Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.
Malakar, P., George, T., Kumar, S., Mittal, R., Natarajan, V., Sabharwal, Y., … Vadhiyar, S. S. (2013). A divide and conquer strategy for scaling weather simulations with multiple regions of interest. In Scientific Programming (Vol. 21, pp. 93–107). Hindawi Limited. https://doi.org/10.3233/SPR-130367