Billion atom molecular dynamics simulations of carbon at extreme conditions and experimental time and length scales

The International Conference for High Performance Computing, Networking, Storage, and Analysis(2021)

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摘要
ABSTRACTBillion atom molecular dynamics (MD) using quantum-accurate machine-learning Spectral Neighbor Analysis Potential (SNAP) observed long-sought high pressure BC8 phase of carbon at extreme pressure (12 Mbar) and temperature (5,000 K). 24-hour, 4650 node production simulation on OLCF Summit demonstrated an unprecedented scaling and unmatched real-world performance of SNAP MD while sampling 1 nanosecond of physical time. Efficient implementation of SNAP force kernel in LAMMPS using the Kokkos CUDA backend on NVIDIA GPUs combined with excellent strong scaling (better than 97% parallel efficiency) enabled a peak computing rate of 50.0 PFLOPs (24.9% of theoretical peak) for a 20 billion atom MD simulation on the full Summit machine (27,900 GPUs). The peak MD performance of 6.21 Matom-steps/node-s is 22.9 times greater than a previous record for quantum-accurate MD. Near perfect weak scaling of SNAP MD highlights its excellent potential to advance the frontier of quantum-accurate MD to trillion atom simulations on upcoming exascale platforms.
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关键词
molecular dynamics, machine-learning interatomic potentials, carbon, extreme conditions
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