Abstract: We present a new platform of code generation for block structured adaptive mesh refinement hierarchies, and discuss their applications to solve partial differential equations. We will begin by discussing the importance of code generation for expanding symbolic tensor equations in numerical solvers for PDEs. Specifically, we will present code generation for AMReX, a software framework for massively parallel, block structured AMR applications. We will demonstrate code generation for the case of spacetime evolution of black hole mergers, where we obtain the time derivatives of the PDEs using finite difference discretization in space. We integrate the resulting system using a Runge-Kutta scheme at each level of the AMR hierarchy, using subcycling in time to integrate all levels of refinement. We will then discuss the data structures and algorithms within AMReX that enable this functionality, and discuss some of the broader applications to numerical simulation.

Speaker’s’ Bio : Don Willcox is a postdoctoral researcher in the Center for Computational Sciences and Engineering (CCSE) in the Computational Research Division at Berkeley Lab. His research in computational astrophysics centers on designing large scale hydrodynamics simulations of supernova explosions. He also develops efficient algorithms for ODE integration to model nuclear burning in various astrophysical processes and accelerates these algorithms for GPU-based supercomputers. Don completed his PhD in Physics at Stony Brook University in August 2018 working on thermonuclear supernovae modeling and the convective Urca process in white dwarf stars before joining Berkeley Lab.

Adam Peterson is a postdoctoral researcher in the Center for Computational Sciences and Engineering in the Computational Research Division at Berkeley Lab. His research interests center around theoretical physics and numerical simulations of high energy, condensed matter, and cosmological/astrophysical systems. He is currently working on developing code generation for numerical relativity and interfacing the Einstein Toolkit with AMReX. Prior to working at Berkeley Lab, he was a postdoctoral fellow at the University of Toronto Department of Physics. He completed his Ph. D. in theoretical physics at the University of Minnesota in August 2016.

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Conference ID: 103 701 85#

Last Updated: July 14, 2020 - 2:20 pm