parallel mapping approaches for GNUMAP

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Mapping short next-generation reads to reference genomes is an important element in SNP calling and expression studies. A major limitation to large-scale whole-genome mapping is the large memory requirements for the algorithm and the long run-time necessary for accurate studies. Several parallel implementations have been performed to distribute memory on different processors and to equally share the processing requirements. These approaches are compared with respect to their memory footprint, load balancing, and accuracy. When using MPI with multi-threading, linear speedup can be achieved for up to 256 processors.

Original languageEnglish (US)
Title of host publication2011 IEEE International Symposium on Parallel and Distributed Processing, Workshops and Phd Forum, IPDPSW 2011
Pages435-443
Number of pages9
DOIs
StatePublished - 2011
Externally publishedYes
Event25th IEEE International Parallel and Distributed Processing Symposium, Workshops and Phd Forum, IPDPSW 2011 - Anchorage, AK, United States
Duration: May 16 2011May 20 2011

Publication series

NameIEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum

Other

Other25th IEEE International Parallel and Distributed Processing Symposium, Workshops and Phd Forum, IPDPSW 2011
Country/TerritoryUnited States
CityAnchorage, AK
Period5/16/115/20/11

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Software
  • Theoretical Computer Science

Keywords

  • Biology computing
  • Next-generation sequencing
  • Parallel computing
  • Sequence mappers
  • Short-read mapping

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