Accelerating Groundwater Flow Simulation in MODFLOW Using JASMIN‐Based Parallel Computing

To accelerate the groundwater flow simulation process, this paper reports our work on developing an efficient parallel simulator through rebuilding the well-known software MODFLOW on JASMIN (J Adaptive Structured Meshes applications Infrastructure). The rebuilding process is achieved by designing patch-based data structure and parallel algorithms as well as adding slight modifications to the compute flow and subroutines in MODFLOW. Both the memory requirements and computing efforts are distributed among all processors; and to reduce communication cost, data transfers are batched and conveniently handled by adding ghost nodes to each patch. To further improve performance, constant-head/inactive cells are tagged and neglected during the linear solving process and an efficient load balancing strategy is presented. The accuracy and efficiency are demonstrated through modeling three scenarios: The first application is a field flow problem located at Yanming Lake in China to help design reasonable quantity of groundwater exploitation. Desirable numerical accuracy and significant performance enhancement are obtained. Typically, the tagged program with load balancing strategy running on 40 cores is six times faster than the fastest MICCG-based MODFLOW program. The second test is simulating flow in a highly heterogeneous aquifer. The AMG-based JASMIN program running on 40 cores is nine times faster than the GMG-based MODFLOW program. The third test is a simplified transient flow problem with the order of tens of millions of cells to examine the scalability. Compared to 32 cores, parallel efficiency of 77 and 68% are obtained on 512 and 1024 cores, respectively, which indicates impressive scalability.

[1]  Xiaolin Cao,et al.  Efficient Coupling of Parallel Visualization and Simulations on Tens of Thousands of Cores , 2011, 2011 International Conference on Virtual Reality and Visualization.

[2]  D. Dudley Williams,et al.  Factors controlling riffle‐scale hyporheic exchange flows and their seasonal changes in a gaining stream: A three‐dimensional groundwater flow model , 2003 .

[3]  Hans De Sterck,et al.  Reducing Complexity in Parallel Algebraic Multigrid Preconditioners , 2004, SIAM J. Matrix Anal. Appl..

[4]  Xiaolin Cao,et al.  JASMIN: a parallel software infrastructure for scientific computing , 2010, Frontiers of Computer Science in China.

[5]  Glenn E. Hammond,et al.  Field‐scale model for the natural attenuation of uranium at the Hanford 300 Area using high‐performance computing , 2010 .

[6]  Erik Elmroth,et al.  High Performance Computations for Large Scale Simulations of Subsurface Multiphase Fluid and Heat Flow , 2004, The Journal of Supercomputing.

[7]  Xiaolin Cao,et al.  Parallel implementation of fast multipole method based on JASMIN , 2011, Science China Information Sciences.

[8]  Erik Elmroth,et al.  Parallel Computing Techniques for Large-Scale Reservoir Simulation of Multi- Component and Multiphase Fluid Flow , 2001 .

[9]  Xiaohui Ji,et al.  CUDA-based solver for large-scale groundwater flow simulation , 2011, Engineering with Computers.

[10]  Junqi Huang,et al.  An assembly model for simulation of large-scale ground water flow and transport. , 2008, Ground water.

[11]  Arlen W. Harbaugh,et al.  A modular three-dimensional finite-difference ground-water flow model , 1984 .

[12]  S. Wondzell,et al.  Geomorphic controls on hyporheic exchange flow in mountain streams , 2003 .

[13]  Mary C. Hill,et al.  PRECONDITIONED CONJUGATE-GRADIENT 2 (PCG2), a computer program for solving ground-water flow equations , 1990 .

[14]  Stanley A. Leake,et al.  A new ghost-node method for linking different models and initial investigations of heterogeneity and nonmatching grids , 2007 .

[15]  Yu-Shu Wu,et al.  An efficient parallel-computing method for modeling nonisothermal multiphase flow and multicomponent transport in porous and fractured media , 2002 .

[16]  Xiao-Chuan Cai,et al.  Parallel numerical solution of groundwater flow problems , 2006 .

[17]  S. W. Mehl,et al.  MODFLOW-2000, the U. S. Geological Survey modular ground-water model; user guide to the Link-AMG (LMG) package for solving matrix equations using an algebraic multigrid solver , 2001 .

[18]  Guomin Li,et al.  A Parallel PCG Solver for MODFLOW , 2009, Ground water.

[19]  Jin P. Gwoa,et al.  HBGC 123 D : a high-performance computer model of coupled hydrogeological and biogeochemical processes q , 2001 .

[20]  Jan Vanderborght,et al.  PARSWMS: A Parallelized Model for Simulating Three‐Dimensional Water Flow and Solute Transport in Variably Saturated Soils , 2007 .

[21]  M. Hill,et al.  Development and evaluation of a local grid refinement method for block-centered finite-difference groundwater models using shared nodes , 2002 .