GPU-based parallel algorithm for particle contact detection and its application in self-compacting concrete flow simulations

Authors:
Jingwei Zheng;Xuehui An;Miansong Huang
Affiliations:
State Key Laboratory of Hydroscience and Engineering, Tsinghua University, 100084 Beijing, China;State Key Laboratory of Hydroscience and Engineering, Tsinghua University, 100084 Beijing, China;State Key Laboratory of Hydroscience and Engineering, Tsinghua University, 100084 Beijing, China
Venue:
Computers and Structures
Year:
2012

Citing 6
Cited 1

Photon mapping on programmable graphics hardware

Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Sliced data structure for particle-based simulations on GPUs

Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia
Real-time KD-tree construction on graphics hardware

ACM SIGGRAPH Asia 2008 papers
A parallel algorithm for construction of uniform grids

Proceedings of the Conference on High Performance Graphics 2009
Interactive SPH simulation and rendering on the GPU

Proceedings of the 2010 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Adaptive sampling and rendering of fluids on the GPU

SPBG'08 Proceedings of the Fifth Eurographics / IEEE VGTC conference on Point-Based Graphics

A coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing

Advances in Engineering Software

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the present paper, we propose a novel parallel graphic processing unit (GPU)-friendly algorithm for contact detection. We develop a GPU-discrete element method (GPU-DEM) platform for self-compacting concrete (SCC) flow simulations. The algorithm takes full advantage of the parallel architecture of the GPU and can rapidly perform contact detection than that using CPU algorithm. Its scalability and robustness make it suitable for particle contact detection for different particle size distributions. The proposed GPU-DEM platform implements all the steps of DEM on GPU, which prevents the transfer of data between GPU and CPU. The proposed methodology is expected to be relevant in computational mechanics with applications to SCC flow simulations, where the number of particles ranges from millions to billions.