GPU-Based Parallel Computing for the Simulation of Complex Multibody Systems with Unilateral and Bilateral Constraints: An Overview
This work reports on advances in large-scale multibody dynamics simulation facilitated by the use of the Graphics Processing Unit (GPU). A description of the GPU execution model along with its memory spaces is provided to illustrate its potential parallel scientific computing. The equations of motion associated with the dynamics of large system of rigid bodies are introduced and a solution method is presented. The solution method is designed to map well on the parallel hardware, which is demonstrated by an order of magnitude reductions in simulation time for large systems that concern the dynamics of granular material. One of the salient attributes of the solution method is its linear scaling with the dimension of the problem. This is due to efficient algorithms that handle in linear time both the collision detection and the solution of the nonlinear complementarity problem associated with the proposed approach. The current implementation supports the simulation of systems with more than one million bodies on commodity desktops. Efforts are under way to extend this number to hundreds of millions of bodies on small affordable clusters.
KeywordsGraphic Processing Unit Collision Detection Global Memory Frictional Contact Multibody Dynamic
- .Moreau JJ (1983) Standard inelastic shocks and the dynamics of unilateral constraints: CISM Courses and Lectures. In: Piero GD, Macieri F (eds) Unilateral problems in structural analysis. Wiley, New York, p 173–221Google Scholar
- .Manferdelli JL (2007) The many-core inflection point for mass market computer systems. CTWatch Quart 3(1)Google Scholar
- .Negrut D (2008) High performance computing for engineering applications, Course Notes ME964 (September 9 Lecture): http://sbel.wisc.edu/Courses/ME964/2008/index.htm, University of Wisconsin
- .NVIDIA (2009) Compute unified device architecture programming guide 2.3: http://developer.download.nvidia.com/compute/cuda/2_3/toolkit/docs/NVIDIA_CUDA_ProgrammingGuide_2.3.pdf.
- .Tasora A, Anitescu M (2008) A fast NCP solver for large rigid-body problems with contacts, friction, and joints. Multibody dynamics: computational methods and applications. Springer, Berlin, p. 45Google Scholar
- .Harris M, Shubhabrata S, Owens JD (2008) Parallel Prefix Sum (Scan) with CUDA. In: Nguyen H (ed) GPU Gems 3, Addison-Wesley, New York, p. 851–876Google Scholar
- .Heyn T, Mazhar H, Negrut D (2009) On the simulation of tracked vehicles operating on granular terrain: a parallel multibody dynamics aproach (to be submitted). Multibody system dynamicsGoogle Scholar
- .Heyn T (2009) Simulation of tracked vehicles on granular terrain leveraging GPU computing. M.S. Thesis, in Mechanical Engineering, University of Wisconsin-Madison, MadisonGoogle Scholar
- .Mazhar H (2009) Million body simulation. http://sbel.wisc.edu/Animations/index.htm
- .Gougar H, Ougouag A, Terry W (2004) Advanced core design and fuel management for pebble-bed reactors. Idaho National Engineering and Environmental Laboratory, INEEL/EXT-04-02245Google Scholar
- .Kadak A, Bazant M (2004) Pebble flow experiments for pebble bed reactors, 2nd International Topical Meeting on High Temperature Reactor Technology, Beijing, China, 22–24 Sept 2004Google Scholar
- .Ougouag A, Ortensi J, Hiruta H (2009) Analysis of an earthquake-initiated-transient in a PBR. Tech. Rep. INL/CON-08-14876, Idaho National Laboratory (INL)Google Scholar