DistDLB: Improving cosmology SAMR simulations on distributed computing systems through hierarchical load balancing

Cosmology SAMR simulations have played a prominent role in the field of astrophysics. The emerging distributed computing systems provide an economic alternative to the traditional parallel machines, and enable scientists to conduct cosmological simulations that require vast computing power. An important issue of conducting distributed cosmological simulations is about performance and efficiency. In this paper, we present a dynamic load balancing scheme called DistDLB that is designed to improve the performance of distributed cosmology simulations. Distributed systems, e.g. the Computation Grid, usually consist of heterogeneous resources connected with shared networks. By considering these features of distributed systems and unique characteristics of cosmology SAMR simulations, DistDLB focuses on reducing the redistribution cost through a hierarchical load balancing approach and a run-time decision making mechanism. Heuristic methods have been proposed to adaptively adjust load balancing strategies based on the observation of the current system and application state. Our experiments with real-world cosmology simulations on production systems indicate that the proposed DistDLB scheme can effectively improve the performance of cosmology simulations by 2.56–79.14% as compared to the scheme that does not consider the heterogeneous and dynamic features of distributed systems.