Dynamic Remapping of Parallel Computations with Varying Resource Demands
IEEE Transactions on Computers
Computer simulation using particles
Computer simulation using particles
Characterizing the parallel performance of a large-scale, particle-in-cell plasma simulation code
Concurrency: Practice and Experience
Parallel remapping algorithms for adaptive problems
FRONTIERS '95 Proceedings of the Fifth Symposium on the Frontiers of Massively Parallel Computation (Frontiers'95)
Workload decomposition strategies for shared memory parallel systems with OpenMP
Scientific Programming
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Particle-in-cell (PIC) plasma simulation codes require two data arrays---particle array and field array---for storing the lists of particles and electromagnetic fields, respectively. In every iteration the two are updated based on the values of each other. The interaction between these two arrays is dynamic due to the movement of particles. Efficient parallelization of PIC requires the two data arrays to be load balanced and the amount of communication generated due to the interaction between them to be minimized. This requires dynamic distribution and alignment of the two arrays. In this paper we present fast and efficient methods for achieving this task at runtime. The implementation and performance of a relativistic electromagnetic PIC plasma simulation code on the CM-5 are described.