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Three complementary methods have been implemented in the code Denovo that accelerate neutral particle transport calculations with methods that use leadership-class computers fully and effectively: a multigroup block (MG) Krylov solver, a…

Numerical Analysis · Computer Science 2017-12-14 R. N. Slaybaugh , M. Ramirez-Zweiger , Tara Pandya , Steven Hamilton , T. M. Evans

We have added a new multigrid in energy (MGE) preconditioner to the Denovo discrete-ordinates radiation transport code. This preconditioner takes advantage of a new multilevel parallel decomposition. A multigroup Krylov subspace iterative…

Numerical Analysis · Mathematics 2016-12-14 R. N. Slaybaugh , T. M. Evans , G. G. Davidson , P. P. H. Wilson

The novel contribution of this paper relies in the proposal of a fully implicit numerical method designed for nonlinear degenerate parabolic equations, in its convergence/stability analysis, and in the study of the related computational…

Numerical Analysis · Mathematics 2010-01-20 Matteo Semplice , Marco Donatelli , Stefano Serra-Capizzano

Large-scale numerical simulations often come at the expense of daunting computations. High-Performance Computing has enhanced the process, but adapting legacy codes to leverage parallel GPU computations remains challenging. Meanwhile,…

Preconditioning techniques are crucial for enhancing the efficiency of solving large-scale linear equation systems that arise from partial differential equation (PDE) discretization. These techniques, such as Incomplete Cholesky…

Machine Learning · Computer Science 2024-12-11 Rui Li , Song Wang , Chen Wang

This work presents efficient solution techniques for radiative transfer in the smoothed particle hydrodynamics discretization. Two choices that impact efficiency are how the material and radiation energy are coupled, which determines the…

Computational Physics · Physics 2021-03-17 Brody R. Bassett , J. Michael Owen , Thomas A. Brunner

The authors propose a recycling Krylov subspace method for the solution of a sequence of self-adjoint linear systems. Such problems appear, for example, in the Newton process for solving nonlinear equations. Ritz vectors are automatically…

Numerical Analysis · Mathematics 2015-03-13 André Gaul , Nico Schlömer

We generalize the Rayleigh Quotient Iteration (RQI) to the problem of solving a nonlinear equation where the variables are divided into two subsets, one satisfying additional equality constraints and the other could be considered as…

Optimization and Control · Mathematics 2023-07-21 Du Nguyen

The multigroup neutron transport equations have been widely used to study the motion of neutrons and their interactions with the background materials. Numerical simulation of the multigroup neutron transport equations is computationally…

An approach is given for solving large linear systems that combines Krylov methods with use of two different grid levels. Eigenvectors are computed on the coarse grid and used to deflate eigenvalues on the fine grid. GMRES-type methods are…

Numerical Analysis · Mathematics 2020-05-08 Ronald B. Morgan , Travis Whyte , Walter Wilcox , Zhao Yang

Many applications involving porous media--notably reservoir engineering and geologic applications--involve tight coupling between multiphase fluid flow, transport, and poromechanical deformation. While numerical models for these processes…

In this paper, we present a data-driven approach to iteratively solve the discrete heterogeneous Helmholtz equation at high wavenumbers. In our approach, we combine classical iterative solvers with convolutional neural networks (CNNs) to…

Numerical Analysis · Mathematics 2022-03-22 Yael Azulay , Eran Treister

Numerical solution of discrete PDEs corresponding to saddle point problems is highly relevant to physical systems such as Stokes flow. However, scaling up numerical solvers for such systems is often met with challenges in efficiency and…

Numerical Analysis · Mathematics 2024-08-23 Yutian Tao , Eftychios Sifakis

The convergence of Krylov-based linear iterative solvers applied to parametric partial differential equations (PDEs) is often highly sensitive to the domain, its discretization, the location/values of the applied Dirichlet/Neumann boundary…

Numerical Analysis · Mathematics 2026-05-12 Francesc Levrero-Florencio , Youngkyu Lee , Jay Pathak , George Em Karniadakis

We present variants of the Conjugate Gradient (CG), Conjugate Residual (CR), and Generalized Minimal Residual (GMRES) methods which are both pipelined and flexible. These allow computation of inner products and norms to be overlapped with…

Numerical Analysis · Mathematics 2016-09-16 Patrick Sanan , Sascha M. Schnepp , Dave. A. May

In this work we investigate replacing standard quadrature techniques used in deterministic linear solvers with a fixed-seed Quasi-Monte Carlo calculation to obtain more accurate and efficient solutions to the neutron transport equation…

Computational Physics · Physics 2022-09-07 Sam Pasmann , Ilham Variansyah , C. T. Kelley , Ryan McClarren

Iterative solvers preconditioned with algebraic multigrid have been devised as an optimal technology to speed up the response of large sparse linear systems. In this work, this technique was implemented in the framework of the dual…

Geophysics · Physics 2020-01-22 M. A. Sbai , A. Larabi

We propose a simple and efficient one-way multigrid method for self-consistent electronic structure calculations based on iterative diagonalization. Total energy calculations are performed on several different levels of grids starting from…

Computational Physics · Physics 2016-01-01 In-Ho Lee , Yong-Hoon Kim , Richard Martin

The application of eigenvalue theory to dual quaternion Hermitian matrices holds significance in the realm of multi-agent formation control. In this paper, we study the Rayleigh quotient iteration (RQI) for solving the right eigenpairs of…

Numerical Analysis · Mathematics 2024-09-25 Shan-Qi Duan , Qing-Wen Wang , Xue-Feng Duan

Lattice quantum chromodynamics simulations in nuclear physics have benefited from a tremendous number of algorithmic advances such as multigrid and eigenvector deflation. These improve the time to solution but do not alleviate the intrinsic…

High Energy Physics - Lattice · Physics 2018-08-09 M. A. Clark , Alexei Strelchenko , Alejandro Vaquero , Mathias Wagner , Evan Weinberg
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