Towards Understanding Optimal Load-Balancing of Heterogeneous Short-Range Molecular Dynamics

For heterogeneous dynamic short-range molecular dynamics simulations it is critical to employ suitable load-balancing methods to minimize the time to solution. However, designing and parametrizing the optimal load-balancing method is a complex task, depending on detailed properties of the simulation scenario.The main challenge in balancing the load of molecular dynamics simulations is the extreme difference in load density for scenarios with heterogeneous particle density, which can easily reach 4-6 orders of magnitude. Therefore, heterogeneity is deemed to be a relevant property and a suitable metric to reliably quantifying heterogeneity is formulated. This metric, which is based on binning particles and evaluating statistical moments, is then applied to example scenarios and correlated to the performance of five load balancing methodologies. Furthermore, how rapidly the load varies over time will determine how long the benefits of a specific partitioning are expected to last. We deem this to be another relevant property, the dynamics, and introduce corresponding metrics. The results indicate that these metric are useful to differentiate between scenarios and facilitate reasoning over the complex relationship between particle simulation scenarios and optimal load balancing methods. This work is a first step towards understanding this relationship, while introducing key concepts we regard as a crucial for this understanding.