Improving the Scalability of the Basin Scale HWRF Model
We present our solution towards making the basin scale HWRF worthy of consideration for operational use by reducing its execution time. Our solution takes advantage of the fact that moving nests can be integrated independent of one another. Hence, instead of sequentially integrating each pair of storm-following nests, they are integrated in parallel. While using different sets of workers for each nest is not trivial within the HWRF framework, we minimized the amount of changes needed by devising a solution that takes advantage of the fact that modern compute nodes contain multiple compute cores. Our modified code uses a subset of cores from each machine to operate on each of the storm-following pairs of nests.
Our results show that with our approach, computation time remains constant regardless of the number of storms, rather than linearly increasing as more storms are simulated. Furthermore, we confirmed that forecasts made using our parallel integration approach are statistically equivalent to those made using sequential integration. The system is currently running as part of the operational demonstration for the 2014 hurricane season. We conclude that the performance and robustness of this approach is a significant milestone towards making the basin scale HWRF meet the operational time constraints.