A Comparative Analysis of Load Balancing Algorithms Applied to a Weather Forecast Model

Among the many reasons for load imbalance in weather forecasting models, the dynamic imbalance caused by lo-calized variations on the state of the atmosphere is the hard-est one to handle. As an example, active thunderstorms may substantially increase load at a certain timestep with re-spect to previous timesteps in an unpredictable manner – after all, tracking storms is one of the reasons for running a weather forecasting model. In this paper, we present a com-parative analysis of different load balancing algorithms to deal with this kind of load imbalance. We analyze the im-pact of these strategies on computation and communication and the effects caused by the frequency at which the load balancer is invoked on execution time. This is done with-out any code modification, employing the concept of proces-sor virtualization, which basically means that the domain is over-decomposed and the unit of rebalance is a sub-domain. With this approach, we were able to reduce the execution time of a full, real-world weather model. 1