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Matt Knepley

Matt Knepley

The Portable Extensible Toolkit for Scientific Computation Workshop

Thursday, April 13th
8:30 AM - 12:30 PM
Student Union, Room 145A

Abstract:  Finite element and finite volume simulators are workhorses for scientific and engineering computation. Successful examples are several decades old. Can a case be made for redesigning these venerable codes to make them more maintainable, portable, efficient, scalable, and flexible? We will argue that indeed simulations can be reorganized to allow easier comparison between modern algorithms, ease the maintenance burden, aid architectural optimization, and greatly reduce the conceptual complexity of the code. We will use ideas from analysis, topology, software engineering, and numerical analysis to arrive at these conclusions.

Biography:  Matthew G. Knepley received his B.S. in Physics from Case Western Reserve University in 1994, an M.S. in Computer Science from the University of Minnesota in 1996, and a Ph.D. in Computer Science from Purdue University in 2000. He was a Research Scientist at Akamai Technologies in 2000 and 2001. Afterwards, he joined the Mathematics and Computer Science department at Argonne National Laboratory (ANL), where he was an Assistant Computational Mathematician, and a Fellow in the Computation Institute at University of Chicago, becoming a Senior Research Associate in 2009. In 2015, he joined the Computational and Applied Mathematics department at Rice University. His research focuses on scientific computation, including scalable algorithms and parallel computing, numerical analysis, software development, and computational geophysics and biology. He is an author of the widely used PETSc library for scientific computing from ANL, and is a principal designer of the PyLith library for the solution of dynamic and quasi-static tectonic deformation problems. He developed the PETSc scalable unstructured mesh support based upon ideas from combinatorial topology. He was a J. T. Oden Faculty Research Fellow at the Institute for Computation Engineering and Sciences, UT Austin, in 2008, won the R&D 100 Award in 2009, and the SIAM/ACM Prize in Computational Science and Engineering in 2015 as part of the PETSc team.