http://arxiv.org/abs/1905.04341
Large scale simulations are a key pillar of modern research and require ever increasing computational resources. Different novel manycore architectures have emerged in recent years on the way towards the exascale era. Performance portability is required to prevent repeated non-trivial refactoring of a code for different architectures. We combine Athena++, an existing magnetohydrodynamics (MHD) CPU code, with Kokkos, a performance portable on-node parallel programming paradigm, into K-Athena to allow efficient simulations on multiple architectures using a single codebase. We present profiling and scaling results for different platforms including Intel Skylake CPUs, Intel Xeon Phis, and NVIDIA GPUs. K-Athena achieves $>10^8$ cell-updates/s on a single V100 GPU for second-order double precision MHD calculations, and a speedup of 30 on up to 24,576 GPUs on Summit (compared to 172,032 CPU cores), reaching $1.94\times10^{12}$ total cell-updates/s at 76% parallel efficiency. Using a roofline analysis we demonstrate that the overall performance is currently limited by DRAM bandwidth and calculate a performance portability metric of 83.1%. Finally, we present the strategies used for implementation and the challenges encountered maximizing performance. This will provide other research groups with a straightforward approach to prepare their own codes for the exascale era. K-Athena is available at https://gitlab.com/pgrete/kathena .
P. Grete, F. Glines and B. O’Shea
Tue, 14 May 19
38/91
Comments: 12 pages, 6 figures, 1 table; submitted to IEEE Transactions on Parallel and Distributed Systems (TPDS)