Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
Solving problems on concurrent processors. Vol. 1: General techniques and regular problems
A general concurrent algorithm for plasma particle-in-cell simulation codes
Journal of Computational Physics
Dynamic load balancing for a 2D concurrent plasma PIC code
Journal of Computational Physics
Object-oriented parallel computation for plasma simulation
Communications of the ACM - Special issue on object-oriented experiences and future trends
Particle-in-cell simulation codes in High Performance Fortran
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Parallel PIC plasma simulation through particle decomposition techniques
Parallel Computing
Plasma Physics Via Computer
High Performance Fortran: Language Specification (PART II)
ACM SIGPLAN Fortran Forum - Special issue: high performance Fortran language specification, part 2
Workload decomposition strategies for shared memory parallel systems with OpenMP
Scientific Programming
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A performance-prediction model is presented, which describes different hierarchical workload decomposition strategies for particle in cell (PIC) codes on Clusters of Symmetric MultiProcessors. The devised workload decomposition is hierarchically structured: a higher-level decomposition among the computational nodes, and a lower-level one among the processors of each computational node. Several decomposition strategies are evaluated by means of the prediction model, with respect to the memory occupancy, the parallelization efficiency and the required programming effort. Such strategies have been implemented by integrating the high-level languages High Performance Fortran (at the inter-node stage) and OpenMP (at the intra-node one). The details of these implementations are presented, and the experimental values of parallelization efficiency are compared with the predicted results.