Abstract
Partitioning computational load over different processing elements is a crucial issue in parallel computing. This is particularly relevant in the case of parallel execution of structured grid computational models, such as Cellular Automata (CA), where the domain space is partitioned in regions assigned to the parallel computing nodes. In this work, we present a dynamic load balancing technique that provides for performance improvements in structured grid model execution on distributed memory architectures. First tests implemented using the MPI technology have shown the goodness of the proposed technique in sensibly reducing execution times with respect to not-balanced parallel versions.
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Notes
- 1.
For the sake of simplicity, in this first implementation of the LB procedure the exchange of columns is not toroidal, i.e. it is not possible to exchange columns between the rightmost node and the leftmost node.
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Authors thank BS student Rodolfo Calabrò from University of Calabria for helping in code implementation and testing phases.
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Giordano, A., De Rango, A., Rongo, R., D’Ambrosio, D., Spataro, W. (2020). A Dynamic Load Balancing Technique for Parallel Execution of Structured Grid Models. In: Sergeyev, Y., Kvasov, D. (eds) Numerical Computations: Theory and Algorithms. NUMTA 2019. Lecture Notes in Computer Science(), vol 11973. Springer, Cham. https://doi.org/10.1007/978-3-030-39081-5_25
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