Design of a Greedy Algorithm for Non-Uniform Space Partitioning across Homogeneous FPGAs in Molecular Simulation
Keywords:
Molecular simulation, Acceleration, Parallelization, Greedy algorithmAbstract
Efficient partitioning of the atomic space among parallel FPGAs is crucial for accelerating molecular simulations. Existing research has primarily focused on uniform partitioning, assuming a homogeneous distribution of atoms. However, in scenarios with non-uniform atomic distributions, these approaches may lead to suboptimal performance. This study investigates the impact of non-uniform atom distributions on molecular simulation performance across parallel FPGAs. We propose a novel space partitioning scheme that optimizes the distribution of atomic space among FPGAs, taking into account the spatial heterogeneity of atoms. Our evaluation demonstrates that the proposed scheme consistently outperforms uniform partitioning in terms of simulation speed across various spatial dimensions and atom counts, particularly in scenarios with non-uniform atom distributions.
Downloads
References
S. Páll et al., "Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS," The Journal of Chemical Physics, vol. 153, no. 13, 2020, doi: 10.1063/5.0018516.
C. Yang et al., "Molecular dynamics range-limited force evaluation optimized for FPGAs," in 2019 IEEE 30th International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2019, pp. 263-271, doi: 10.1109/ASAP.2019.00016.
C. Wu et al., "Optimized mappings for symmetric range-limited molecular force calculations on FPGAs," in 2022 32nd International Conference on Field-Programmable Logic and Applications (FPL), 2022, pp. 101-108, doi: 10.1109/FPL57034.2022.00026.
J. C. Phillips et al., "Scalable molecular dynamics with NAMD," Journal of Computational Chemistry, vol. 26, no. 16, pp. 1781-1802, 2005, doi: 10.1002/jcc.20289.
M. J. Abraham et al., "GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers," SoftwareX, vol. 1, pp. 19-25, 2015, doi: 10.1016/j.softx.2015.06.001.
P. Eastman et al., "OpenMM 7: Rapid development of high performance algorithms for molecular dynamics," PLoS Computational Biology, vol. 13, no. 7, p. e1005659, 2017, doi: 10.1371/journal.pcbi.1005659.
D. Lu et al., "86 PFLOPS deep potential molecular dynamics simulation of 100 million atoms with ab initio accuracy," Computer Physics Communications, vol. 259, p. 107624, 2021, doi: 10.1016/j.cpc.2020.107624.
S. Kasap and K. Benkrid, "Parallel processor design and implementation for molecular dynamics simulations on a FPGA-based supercomputer," Journal of Computers, vol. 7, no. 6, pp. 1312-1328, 2012, doi: 10.4304/jcp.7.6.1312-1328.
M. A. Khan, M. Chiu, and M. C. Herbordt, "FPGA-accelerated molecular dynamics," in High-Performance Computing Using FPGAs, 2013, pp. 105-135.
H. M. Waidyasooriya, M. Hariyama, and K. Kasahara, "An FPGA accelerator for molecular dynamics simulation using OpenCL," International Journal of Networked and Distributed Computing, vol. 5, no. 1, pp. 52-61, 2017, doi: 10.2991/ijndc.2017.5.1.6.
C. Pascoe, L. Stewart, B. W. Sherman, V. Sachdeva, and M. W. Herbordt, "Execution of complete molecular dynamics simulations on multiple FPGAs," in 2020 IEEE High Performance Extreme Computing Conference (HPEC), 2020, pp. 1-2, doi: 10.1109/HPEC43674.2020.9286155.
C. Yang et al., "Fully integrated FPGA molecular dynamics simulations," in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2019, pp. 1-31, doi: 10.1145/3295500.3356179.
D. Shallom, D. Naiger, S. Weiss, and T. Tuller, "Accelerating whole-cell simulations of mRNA translation using a dedicated hardware," ACS Synthetic Biology, vol. 10, no. 12, pp. 3489-3506, 2021, doi: 10.1021/acssynbio.1c00415.
L. C. Stewart, C. Pascoe, B. W. Sherman, M. Herbordt, and V. Sachdeva, "Particle mesh Ewald for molecular dynamics in OpenCL on an FPGA cluster," in arXiv preprint arXiv:2009.12617, 2020, doi: 10.1109/FCCM51124.2021.00055.
A. Ramaswami, T. Kenter, T. D. Kühne, and C. Plessl, "Efficient ab-initio molecular dynamic simulations by offloading fast Fourier transformations to FPGAs," in 2020 30th International Conference on Field-Programmable Logic and Applications (FPL), 2020, pp. 353-354, doi: 10.1109/FPL50879.2020.00065.
C. Wu, T. Geng, C. Yang, V. Sachdeva, W. Sherman, and M. Herbordt, "A Communication-Efficient Multi-Chip Design for Range-Limited Molecular Dynamics," in 2020 IEEE High Performance Extreme Computing Conference (HPEC), 2020, pp. 9-19, doi: 10.1109/HPEC43674.2020.9286146.
C. Wu et al., "Upgrade of FPGA range-limited molecular dynamics to handle hundreds of processors," in 2021 IEEE 29th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2021, pp. 142-151, doi: 10.1109/FCCM51124.2021.00024.
M. Yuan et al., "FPGA-accelerated Tersoff multi-body potential for molecular dynamics simulations," in International Symposium on Applied Reconfigurable Computing, 2022, pp. 17-31, doi: 10.1007/978-3-031-19983-7_2.
Downloads
Published
Submitted
Revised
Accepted
Issue
Section
License
Copyright (c) 2025 Faezeh Sadat Mozneb (Author); Kambiz Rahbar; Parvaneh Asghari, Parand Akhlaghi (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
