Mark S. Dortch

Comparison of HPC Methods for Long-Term Contaminant Modeling

Model simulations on the order of decades are required to fully evaluate the effects of system alterations on the estuarine/coastal environment since these environments and their components (e.g., bottom sediments, sea grass, nutrient stores, etc.) can have long response times and process memories. High performance computing (HPC) is required to make such simulations feasible. Modern HPC methods can decrease computation time by orders of magnitude, thus, making such long-term calculations feasible and practical. An investigation was conducted to evaluate the performance of various methods and machines for executing a three-dimensional contaminant transport/fate model for surface water where the Hudson River Estuary was used for the test case. Domain decomposition was used with two grid-partitioning methods, METIS and Hilbert Space filling Curve Technique (HSFT). The Message Passing Interface (MPI) was incorporated into model source code to provide the capability to execute multiple sub-domains on different numbers of processor elements (PEs). The code was written to be portable among various machines with varying numbers of PEs. Tests were conducted for the Hudson River contaminant model example for varying levels of grid resolution for both grid-partitioning methods on three machines (Cray T3E, SGI Origin 2000, and IBM SP) with varying numbers of processors (from 1 up to 64 PEs) to evaluate both parallel and scaled speedup. The conclusions of these tests are presented. The methodology was successfully used to conduct the Chesapeake Bay Tributary Refinement Model Study, where 20-year simulations were required on a relatively dense grid, thus, making it feasible to investigate many management scenarios in a timely and practical manner.