Inverse Space-Filling Curve Partitioning of a Global Ocean Model

In this paper, we describe how inverse space-filling curve partitioning is used to increase the simulation rate of a global ocean model. Space-filling curve partitioning allows for the elimination of load imbalance in the computational grid due to land points. Improved load balance combined with code modifications within the conjugate gradient solver significantly increase the simulation rate of the parallel ocean program at high resolution. The simulation rate for a high resolution model nearly doubled from 4.0 to 7.9 simulated years per day on 28,972 IBM Blue Gene/L processors. We also demonstrate that our techniques increase the simulation rate on 7545 Cray XT3 processors from 6.3 to 8.1 simulated years per day. Our results demonstrate how minor code modifications can have significant impact on resulting performance for very large processor counts.