Strong Scaling of OpenACC enabled Nek5000 on several GPU based HPC systems
Jonathan Vincent, Jing Gong, Martin Karp, Adam Peplinski, Niclas Jansson, Artur Podobas, Andreas Jocksch, Jie Yao, Fazle Hussain, Stefano Markidis, Matts Karlss… 展开作者
Jonathan Vincent, Jing Gong, Martin Karp, Adam Peplinski, Niclas Jansson, Artur Podobas, Andreas Jocksch, Jie Yao, Fazle Hussain, Stefano Markidis, Matts Karlsson, Dirk Pleiter, Erwin Laure, Philipp Schlatter
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9 pages, 8 figures. Submitted to HPC-Asia 2022 conference, updated to address reviewers comments
We present new results on the strong parallel scaling for the OpenACC-accelerated implementation of the high-order spectral element fluid dynamics solver Nek5000. The test case considered consists of a direct numerical simulation of fully-developed turbulent flow in a straight pipe, at two different Reynolds numbers $Re_τ=360$ and $Re_τ=550$, based on friction velocity and pipe radius. The strong scaling is tested on several GPU-enabled HPC systems, including the Swiss Piz Daint system, TACC's Longhorn, Jülich's JUWELS Booster, and Berzelius in Sweden. The performance results show that speed-up between 3-5 can be achieved using the GPU accelerated version compared with the CPU version on these different systems. The run-time for 20 timesteps reduces from 43.5 to 13.2 seconds with increasing the number of GPUs from 64 to 512 for $Re_τ=550$ case on JUWELS Booster system. This illustrates the GPU accelerated version the potential for high throughput. At the same time, the strong scaling limit is significantly larger for GPUs, at about $2000-5000$ elements per rank; compared to about $50-100$ for a CPU-rank.
SPARS: A Reinforcement Learning-Enabled Simulator for Power Management in HPC Job Scheduling
Universitas Gadjah Mada（加查马达大学）；Universitas Ahmad Dahlan（艾哈迈德·达兰大学）；Institut Bisnis dan Teknologi Indonesia（印度尼西亚商业技术学院）；National Taiwan University of Science and Technology（台湾科技大学）；Tohoku University（东北大学）
Multi-Partner Project: Multi-GPU Performance Portability Analysis for CFD Simulations at Scale
National Technical University of Athens（雅典国立技术大学）；KTH Royal Institute of Technology（皇家理工学院）；Hewlett Packard Enterprise (HPE)（惠普企业）；Technical University of Delft（代尔夫特理工大学）；University of Michigan（密歇根大学）
