G. Mahinthakumar

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The hybrid MPI-OpenMP model is a natural parallel programming paradigm for emerging parallel architectures that are based on symmetric multiprocessor (SMP) clusters. This paper presents a hybrid implementation adapted for an implicit finite-element code developed for groundwater transport simulations. The original code was parallel-ized for distributed(More)
We describe the implementation and analyze the performance of a parallel finite–element multi-component groundwater transport code on a variety of parallel architectures. The code exhibits characteristics that are typical to many simulation codes such as explicit communication, global reduction operations, sparse matrix operations, and parallel I/O. The(More)
In this paper we present parallel solvers for large linear systems arising from the finite–element discretization of three–dimensional groundwater flow problems. We have tested our parallel implementations on the Intel Paragon XP/S 150 supercomputer using up to 1024 parallel processors. Our solvers are based on multigrid and Krylov subspace methods. Our(More)
The computation of Contaminant Source Characterization (CSC) is a critical research issue in Water Distribution System (WDS) management. We use a simulation framework to identify optimized locations of sensors that lead to fast detection of contamination sources [1, 2]. The optimization engine is based on a Genetic Algorithm (GA) that interprets trial(More)
This study investigates the use of ozone for soil remediation. Batch experiments, in which ozone-containing gas was continuously recycled through a soil bed, were conducted to quantify the rate of ozone self-decomposition and the rates of ozone interaction with soil organic and inorganic matter. Column experiments were conducted to measure ozone(More)
In this paper we present parallel solvers for large linear systems arising from the finite–element discretization of three–dimensional groundwater flow problems. We have tested our parallel implementations on the Intel Paragon XP/S 150 supercomputer using up to 1024 parallel processors. Our solvers are based on multigrid and Krylov subspace methods. Our(More)
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