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- W3025648538 abstract "Cellular Automata (CA) are parallel models well-suited for studying complex systems that are based on local rules of evolution. Notable examples of application are found in fluid-dynamics, crowd simulation, flow-simulation and many more. Nevertheless, CA can be fruitfully exploited as a support in numerical approaches, such as finite element and finite volume methods. Though easily parallelizable by domain partitioning among the nodes of a parallel system, the performance and scalability of cellular automata executed on parallel/distributed machines are limited due to the need of synchronizing nodes at each computational step. With the aim of reducing the synchronization burden, we here present a preliminary study on techniques stemmed from the Discrete-Event Simulation field for the optimization of CA on distributed memory architectures. Preliminary results, executed in a distributed memory environment, have shown the usefulness of the considered approach in reducing execution times and therefore in improving the speed up of the parallel execution of the test case." @default.
- W3025648538 created "2020-05-21" @default.
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- W3025648538 date "2020-03-01" @default.
- W3025648538 modified "2023-09-23" @default.
- W3025648538 title "Optimizing Cellular Automata Execution by Distributed Discrete Event Simulation Techniques" @default.
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- W3025648538 doi "https://doi.org/10.1109/pdp50117.2020.00056" @default.
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