Abstract

Different from previous molecular dynamics (MD) simulation with pair potentials and many-body potentials, an efficient and highly scalable algorithm for GPU-accelerated MD simulation of solid covalent crystals is described in detail in this paper using sophisticated many-body potentials, such as Tersoff potentials for silicon crystals. The algorithm has effectively taken advantage of the reordering and sorting of atoms and the hierarchical memory of a GPU. The final results indicate that, about 30.5% of the peak performance of a single GPU can be achieved with a speedup of about 650 over a contemporary CPU core, and more than 15 million atoms can be processed by a single GPU with a speed of around 2 ns/day. Furthermore, the proposed algorithm is scalable and transferable, which can be applied to other many-body interactions and related large-scale parallel computation.

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