EPJ Web Conf.
Volume 175, 201835th International Symposium on Lattice Field Theory (Lattice 2017)
|Number of page(s)||8|
|Section||9 Software Development|
|Published online||26 March 2018|
Performance Portability Strategies for Grid C++ Expression Templates
Higgs Centre for Theoretical Physics, School of Physics & Astronomy, University of Edinburgh, EH9 3FD, UK
2 NVIDIA Corporation, Santa Clara, CA 95050, USA
3 Department of Physics and Astronomy, University of Utah, Salt Lake City, UT 84112, USA
4 Computational Science Initiative, Brookhaven National Laboratory, Upton, New York 11973, USA
* Speaker, e-mail: firstname.lastname@example.org
Published online: 26 March 2018
One of the key requirements for the Lattice QCD Application Development as part of the US Exascale Computing Project is performance portability across multiple architectures. Using the Grid C++ expression template as a starting point, we report on the progress made with regards to the Grid GPU offloading strategies. We present both the successes and issues encountered in using CUDA, OpenACC and Just-In-Time compilation. Experimentation and performance on GPUs with a SU(3)×SU(3) streaming test will be reported. We will also report on the challenges of using current OpenMP 4.x for GPU offloading in the same code.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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