Abstract
Molecular Dynamics simulation (MD) models the interactions of thousands to millions of particles through the iterative application of fundamental physics, and MD is one of the core methods in High-Performance Computing (HPC). However, the inherent weak scalability problem of force interactions renders MD simulation quite computationally intensive and challenging to scale. To this end, specialized FPGA-based accelerators have been proposed to solve this problem. In this work, we focus on many-body potentials on a single FPGA. Firstly, we proposed an efficient data transfer strategy to eliminate the latency between on-chip and off-chip memory. Then, the fixed-point description of data type is developed for computation to increase the utilization of on-chip resources. At last, a custom pipelined strategy is presented for Tersoff to get a better simulation performance. Compared with a floating-point implementation based on NVIDIA 28080ti GPUs, our design based on Xilinx U200 FPGA is 1.2 times better.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China (No. 62102114, U21B2031), and the Key Research Project of Zhejiang Lab (No. 2021PB0AC01).
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Yuan, M. et al. (2022). FPGA-Accelerated Tersoff Multi-body Potential for Molecular Dynamics Simulations. In: Gan, L., Wang, Y., Xue, W., Chau, T. (eds) Applied Reconfigurable Computing. Architectures, Tools, and Applications. ARC 2022. Lecture Notes in Computer Science, vol 13569. Springer, Cham. https://doi.org/10.1007/978-3-031-19983-7_2
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DOI: https://doi.org/10.1007/978-3-031-19983-7_2
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