当前位置: X-MOL 学术Int. J. Rock Mech. Min. Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A novel GPGPU-parallelized contact detection algorithm for combined finite-discrete element method
International Journal of Rock Mechanics and Mining Sciences ( IF 7.2 ) Pub Date : 2021-06-04 , DOI: 10.1016/j.ijrmms.2021.104782
He Liu , Quansheng Liu , Hao Ma , Jacob Fish

This paper presents a novel algorithm for contact detection for the three-dimensional combined finite-discrete element method (3D FDEM). The contact detection consists of two phases, neighbor search and fine search. Both phases are fully parallelized with Compute Unified Device Architecture (CUDA). In contrast to the non-binary search (NBS) algorithm, the proposed neighbor search algorithm is not sensitive to the element size distribution. To avoid the algorithm being performed at every step, an efficient GPGPU (general purpose graphic processing unit) -parallelized velocity reduction algorithm is employed. For the fine search, the concepts of “positive faces” and “positive edges” are proposed, and the process is considerably simplified and runs faster than the 3D separation axis algorithm. Numerical tests are performed to validate the efficiency and effectiveness of the proposed algorithms. The result shows that for both phases, the computation time is linearly proportional to the number of potential contact pairs regardless of the element size distribution. Furthermore, by using NVIDIA Telsa V100, the resultant overall speed-up ratios of the proposed contact detection algorithms relative to the original Y3D version for uniform and non-uniform element size distributions can reach up to 1982.6 and 13,894.7, respectively. For both quasi-static and dynamic problems, the simulated fracture patterns are in good agreement with the results generated by the NBS algorithm. The proposed methodology can be also employed for 2D FDEM and discrete element method (DEM).



中文翻译:

一种新的联合有限离散元方法的GPGPU并行接触检测算法

本文提出了一种用于三维组合有限离散元方法 (3D FDEM) 的接触检测的新算法。接触检测包括两个阶段,邻居搜索和精细搜索。这两个阶段都与统一计算设备架构 (CUDA) 完全并行。与非二元搜索 (NBS) 算法相比,所提出的邻居搜索算法对元素大小分布不敏感。为了避免在每一步都执行算法,采用了高效的 GPGPU(通用图形处理单元)-并行速度降低算法。对于精细搜索,提出了“正脸”和“正边缘”的概念,过程大大简化,运行速度比3D分离轴算法快。进行数值测试以验证所提出算法的效率和有效性。结果表明,对于这两个阶段,无论单元尺寸分布如何,计算时间都与潜在接触对的数量成线性比例。此外,通过使用 NVIDIA Telsa V100,所提出的接触检测算法相对于原始 Y3D 版本的均匀和非均匀元素尺寸分布的整体加速比分别可达到 1982.6 和 13,894.7。对于准静态和动态问题,模拟的裂缝模式与 NBS 算法生成的结果非常吻合。所提出的方法也可用于 2D FDEM 和 无论单元大小分布如何,计算时间都与潜在接触对的数量成线性比例。此外,通过使用 NVIDIA Telsa V100,所提出的接触检测算法相对于原始 Y3D 版本的均匀和非均匀元素尺寸分布的整体加速比分别可达到 1982.6 和 13,894.7。对于准静态和动态问题,模拟的裂缝模式与 NBS 算法生成的结果非常吻合。所提出的方法也可用于 2D FDEM 和 无论单元大小分布如何,计算时间都与潜在接触对的数量成线性比例。此外,通过使用 NVIDIA Telsa V100,所提出的接触检测算法相对于原始 Y3D 版本的均匀和非均匀元素尺寸分布的整体加速比分别可达到 1982.6 和 13,894.7。对于准静态和动态问题,模拟的裂缝模式与 NBS 算法生成的结果非常吻合。所提出的方法也可用于 2D FDEM 和 对于均匀和非均匀元素尺寸分布,所提出的接触检测算法相对于原始 Y3D 版本的整体加速比可分别达到 1982.6 和 13,894.7。对于准静态和动态问题,模拟的裂缝模式与 NBS 算法生成的结果非常吻合。所提出的方法也可用于 2D FDEM 和 对于均匀和非均匀元素尺寸分布,所提出的接触检测算法相对于原始 Y3D 版本的整体加速比可分别达到 1982.6 和 13,894.7。对于准静态和动态问题,模拟的裂缝模式与 NBS 算法生成的结果非常吻合。所提出的方法也可用于 2D FDEM 和离散元法 (DEM)。

更新日期:2021-06-04
down
wechat
bug