OpenKMC: a KMC Design for a Hundred-Billion-Atom Simulation Using Millions of Cores on Sunway Taihulight

Authors: Kun Li (Institute of Computing Technology, Chinese Academy of Sciences; Chinese Academy of Sciences), Honghui Shang (Institute of Computing Technology, Chinese Academy of Sciences), Yunquan Zhang (Institute of Computing Technology, Chinese Academy of Sciences), Shigang Li (ETH Zurich), Baodong Wu (Institute of Computing Technology, Chinese Academy of Sciences; SenseTime Research), Dong Wang (Dalian Ocean University), Libo Zhang (Wuxi Jiangnan Institute of Computing Technology), Fang Li (Wuxi Jiangnan Institute of Computing Technology), Dexun Chen (National Supercomputing Center, Wuxi), Zhiqiang Wei (Qingdao National Laboratory for Marine Science and Technology)

Abstract: With more attention attached to nuclear energy, the formation mechanism of the solute clusters precipitation within complex alloys becomes intriguing research in the embrittlement of nuclear reactor pressure vessel (RPV) steels. Such phenomenon can be simulated with atomic kinetic Monte Carlo (AKMC) software, which evaluates the interactions of solute atoms with point defects in metal alloys. In this paper, we propose OpenKMC to accelerate large-scale KMC simulations on Sunway many-core architecture. To overcome the constraints caused by complex many-core architecture, we employ six levels of optimization in OpenKMC: (1) a new efficient potential computation model; (2) a group reaction strategy for fast event selection; (3) a software cache strategy; (4) combined communication optimizations; (5) a Transcription-Translation-Transmission algorithm for many-core optimization; (6) vectorization acceleration. Experiments illustrate that our OpenKMC has high accuracy and good scalability of applying hundred-billion-atom simulation over 5.2 million cores with a performance of over 80.1% parallel efficiency.


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