Title :
Parallel Mapping Approaches for GNUMAP
Author :
Clement, Nathan L. ; Clement, Mark J. ; Snell, Quinn ; Johnson, W. Evan
Author_Institution :
Dept. of Comput. Sci., Univ. of Texas at Austin, Austin, TX, USA
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.
Keywords :
biology computing; genomics; message passing; multi-threading; resource allocation; storage management; GNUMAP; MPI; SNP calling; expression study; large-scale whole-genome mapping; linear speedup; load balancing; memory distribution; memory footprint; memory requirement; multithreading; next-generation sequencing; parallel mapping approach; processing requirement sharing; Bioinformatics; Genomics; Heuristic algorithms; Instruction sets; Memory management; Probabilistic logic; Random access memory;
Conference_Titel :
Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-425-1
Electronic_ISBN :
1530-2075
DOI :
10.1109/IPDPS.2011.184