
Understanding the Propagation of Silent Data Corruption in Algebraic Multigrid
04 Feb 2016  Online Presentations  Contributor(s): Jon Calhoun
Sparse linear solvers from a fundamental kernel in high performance computing (HPC). Exascale systems are expected to be more complex than systems of today being composed of thousands of...
http://nanohub.org/resources/23483

A Performance Comparison of Algebraic Multigrid Preconditioners on GPUs and MIC
04 Feb 2016  Online Presentations  Contributor(s): Karl Rupp
Algebraic multigrid (AMG) preconditioners for accelerators such as graphics processing units (GPUs) and Intel's manyintegrated core (MIC) architecture typically require a careful,...
http://nanohub.org/resources/23485

Monolithic Multigrid Methods for Coupled MultiPhysics Problems
04 Feb 2016  Online Presentations  Contributor(s): Scott Maclachlan
While blockdiagonal and approximate blockfactorization preconditioners are often considered for coupled problems, monolithic approaches can offer improved performance, particularly when the...
http://nanohub.org/resources/23487

Application of Multigrid Techniques to Magnetic and Electromagnetic Systems
04 Feb 2016  Online Presentations  Contributor(s): Benjamin Cowan
We discuss the use of multigrid techniques for several novel systems related to electromagnetics. One of these is the magnetostatic problem, in which systems can involve highly anisotropic and...
http://nanohub.org/resources/23489

Geometric Multigrid for MHD Simulations with Nedelec Finite Elements on Tetrahedral Grids
04 Feb 2016  Online Presentations  Contributor(s): Chris Hansen
The MagnetoHydroDynamic (MHD) model is used extensively to simulate macroscopic plasma dynamics in Magnetic Confinement Fusion (MCF) devices. In these simulations, the span of time scales from...
http://nanohub.org/resources/23491

Parallel Multigrid Preconditioner Based on Automatic 3D Tetradedric Meshes
04 Feb 2016  Online Presentations  Contributor(s): Frederic Vi
Multigrid methods are efficient for solving large sparse linear systems. Geometric (GMG) and Algebraic Multigrid (AMG) have both their own benefits and limitations. Combining the simplicity of AMG...
http://nanohub.org/resources/23493

HPGMG: Benchmarking Computers Using Multigrid
04 Feb 2016  Online Presentations  Contributor(s): Jed Brown
HPGMG (https://hpgmg.org) is a geometric multigrid benchmark designed to measure the performance and versatility of computers. For a benchmark to be representative of applications, good...
http://nanohub.org/resources/23495

A Scalable Algorithm for Inverse Medium Problems with Multiple Sources
04 Feb 2016  Online Presentations  Contributor(s): Keith Kelly
We consider the problem of acoustic scattering as described by the freespace, timeharmonic scalar wave equation given by (0.1) along with radiation boundary conditions. Here, is a...
http://nanohub.org/resources/23498

Support Graph Smoothing Techniques
04 Feb 2016  Online Presentations  Contributor(s): Alyson Fox
Many tasks in largescale network analysis and simulation require efficient approximation of the solution to the linear system $ Lx=b$, where $ L$ is a graph Laplacian. However, due to the large...
http://nanohub.org/resources/23500

TaskGraph and Functional Programming Models: The New Paradigm
04 Feb 2016  Online Presentations  Contributor(s): Ben Bergen
The Message Passing Interface (MPI) is an example of a distributedmemory communication model that has served us well through the CISC processor era. However, because of MPI's lowlevel...
http://nanohub.org/resources/23502

A Fast Multigrid Approach for Solving the Helmholtz Equation with a Point Source
04 Feb 2016  Online Presentations  Contributor(s): Eran Treister
Solving the discretized Helmholtz equations with high wave numbers in large dimensions is a challenging task. However, in many scenarios, the solution of these equations is required for a point...
http://nanohub.org/resources/23504

Compatible Relaxation Based GeometricAlgebraic Multigrid
04 Feb 2016  Online Presentations  Contributor(s): Fei Cao
We develop compatible relaxation algorithms for smoothed aggregationbased multigrid coarsening. In the proposed method, we use the geometry of the given discrete problem on the finest level to...
http://nanohub.org/resources/23506

Hub Snub: Removing Vertices with High Degree from Coarsegrid Correction
04 Feb 2016  Online Presentations  Contributor(s): Geoffry Sanders
Network scientists often employ numerical solutions to linear systems as subroutines of data mining algorithms. Due to the illconditioned nature of the systems, obtaining solutions with standard...
http://nanohub.org/resources/23508

On the Preconditioning of a HighOrder RDGbased AllSpeed NavierStokes Solver
04 Feb 2016  Online Presentations  Contributor(s): Brian Weston
We investigate the preconditioning of an allspeed NavierStokes solver, based on the orthogonalbasis Reconstructed Discontinuous Galerkin (RDG) space discretization, and integrated using a...
http://nanohub.org/resources/23510

Is the Ideal Approximation Operator Always "Ideal" for a Particular C/F Splitting?
04 Feb 2016  Online Presentations  Contributor(s): Erin Molloy
Given a coarse grid, the ideal prolongation operator is defined by , where the weight matrix, , interpolates a set of fine grid variable (points) from a set of coarse grid...
http://nanohub.org/resources/23512

Reducing Communication Costs for Sparse Matrix Multiplication within Algebraic Multigrid
04 Feb 2016  Online Presentations  Contributor(s): Grey Ballard
We consider the sequence of sparse matrixmatrix multiplications performed during the setup phase of algebraic multigrid. In particular, we show that the most commonly used parallel algorithm is...
http://nanohub.org/resources/23514

Spacetime constrained FOSLS with AMGe upscaling
04 Feb 2016  Online Presentations  Contributor(s): Panayot Vassilevski
We consider timedependent PDEs discretized in combined spacetime domains. We first reduce the PDE to a first order system. Very often in practice, one of the equations of the reduced system...
http://nanohub.org/resources/23516

Multilevel Markov Chain Monte Carlo for Uncertainty Quantification in Subsurface Flow
04 Feb 2016  Online Presentations  Contributor(s): Christian Ketelsen
The multilevel Monte Carlo method has been shown to be an effective variance reduction technique for quantifying uncertainty in subsurface flow simulations when the random conductivity field can...
http://nanohub.org/resources/23518

Discretization of Elliptic Differential Equations Using Sparse Grids and Prewavelets
04 Feb 2016  Online Presentations  Contributor(s): Christoph Pflaum
Sparse grids can be used to discretize second order elliptic differential equations on a ddimensional cube. Using Galerkin discretization, we obtain a linear equation system...
http://nanohub.org/resources/23520

High Dimensional Uncertainty Quantification via Multilevel Monte Carlo
04 Feb 2016  Online Presentations  Contributor(s): Hillary Fairbanks
Multilevel Monte Carlo (MLMC) has been shown to be a cost effective way to compute moments of desired quantities of interest in stochastic partial differential equations when the uncertainty in...
http://nanohub.org/resources/23522