ELEMENT - Exascale Mesh Network

ELEMENT - 百兆亿级网状网络

• 批准号: EP/V001345/1
• 负责人: Mark Parsons
• 金额: $ 31.3万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV001345%2F1
• 关键词: ELEMENT; Exascale; Mesh; Network

The Exascale Mesh Network - ELEMENT - addresses the high priority use case of meshing for the Exascale (i.e. ensuring that meshes are of sufficient quality to represent Exascale problems and can be partitioned efficiently to minimise load imbalance) as well as meshing at the Exascale (i.e. creating highly scalable solutions that will be able to exploit extreme levels of parallelism). The meshes required for Exascale simulations, under which we will aim to model problems with extreme geometric complexity and levels of refinement, will necessarily be very large with 10^9 cells and above, and contain cells that may differ in size by many orders of magnitude to faithfully resolve the underlying physics at their appropriate scales. Meshing and geometry management remain a significant bottleneck for complex applications on HPC platforms, posing a challenging obstacle that must be overcome to enable Exascale simulations. From a technical perspective, these issues include (but are not limited to) improved geometric handling, mesh adaptation and optimisation, intelligent meshing, automation and robustness, all within a large distributed environment that lies outside of our current capabilities.ELEMENT's objectives are threefold: building a community around meshing practice by establishing a collaborative network; undertaking proof of concept studies, with prototype implementations of two target challenges; and publishing a Vision Paper and strategic research agenda covering the full meshing workflow, from mesh generation to adaptation, partitioning and visualisation.

亿级网格网络元素--解决亿级网格划分的高优先级用例(即确保网格具有足够的质量来表示亿级级问题，并且可以有效地进行分区以最大限度地减少负载不平衡)以及亿级级网格划分(即创建高度可扩展的解决方案，能够利用极端的并行性)。亿级模拟所需的网格，我们将致力于模拟具有极端几何复杂性和精细化水平的问题，必须非常大，具有10^9个或更高的单元，并包含大小可能相差许多个数量级的单元，以在适当的比例忠实地解决潜在的物理问题。网格划分和几何图形管理仍然是HPC平台上复杂应用程序的一个重要瓶颈，这是一个必须克服的具有挑战性的障碍，才能实现艾级模拟。从技术角度来看，这些问题包括(但不限于)改进的几何处理、网格适应和优化、智能网格划分、自动化和健壮性，所有这些都在我们当前能力之外的大型分布式环境中。ELEMENT的目标有三个：通过建立一个协作网络，围绕网格划分实践建立一个社区；进行概念验证研究，并实施两个目标挑战的原型；以及发布一份愿景文件和战略研究议程，涵盖从网格生成到适应、划分和可视化的整个网格划分工作流程。

项目成果

Fast Barycentric-Based Evaluation Over Spectral/hp Elements

• DOI: 10.1007/s10915-021-01750-2
• 发表时间: 2021-03
• 期刊: Journal of Scientific Computing
• 影响因子: 2.5
• 作者: Edward Laughton;Vidhi Zala;A. Narayan;R. Kirby;D. Moxey

A comparison of interpolation techniques for non-conformal high-order discontinuous Galerkin methods

• DOI: 10.1016/j.cma.2021.113820
• 发表时间: 2020-07
• 期刊: ArXiv
• 作者: Edward Laughton;G. Tabor;D. Moxey