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ENABLING COMPUTATIONAL DYNAMICS IN DISTRIBUTED COMPUTING ENVIRONMENTS USING A HETEROGENEOUS COMPUTING TEMPLATE

机译:使用异构计算模板在分布式计算环境中启用计算动力学

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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 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 sub-domains 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) a method for the geometric domain decomposition and mapping onto heterogeneous hardware; (b) methods for proximity computation or collision detection; (c) support for moving data among the corresponding hardware as elements move from subdomain to subdomain; (d) numerical methods for solving the specific dynamics problem of interest; and (e) tools for performing visualization and post-processing in a distributed manner. In this contribution the components (a) and (c) 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; i.e., task (b) above, is discussed separately and in the context of GPU computing. This task is shown to benefit 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 US 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.
机译:本文介绍了由工具和库组成的软件基础结构,这些工具和库旨在帮助开发人员实现在异构和分布式计算环境上运行的计算动力学应用程序。这些工具和库一起构成了所谓的异构计算模板(HCT)。此处假设异构和分布式计算硬件基础结构由CPU和GPU的组合组成。旨在在这种硬件拓扑上执行的计算动力学应用程序包括多体动力学,平滑粒子流体动力学(SPH)流体模拟和流固相互作用分析。 HCT所采用的解决方案方法的基本主题是将关注域划分为多个子域,每个子域均由单独的核心/加速器(CPU / GPU)对进行管理。 HCT的核心有五个组成部分,可以实现针对大规模动态系统仿真的分布式计算方法:(a)一种用于几何域分解并映射到异构硬件的方法; (b)接近度计算或碰撞检测的方法; (c)当元素从子域移到子域时,支持在相应的硬件之间移动数据; (d)解决感兴趣的特定动力学问题的数值方法; (e)用于以分布式方式执行可视化和后处理的工具。在此贡献中,通过离散元素方法(DEM)的示例演示了HCT的成分(a)和(c),该方法用于具有摩擦和接触的刚体动力学。摩擦接触动力学所需的碰撞检测任务;也就是说,上面的任务(b)在GPU计算的背景下进行了单独讨论。与传统的顺序实现相比,该任务的效率提高了两个数量级。注意:此处以商标名称,商标,制造商或其他名称提及任何特定的商业产品,过程或服务,并不表示其得到美国陆军的认可,推荐或偏爱。本文所表达的作者的观点和见解不一定表示或反映美国陆军的观点和见解,不得用于广告或产品背书目的。

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