A High Performance Computing Framework for Physics-based Modeling and Simulation of Military Ground Vehicles

被引:1
作者
Negrut, Dan [1 ]
Lamb, David [1 ]
Gorsich, David [1 ]
机构
[1] Univ Wisconsin, Dept Mech Engn, Madison, WI 53706 USA
来源
MODELING AND SIMULATION FOR DEFENSE SYSTEMS AND APPLICATIONS VI | 2011年 / 8060卷
基金
美国国家科学基金会;
关键词
physics-based simulation; high performance computing; heterogeneous CPU/GPU computing; vehicle/terrain interaction; computational dynamics;
D O I
10.1117/12.882889
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper describes a software infrastructure made up of tools and libraries designed to assist developers in implementing computational dynamics applications running on heterogeneous and distributed computing environments. Together, these tools and libraries compose a so called Heterogeneous Computing Template (HCT). The heterogeneous and distributed computing hardware infrastructure is assumed herein to be made up of a combination of CPUs and Graphics Processing Units (GPUs). The computational dynamics applications targeted to execute on such a hardware topology include many-body dynamics, smoothed-particle hydrodynamics (SPH) fluid simulation, and fluid-solid interaction analysis. The underlying theme of the solution approach embraced by HCT is that of partitioning the domain of interest into a number of subdomains that are each managed by a separate core/accelerator (CPU/GPU) pair. Five components at the core of HCT enable the envisioned distributed computing approach to large-scale dynamical system simulation: (a) the ability to partition the problem according to the one-to-one mapping; i.e., spatial subdivision, discussed above (pre-processing); (b) a protocol for passing data between any two co-processors; (c) algorithms for element proximity computation; and (d) the ability to carry out post-processing in a distributed fashion. In this contribution the components (a) and (b) of the HCT are demonstrated via the example of the Discrete Element Method (DEM) for rigid body dynamics with friction and contact. The collision detection task required in frictional-contact dynamics (task (c) above), is shown to benefit on the GPU of a two order of magnitude gain in efficiency when compared to traditional sequential implementations. Note: Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not imply its endorsement, recommendation, or favoring by the United States Army. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Army, and shall not be used for advertising or product endorsement purposes.
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页数:11
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