A scalable dynamical core for Next Generation Weather and Climate Prediction - Phase 2

下一代天气和气候预测的可扩展动力核心 - 第 2 阶段

• 批准号: NE/K006770/1
• 负责人: Graham Riley
• 金额: $ 6.2万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FK006770%2F1
• 关键词: scalable; dynamical; core; Next; Generation

Historically, major improvements in the accuracy of numerical weather forecasts and climate simulations have come from the increased resolution enabled by the exponential growth in computer power. In order to achieve further gains in accuracy through further increases in resolution, it will be necessary to exploit the massively parallel computer architectures that are becoming available. However, current state-of-the-art operational algorithms are not expected to perform well beyond a few thousand processors: the grid structure of the traditional latitude-longitude grid means that interprocessor communication eventually but inevitably becomes a bottleneck.The overall aim of the proposed project is to develop a new, three-dimensional, fully compressible dynamical core suitable for operational global and regional weather and climate prediction, as well as for research use, on massively parallel machines, and to demonstrate its accuracy, efficiency, and scalability. The accuracy should be comparable to that of existing state of the art algorithms. The algorithm must be efficient enough to run in the available operational time slots, and it must scale well on 100,000 to 1000,000 processors.Phase 1 of this project (Feb 2011 - Jan 2013) addressed several of the basic scientific questions that underpin the development, including choice of quasi-uniform horizontal grid, choice of horizontal discretization, choice of transport scheme, time integration scheme, and some of the computer science aspects of the project. Several candidate approaches were tested and evaluated in a simplified two-dimensional fluid system (the Shallow Water Equations), and a small number of promising approaches were identified for further development in Phase 2.Phase 2 of this project will build on the progress made in Phase 1 in order to develop a three-dimensional, fully compressible dynamical core. The work in Phase 2 falls broadly into three work packages:* Vertical aspects. The stability and accuracy of the discretization depends crucially on the choice of vertical coordinate, the choice of thermodynamic variables predicted, and the vertical placement of variables relative to each other (`staggering'). It will also depend on the details of how, for example, the pressure gradient term is evaluated, especially near steep mountains, and how the vertical discretization couples with the horizontal discretization. Building on current understanding, candidate schemes will be formulated and tested.* Code design and development. The code for the three-dimensional dynamical core will be based around a carefully designed software framework. The interface between the numerical discretization and its parallel implementation will be optimized, so that modifications to the former require minimal knowledge of the latter. The software framework will be highly flexible, so that it can easily accommodate future evolution of the dynamical core, such as changes in grid structure.* Testing. The behaviour of complex numerical algorithms can be difficult to predict theoretically, even when individual components are well understood and tested. It will be vital, therefore, to test comprehensively the proposed formulations at the earliest opportunity, and revise if necessary. Early testing will focus on the shallow water formulation arising out of Phase 1 of the project, and on one-dimensional (column) and two-dimensional (vertical slice) prototypes of the vertical formulation. Testing of the three-dimensional formulation will begin as soon as code is available.

从历史上看，数值天气预报和气候模拟准确性的主要改进来自计算机能力指数增长所带来的分辨率提高。为了通过进一步提高分辨率来进一步提高精度，有必要利用正在变得可用的大规模并行计算机体系结构。然而，目前最先进的运算算法预计不会在几千个处理器以上执行得很好：传统经纬度网格的网格结构意味着处理器间的通信最终但不可避免地成为瓶颈。拟议项目的总体目标是开发一种新的、三维的、完全可压缩的动力核心，适用于业务性的全球和区域天气和气候预测，以及用于研究，在大规模并行机上，并证明其准确性，效率和可扩展性。准确度应与现有最先进算法的准确度相当。该算法必须足够高效，能够在可用的操作时间段内运行，并且必须在100，000到1000，000个处理器上具有良好的扩展性。（2011年2月-2013年1月）解决了支持开发的几个基本科学问题，包括准均匀水平网格的选择，水平离散化的选择，运输方案的选择，时间积分方案，以及该项目的一些计算机科学方面。在简化的二维流体系统（浅水方程）中测试和评估了几种候选方法，并确定了少数有前途的方法，以在第2阶段中进一步发展。该项目的第2阶段将建立在第1阶段所取得的进展的基础上，以开发一个三维的，完全可压缩的动力核心。第二阶段的工作福尔斯大致分为三个工作包：离散化的稳定性和准确性关键取决于垂直坐标的选择、预测的热力学变量的选择以及变量相对于彼此的垂直位置（“交错”）。它还取决于如何评估压力梯度项的细节，特别是在陡峭的山脉附近，以及垂直离散化如何与水平离散化耦合。在现有认识的基础上，将制定和测试候选方案。代码设计和开发。三维动力核心的代码将基于精心设计的软件框架。将优化数值离散化及其并行实施之间的接口，以便对前者进行修改只需要对后者了解最少。软件框架将具有高度的灵活性，因此它可以很容易地适应动态核心的未来发展，例如网格结构的变化。试验.复杂的数值算法的行为可能很难从理论上预测，即使在很好地理解和测试单个组件时也是如此。因此，至关重要的是尽早全面测试拟议的方案，并在必要时加以修订。早期测试将侧重于项目第1阶段产生的浅水配方，以及垂直配方的一维（柱）和二维（垂直切片）原型。一旦代码可用，将开始对三维制剂进行检测。

项目成果

Sharing experiences and outlook on Coupling Technologies for Earth System Models

• DOI: 10.1175/bams-d-15-00239.1
• 发表时间: 2016-04
• 期刊: Bulletin of the American Meteorological Society
• 影响因子: 8
• 作者: S. Valcke;A. Craig;R. Dunlap;G. Riley

The development of a data-driven application benchmarking approach to performance modelling

开发数据驱动的应用程序性能建模基准测试方法

• DOI: 10.1109/hpcsim.2014.6903760
• 发表时间: 2014
• 作者: Osprey A

A Benchmark-Driven Modelling Approach For Evaluating Deployment Choices On A Multi-Core Architecture

用于评估多核架构上的部署选择的基准驱动建模方法

• 发表时间: 2013
• 期刊: The 19th International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2013)
• 作者: Osprey, A

Towards Compiler-Agnostic Performance in Finite-Difference Codes

实现有限差分代码中与编译器无关的性能

• 发表时间: 2015
• 作者: Porter, AR

First Steps in Porting the LFRic Weather and Climate Model to the FPGAs of the EuroExa Architecture

将 LFRic 天气和气候模型移植到 EuroExa 架构 FPGA 的第一步

• DOI: 10.1155/2019/7807860
• 发表时间: 2019
• 期刊: Scientific Programming
• 作者: Ashworth M