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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=680224
• 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.

百亿亿级高性能计算趋势表明，未来将以低成本提供大量计算资源，但需要新的软件设计和并行化策略来充分利用这些新兴的众核硬件系统。在过去六年中，申请人领导了名为 EXN/Aero 的多核计算流体动力学 (CFD) 代码的开发，与通过空间域分解获得的传统 CPU 解决方案相比，该代码目前正在展示显着的解决方案加速（使用 GPU）。 EXN/Aero 的开发还包括一种称为 parareal 的组合时空并行计算方法。这里，域分解包括空间和时间，是百亿亿级计算中的一个新兴研究领域，因为它提供了一种在高度并行应用程序受内存限制时减少计算时间的方法。然而，需要改进高雷诺数和多物理场 CFD 应用的方法。拟议研究的应用选择是环境和船舶/海底海洋流领域。 在这些领域建立一套高效的 3D 非定常湍流 CFD 模型对于全面的声源建模非常重要，包括随后输入到各种特征研究中。 申请人已与加拿大国防研究与发展部合作开展潜艇项目（开发包括 EXN/Aero 在内的一系列 CFD 模拟功能）多年，因此扩展到船舶领域是很自然的事情。特别是，该提案将重点关注开发船舶模拟的准真实方法的目标，其中包括波浪、船舶运动和推进（包括空化）的重要耦合。 所有这些方面在耦合时对于预测产生噪声源的高度湍流环境都很重要。这项研究将使加拿大工业界和政府能够利用未来的 CFD 超级计算技术，这对于开发船舶和海底平台等复杂系统以及潮汐能开发等环境流至关重要。