M
Matthew G. Knepley
Researcher at University at Buffalo
Publications - 149
Citations - 5343
Matthew G. Knepley is an academic researcher from University at Buffalo. The author has contributed to research in topics: Finite element method & Solver. The author has an hindex of 25, co-authored 136 publications receiving 4680 citations. Previous affiliations of Matthew G. Knepley include Case Western Reserve University & University of Illinois at Chicago.
Papers
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PETSc Users Manual
Satish Balay,Shrirang Abhyankar,Mark F. Adams,Jed Brown,Peter R. Brune,Kristopher R. Buschelman,Lisandro Dalcin,Alp Dener,Eijkhout,William Gropp,Dmitry Karpeyev,Dinesh K. Kaushik,Matthew G. Knepley,Dave A. May,L. Curfman McInnes,Richard T. Mills,Todd Munson,Karl Rupp,Patrick Sanan,Barry Smith,Stefano Zampini,Hong Zhang +21 more
TL;DR: The Portable, Extensible Toolkit for Scientific Computation (PETSc), is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations that supports MPI, and GPUs through CUDA or OpenCL, as well as hybrid MPI-GPU parallelism.
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A domain decomposition approach to implementing fault slip in finite-element models of quasi-static and dynamic crustal deformation
TL;DR: In this article, a domain decomposition approach with Lagrange multipliers is employed to implement fault slip in a finite-element code, PyLith, for use in both quasi-static and dynamic crustal deformation applications.
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A Domain Decomposition Approach to Implementing Fault Slip in Finite-Element Models of Quasi-static and Dynamic Crustal Deformation
TL;DR: In this article, a domain decomposition approach with Lagrange multipliers is employed to implement fault slip in a finite-element code, PyLith, for use in both quasi-static and dynamic crustal deformation applications.
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Composing Scalable Nonlinear Algebraic Solvers
TL;DR: In this paper, the basic concepts of nonlinear omposition and preconditioning are described and a number of solvers applicable to nonlinear partial differential equations are presented, where the performance gains from using composed solvers can be substantial compared with gains from standard Newton-Krylov methods.
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Modular and flexible spectral-element waveform modelling in two and three dimensions
Michael Afanasiev,Christian Boehm,Martin van Driel,Lion Krischer,Max Rietmann,Dave A. May,Matthew G. Knepley,Andreas Fichtner +7 more
TL;DR: This section explains the motivation behind selecting the finiteelement method as a spatial discretization and shows how the mathematical details of the method can be abstracted and implemented efficiently on a computer.