Engineering topics
Tuminaro, Raymond S.
Publications and source records attributed to Tuminaro, Raymond S..
A Scalable Solver Algorithm to Enable Sea-Level Rise Prediction using Agile Components.
Abstract not provided.
A Quasi-Algebraic Multigrid Approach to PDE systems with Variable Degrees-of-Freedom Per Node.
Abstract not provided.
Monolithic multigrid methods for two-dimensional resistive magnetohydrodynamics
Magnetohydrodynamic (MHD) representations are used to model a wide range of plasma physics applications and are characterized by a nonlinear system of partial differential equations that strongly couples a charged fluid with the evolution of electromagnetic fields. The resulting linear systems that arise from discretization and linearization of the nonlinear problem are generally difficult to solve. In this paper, we investigate multigrid preconditioners for this system. We consider two well-known multigrid relaxation methods for incompressible fluid dynamics: Braess--Sarazin relaxation and Vanka relaxation. We first extend these to the context of steady-state one-fluid viscoresistive MHD. Then we compare the two relaxation procedures within a multigrid-preconditioned GMRES method employed within Newton's method. To isolate the effects of the different relaxation methods, we use structured grids, inf-sup stable finite elements, and geometric interpolation. Furthermore, we present convergence and timing results for a two-dimensional, steady-state test problem.
Monolithic Multigrid for a B-field Incompressible Resistive Magnetohydrodynamics Model.
Abstract not provided.
Component-based application code development, part 2:
Abstract not provided.
Component-Based Application Code Development Part 2: Demonstration on a Land-Ice Model and Proposed Extension to Other Climate Components.
Abstract not provided.
Albany: Integrating Algorithmic Components to Build Advanced Applications.
Abstract not provided.
Albany/FELIX: A Robust & Scalable Trilinos-Based Finite-Element Ice Flow Dycore Built for Advanced Architectures & Analysis.
Abstract not provided.
Algebraic Multigrid Preconditioners for Q2-Q1 discretizations of the incompressi ble Navier-Stokes equations.
Abstract not provided.
Linear solver strategy for coupled and implicit discontinuous Galerkin method to model miscible displacement with adverse mobility ratio.
Abstract not provided.
Progress on the PISCEES FELIX Ice Sheet Dynamical Cores.
Abstract not provided.
On the scalability of the Albany/FELIX first-order Stokes approximation ice sheet solver for large-scale simulations of the Greenland and Antarctic ice sheets.
Abstract not provided.
On the Development & Performance of a First Order Stokes Finite Element Ice Sheet Dycore Built Using Trilinos Software Components.
Abstract not provided.
A Hybrid Operator Dependent MG / AMG Approach: Application to Ice Sheet Modeling.
Abstract not provided.
On the scalability of the Albany/FELIX first-order Stokes approximation ice sheet solver for large-scale simulations of the Greenland and Antarctic ice sheets
We examine the scalability of the recently developed Albany/FELIX finite-element based code for the first-order Stokes momentum balance equations for ice flow. We focus our analysis on the performance of two possible preconditioners for the iterative solution of the sparse linear systems that arise from the discretization of the governing equations: (1) a preconditioner based on the incomplete LU (ILU) factorization, and (2) a recently-developed algebraic multigrid (AMG) preconditioner, constructed using the idea of semi-coarsening. A strong scalability study on a realistic, high resolution Greenland ice sheet problem reveals that, for a given number of processor cores, the AMG preconditioner results in faster linear solve times but the ILU preconditioner exhibits better scalability. A weak scalability study is performed on a realistic, moderate resolution Antarctic ice sheet problem, a substantial fraction of which contains floating ice shelves, making it fundamentally different from the Greenland ice sheet problem. Here, we show that as the problem size increases, the performance of the ILU preconditioner deteriorates whereas the AMG preconditioner maintains scalability. This is because the linear systems are extremely ill-conditioned in the presence of floating ice shelves, and the ill-conditioning has a greater negative effect on the ILU preconditioner than on the AMG preconditioner.
On the scalability of the Albany/FELIX first-order Stokes approximation ice sheet solver for large-scale simulations of the Greenland and Antarctic ice sheets.
Abstract not provided.