Investigation on Accelerating Dust Storm Simulation via Domain Decomposition Methods

Dust storm simulation is a data and computing intensive process, which requires high efficiency and adequate computing resources. To speed up the process, high performance computing is widely adopted. By partitioning a large study area into small subdomains according to their geographic location and executing them on different computing nodes in a parallel fashion, the computing performance can be significantly improved. However, it is still a question worthy of consideration that how to allocate these subdomain processes into computing nodes without introducing imbalanced task loads and unnecessary communications among computing nodes. Here we propose a domain decomposition and allocation framework that can carefully leverage the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire system. The framework is tested in the NMM (Nonhydrostatic Mesoscale Model)-dust model, where a 72-hour processes of the dust load are simulated. Performance result using the proposed scheduling method is compared with the one using default scheduling methods of MPI. Results demonstrate that the system improves the performance of simulation by 20% up to 80%.