
Plasmonics and Metasurfaces for Extreme Manipulation of Light
08 Mar 2016  Online Presentations  Contributor(s): Yongmin Liu
In this talk, I will present some of our work in the fascinating field of plasmonics and optical metasurfaces. First, I will discuss reconfigurable plasmonic lenses operating in microfluidic environment, which can dynamically diverge, collimate and focus surface plasmons [5]. Second, I will...

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 with unknowns. The corresponding discretization error is in the norm. A major difficulty in...

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 be represented by a simple prior distribution. In stateoftheart subsurface simulation the...

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 involves the divergence operator (in spacetime). The popular FOSLS (first order system leastsquares)...

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 often not the most communicationefficient one for all of the matrix multiplications involved. By...

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 variable (points), and the identity matrix, , represents the injection of points to and from...

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 highorder fullyimplicit time discretization method. The work is motivated by applications in Additive...

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 iterative methods is often prohibitively costly; current research aims to automatically construct...

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 coarsen the system together with compatible relaxation to from the sparsity structure of the...

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 source. In this case, the problem can be be reformulated and split into two parts: one in a solution...

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 interface, which requires the user to manage raw memory buffers, and its bulksynchronous communication...

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 size and complexity of scalefree graphs, standard iterative methods do not perform optimally. The...

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 point in , is the source term, and is the wavenumber. Our formulation is based on potential theory....

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 performance on the benchmark should be sufficient to ensure good performance on most important applications...

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 with the efficiency of GMG lead us to the development of an Hybrid Multigrid preconditionner. From...

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 fast wave dynamics to the desired evolution of equilibrium due to transport processes is large,...

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 nonlinear materials. We describe the linear problems arising in several variations of this problem,...

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 coupling between equations is strong. In this talk, we discuss the extension of BraessSarazin...

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, problemdependent tradeoff between efficient hardware use, robustness, and convergence rate in order to...

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 heterogeneous processing elements that operate at nearthresholdvoltage to meet power constraints. The...