MILC Code Performance on High End CPU and GPU Supercomputer Clusters
Department of Physics & Astronomy, University of Utah, Salt Lake City, UT 84112, U.S.A.
2 Department of Physics, Indiana University, Bloomington, IN 47405, U.S.A.
3 Department of Physics, University of Arizona, Tucson, AZ 85721, U.S.A.
** Speaker, e-mail: firstname.lastname@example.org
Published online: 26 March 2018
With recent developments in parallel supercomputing architecture, many core, multi-core, and GPU processors are now commonplace, resulting in more levels of parallelism, memory hierarchy, and programming complexity. It has been necessary to adapt the MILC code to these new processors starting with NVIDIA GPUs, and more recently, the Intel Xeon Phi processors. We report on our efforts to port and optimize our code for the Intel Knights Landing architecture. We consider performance of the MILC code with MPI and OpenMP, and optimizations with QOPQDP and QPhiX. For the latter approach, we concentrate on the staggered conjugate gradient and gauge force. We also consider performance on recent NVIDIA GPUs using the QUDA library.
© 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/).