GPU Algorithms for Efficient Exascale Discretizations
A. Abdelfattah
V. Barra
Natalie N. Beams
R. Bleile
Jed Brown
Sylvain Camier
R. Carson
Noel Chalmers
V. Dobrev
Yohann Dudouit
Paul F. Fischer
A. Karakus
S. Kerkemeier
T. Kolev
Yu-Hsiang Lan
Elia Merzari
M. Min
Malachi Phillips
T. Rathnayake
R. Rieben
T. Stitt
A. Tomboulides
S. Tomov
V. Tomov
A. Vargas
T. Warburton
K. Weiss

Abstract
In this paper we describe the research and development activities in the Center for Efficient Exascale Discretization within the US Exascale Computing Project, targeting state-of-the-art high-order finite-element algorithms for high-order applications on GPU-accelerated platforms. We discuss the GPU developments in several components of the CEED software stack, including the libCEED, MAGMA, MFEM, libParanumal, and Nek projects. We report performance and capability improvements in several CEED-enabled applications on both NVIDIA and AMD GPU systems.
View on arXivComments on this paper