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作者机构:Univ Illinois Dept Civil & Environm Engn Chicago IL 60680 USA Univ Illinois Natl Ctr Supercomp Applicat Chicago IL 60680 USA
出 版 物:《COMPUTERS AND GEOTECHNICS》 (计算机与土工学)
年 卷 期:2021年第137卷
页 面:104008-104008页
核心收录:
学科分类:0709[理学-地质学] 081803[工学-地质工程] 07[理学] 08[工学] 0708[理学-地球物理学] 0818[工学-地质资源与地质工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:Innovative Systems Laboratory
主 题:Shared-memory parallelization Discrete element method Polyhedral particle Impulse-based discrete element method
摘 要:Particle shape plays a vital role in granular material behavior, but simulations with realistic particle shapes are uncommon due to significant computational demands of complex particle geometry representation. In this work, BLOKS3D, a polyhedral Discrete Element Method (DEM) and impulse-based DEM (iDEM) codes are parallelized to enable large-scale simulations with realistic particle shapes on readily accessible multi-core machines. Data structures used in the original codes were redesigned and optimized, leading to 15% improved performance of the original serial codes. New parallel algorithms were developed resulting in 28 times performance improvement on a 48-core (quad-CPU) shared memory system over single core serial algorithm. The parallelized 3D polyhedral DEM and iDEM were applied to series of column collapse simulations. The codes successfully reproduced the runout distance in granular column collapse experiments. The particle force data from both parallelized DEM and iDEM matched data from the serial algorithm. The new parallel implementation of iDEM was then demonstrated with unprecedented 52 million 3D polyhedral particles simulations. This work will benefit future granular material studies with the newly introduced capacity to run large-scale simulations with realistic particle shapes on shared memory hardware platforms readily accessible to many engineers and researchers.