Dynamic Load Balancing of SAMR Applications on Distributed Systems

Dynamic load balancing (DLB) for parallel systems has been studied extensively; however, DLB for distributed systems is relatively new. To efficiently utilize computing resources provided by distributed systems, an underlying DLB scheme must address both heterogeneous and dynamic features of distributed systems. In this paper, we propose a DLB scheme for Structured Adaptive Mesh Refinement (SAMR) applications on distributed systems. While the proposed scheme can take into consideration (1) the heterogeneity of processors and (2) the heterogeneity and dynamic load of the networks, the focus of this paper is on the latter. The load-balancing processes are divided into two phases: global load balancing and local load balancing. We also provide a heuristic method to evaluate the computational gain and redistribution cost for global redistribution. Experiments show that by using our distributed DLB scheme, the execution time can be reduced by 9-46% as compared to using parallel DLB scheme which does not consider the heterogeneous and dynamic features of distributed systems.