Accelerating Manycore Fluid Flow Predictions Including Wave/Ship Motions Using Parareal

使用 Parareal 加速众核流体流动预测，包括波浪/船舶运动

• 批准号: RGPIN-2017-04247
• 负责人: Gerber, Andrew
• 金额: $ 1.82万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=638736
• 关键词: Accelerating; Manycore; Fluid; Flow; Predictions

Exascale high-performance computing trends point to substantial computing resources at a low cost moving into the future, but new software designs and parallelization strategies are required to take full advantage of these emerging manycore hardware systems. Over the past six years, the applicant has led the development of a manycore Computational Fluid Dynamics (CFD) code called EXN/Aero that is now demonstrating significant solution speed-up (using GPUs) versus traditional CPU solutions obtained with spatial domain decompositions. The EXN/Aero development has also included a combined space-time parallel computing approach called parareal. Here, the domain decomposition includes both space and time, and is an emerging research area in exascale computing since it provides a way to reduce computing time when a highly parallel application is memory-bound. There is, however, a need to refine the methodology for high-Reynolds number and multi-physics CFD applications. The applications of choice for the proposed research is in the area of environmental and ship/submarine ocean flows. Building an efficient set 3D unsteady turbulent flow CFD models in these areas is important for comprehensive acoustic source modeling, including subsequent input into a wide range of signatures studies. The applicant has worked for a number of years with Defense Research and Development Canada on their submarine program (developing a range of CFD simulation capabilities including EXN/Aero) and the extension to ships is therefore a natural one. In particular, the proposal will focus on objectives that develop the parareal method for ship simulations that include the important couplings of waves, ship motion and propulsion (including cavitation). All of these aspects are important, when coupled, to predicting the highly turbulent flow environment from which noise sources arise. The research will allow Canadian industry and government to tap into future CFD supercomputing technologies which will be essential to developing complex systems such as ship and submarine platforms, and environmental flows such as that for tidal energy development.

Exascale高性能计算趋势指出，以低成本转移到未来的大量计算资源，但是需要新的软件设计和并行化策略才能充分利用这些新出现的许多核心硬件系统。在过去的六年中，申请人领导了称为EXN/AERO的多核计算流体动力学（CFD）代码的开发，该代码现在证明了明显的解决方案加速（使用GPU）与通过空间域分解获得的传统CPU解决方案相比。 EXN/AERO开发还包括一种称为Parareal的时空平行计算方法。在这里，域的分解既包括空间和时间，也是Exascale计算中新兴的研究领域，因为它提供了一种减少高度平行应用程序为内存的计算时间的方法。但是，有必要优化高雷诺数和多物理CFD应用程序的方法。拟议研究的首选应用是在环境和船舶/海底海洋流的领域。 在这些区域中构建有效的集合3D不稳定的湍流CFD模型对于全面的声源建模很重要，包括随后对广泛的签名研究的输入。 申请人已经在加拿大国防研究和开发的潜艇计划（开发一系列CFD模拟功能）上工作了多年，因此，船舶的扩展是自然的。特别是，该提案将集中于开发用于船舶模拟方法的目标，其中包括波浪的重要耦合，船舶运动和推进（包括空穴）。 当耦合时，所有这些方面对于预测噪声源出现的高度湍流环境至关重要。这项研究将使加拿大工业和政府能够利用未来的CFD超级计算技术，这对于开发复杂的系统（例如船舶和海底平台）以及诸如潮汐能源开发之类的环境流程至关重要。