GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations

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• 作者：Trung Dac Nguyen ; ^{nguyentd@imech.ac.vn}
• 关键词：Tersoff ; LAMMPS ; GPU acceleration ; Hybrid MPI/GPU ; High-performance computing
• 刊名：Computer Physics Communications
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：212
• 期：Complete
• 页码：113-122
• 全文大小：1221 K
• 卷排序：212

文摘

The Tersoff potential is one of the empirical many-body potentials that has been widely used in simulation studies at atomic scales. Unlike pair-wise potentials, the Tersoff potential involves three-body terms, which require much more arithmetic operations and data dependency. In this contribution, we have implemented the GPU-accelerated version of several variants of the Tersoff potential for LAMMPS, an open-source massively parallel Molecular Dynamics code. Compared to the existing MPI implementation in LAMMPS, the GPU implementation exhibits a better scalability and offers a speedup of 2.2X when run on 1000 compute nodes on the Titan supercomputer. On a single node, the speedup ranges from 2.0 to 8.0 times, depending on the number of atoms per GPU and hardware configurations. The most notable features of our GPU-accelerated version include its design for MPI/accelerator heterogeneous parallelism, its compatibility with other functionalities in LAMMPS, its ability to give deterministic results and to support both NVIDIA CUDA- and OpenCL-enabled accelerators. Our implementation is now part of the GPU package in LAMMPS and accessible for public use.