Effective Use of Multicore Clusters in Parallel Cellular Automata

Abstract

Cellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. We start from a template designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the template is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this work we discuss and evaluate strategies that will be important in optimizing prototype to run on multicore cluster. The underlying idea in our proposal is the establishment of a relation among parallel processes based on the communication topology that arises in the implementation of task division functions. We propose that this relation can efficiently map on the multicore cluster topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.