@Article{CiCP-27-2,
author = {S., Maurice, Fabien},
title = {A GPU-Accelerated Hybridizable Discontinuous Galerkin Method for Linear Elasticity},
journal = {Communications in Computational Physics},
year = {2020},
volume = {27},
number = {2},
pages = {513--545},
abstract = {<p style="text-align: justify;">We design and analyze an efficient GPU-accelerated hybridizable discontinuous Galerkin method for linear elasticity. Performance analysis of the method is
done using the state-of-the-art Time-Accuracy-Size (TAS) spectrum. TAS is a new performance measure which takes into account the accuracy of the solution. Standard
performance measures, like floating point operations or run-time, are not completely
appropriate for gauging the performance of approximations of continuum mechanics
problems, as they neglect the solutions accuracy. A standard roofline model demonstrates that our method is utilizing computational resources efficiently, and as such,
significant speed ups over a serial implementation are obtained. By combining traditional performance measures and the novel time-accuracy measures [7] into our performance model, we are able to draw more complete conclusions about which discretizations are best suited for an application. Several numerical experiments validate
and verify our numerical scheme.</p>},
issn = {1991-7120},
doi = {https://doi.org/10.4208/cicp.OA-2018-0235},
url = {https://global-sci.com/article/79776/a-gpu-accelerated-hybridizable-discontinuous-galerkin-method-for-linear-elasticity}
}