DocumentCode :
2721358
Title :
Parallel sorting algorithms for optimizing particle simulations
Author :
Hofmann, Michael ; Runger, Gudula ; Gibbon, Paul ; Speck, Robert
Author_Institution :
Dept. of Comput. Sci., Chemnitz Univ. of Technol., Chemnitz, Germany
fYear :
2010
fDate :
20-24 Sept. 2010
Firstpage :
1
Lastpage :
8
Abstract :
Real world particle simulation codes have to handle a huge number of particles and their interactions. Thus, parallel implementations are required to get suitable production codes. Parallel sorting is often used to organize the set of particles or to redistribute data for locality and load balancing concerns. In this article, the use and design of parallel sorting algorithms for parallel particle simulation codes are discussed. As a typical example, the particle simulation code PEPC is considered and a specific parallel sorting algorithm for this application is presented. The resulting parallel simulation code was implemented on an IBM Blue Gene/P system and corresponding performance results are shown.
Keywords :
optimisation; parallel processing; physics computing; resource allocation; sorting; IBM Blue Gene; P system; PEPC; load balancing; parallel implementations; parallel sorting; parallel sorting algorithms; particle simulations optimization; Arrays; Computational modeling; Data models; Load modeling; Memory management; Partitioning algorithms; Sorting; data redistribution; load balancing; parallel sorting; particle simulations; performance optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS), 2010 IEEE International Conference on
Conference_Location :
Heraklion, Crete
Print_ISBN :
978-1-4244-8395-2
Electronic_ISBN :
978-1-4244-8397-6
Type :
conf
DOI :
10.1109/CLUSTERWKSP.2010.5613105
Filename :
5613105
Link To Document :
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