A Dynamic Load Balancing technique for Parallel Execution of Structured Grid Models

The distribution of computational load over different processing elements represents an important issue in parallel computing [1]. This is particularly relevant in the case of parallel execution of structured grid computational models, such as Cellular Automata (CA) [2], where the domain space is partitioned in region assigned to the parallel computing nodes. Load balancing techniques are particularly effective when structured grid computational models are exploited to simulate topologically connected physical phenomena like lava or debris flows (e.g., [3]), in which the evolution develops in a usually small sub-region of the domain. In this work, we present a dynamic load balancing technique that can provide performance improvements in structured grid model development on distributed memory architectures by adopting the MPI technology. First tests have demonstrated the usefulness of the feature in appreciably reducing execution times in comparison with not-balanced parallel versions.