G8 Multilateral Research Funding - ICOMEX

目前需要有能力以更高的分辨率运行大气模型，改进天气预报，特别是恶劣天气的预报，增进对气候过程的了解，并改进气候预测。更高的分辨率只能通过开发基于数十万处理器的未来超级计算平台来实现;对于这样的架构，处理器之间的通信是性能的显著瓶颈，并且需要与历史上使用的算法完全不同的算法。它们的准均匀分辨率应该最小化通信瓶颈，从而提供良好的性能。数值分析的最新进展意味着现在已有足够精度的格式。在特定应用需要更高分辨率的情况下，网格的局部细化是可能的。一个二十面体格网模型已被德国气象局使用了好几年，其他几个小组也有这种处于高级开发阶段的模型，拟议的项目将评估和比较一些二十面体格网模型的并行计算性能，并进行研究以提高其性能。具体的研究课题包括开发一个抽象模型描述方案，（尽可能）来自计算机科学问题的数值分析问题，基于图形处理单元（GPU）架构的模型实现，椭圆求解器的开发和评估，以确定稳定的长时间步长积分方案的可行性，开发内部后处理程序包，提供用户所需的诊断，同时尽量减少数据输出瓶颈，并制定优化输入/输出的战略。埃克塞特大学将特别致力于椭圆解算器和后处理工作包。

There is an ongoing need for a capability to run atmospheric models at higher resolution, to improve weather forecasts, particularly of severe weather, to improve understanding of climate processes, and to improve climate prediction. Higher resolution can only be achieved by exploiting future supercomputing platforms based on hundreds of thousand of processors; for such architectures communication between processors is a significant bottleneck to performance, and requires quite different algorithms from those used historically.Grids based on a refined icosahedron provide a promising basis for a new generation of atmospheric models. Their quasi-uniform resolution should minimize the communication bottleneck giving good performance. Recent advances in numerical analysis mean that schemes of sufficient accuracy are now available. Local refinement of the grid is possible where higher resolution is needed for specific applications. An icosahedral grid model has been used operationally by the German Weather Service for several years, and several other groups have such models at an advanced stage of development.The proposed project will assess and compare the parallel computing performance of a number of icosahedral grid models and carry out research to improve their performance. The specific research topics include the development of an abstract model description scheme to separate (as far as possible) numerical analysis issues from computer science issues, a model implementation targeted on Graphical Processing Unit (GPU) based architectures, development and evaluation of elliptic solvers to determine the feasibility of stable long-time-step integration schemes, the development of an internal postprocessing package to provide diagnostics required by the user while minimizing the data output bottleneck, and development of strategies to optimize input/output. The University of Exeter will contribute particularly to the elliptic solver and postprocessing work packages.