A Feedback Based Load Balance Algorithm for Physics Routines in Nwp

In recent years, Numerical Weather Prediction (NWP) has made increasing use of parallel machines with large numbers of processors. The physics portion of NWP is particularly amenable to large scale parallelism as, in most cases, each grid column can be independently computed. However, grid columns have varying amounts of work associated with them, so, a simple partition of grid columns can leave some processors with much less work than others. As the number of processors grows, this eeect becomes increasingly important. Such imbalance can be time invariant (such as computation based on orographic features), vary predictably in time (such as short wave radiation), or vary unpredictably in time (such as convection and precipitation). This paper presents a load balance algorithm which is particularly aimed at the last of these cases. The feedback mechanism uses the time taken and number of grid columns for each processor at the previous time-step, to provide an improved partition for the current time-step. Simulation results are presented both for synthetic workloads, and using data from ECMWF's IFS model.