Parallelization of the canal subsystem of the Everglades Landscape Model

Environmental simulations are computationally very demanding. South Florida Water Management District has implemented the Everglades Landscape Model (ELM) to simulate the ecosystem in South Florida. The current implementation parallelizes all of the model except the canal system. This thesis describes the parallelization of the canal system. We study the canal system and its interaction with the rest of the ELM, and created three distinct parallel implementations. Two of the methods, one-do-all and all-do-all, provide parallelism via task replication while the third method, task-parallel, decomposes the canal system into tasks and uses a locality-based heuristic algorithm to schedule the tasks. We analyze the performance of three methods and discuss future directions for parallelization of the ELM and other environmental models.