Abstracting the environment: automating geoscientific simulation

抽象环境：自动化地球科学模拟

• 批准号: NE/K008951/1
• 负责人: David Ham
• 金额: $ 63.91万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 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%2FK008951%2F1
• 关键词: Abstracting; environment; automating; geoscientific; simulation

This project will deliver a revolutionary increase in the ability ofgeoscientists to implement computer simulations, especially foremerging parallel hardware, and to work with the results of simulations.Computer simulation of processes in the Earth system has become one ofthe key tools if science. In the atmosphere and ocean and from frozenice sheets to the molten rock of the Earth's mantle, simulations offluids and solids are ubiquitous and essential tools. These arecritical processes: many of the world's largest computers are engagedin simulating them.The numerical methods used to produce these models are becomingrapidly more sophisticated. At the same time the emergence ofmassively parallel computer hardware presents the opportunity forunprecedented levels of resolution. However, the complexity of thenumerics and the new hardware is such that it is becoming verydifficult for researchers to write computer code which is correct,sufficiently high performance and sufficiently usable. Conventionalsoftware development essentially requires superhuman developers whoare simultaneously geoscientists, mathematicians and computerscientists.In essence these difficulties occur because conventional computer codemixes the numerics and the parallel implementation. Instead, modelscould be developed by specifying the numerical methods in a high-levelcomputer language similar to the maths, and the parallelimplementation could be generated automatically. This would enableexperts in numerical modelling to specify their algorithm, and arriveat correct, parallel code at a tiny fraction of current developmentcosts. This automatic generation of models is a reality today for scientistsand engineers working on smaller-scale and simplified simulationproblems. However the curvature of the earth, the extreme flatness ofgeophysical domains and the scale of the domains involved mean thatgeoscientists have additional needs which require deep changes insimulation code generation systems. I will extend code generationtechniques to meet these special challenges, and therefore deliverautomation to geoscientific model development.Much science does not just depend on simulating processes: it alsodepends on studying the sensitivity of systems, optimising inputs andparameters, stability analysis and error analysis. All of theseprocesses require an adjoint model: essentially the gradient of theoriginal simulation. Developing adjoint models is so complex that onlythe largest national centres can typically afford to developthem. Using code generation, I have already demonstrated that this canbe made almost automatic for some types of model. I will extend thiscapability to other discretisations which are more common in thegeosciences, and thereby put the powerful tool that adjoints are intothe hands of the individual scientists and students who conduct muchof the cutting edge geoscience.The largest simulations, particularly of the climate system, produceso much complex data that much important science occurs by studyingthe output of archived simulations. For large collections of data frommany models, even the process of calculating statistics is labouriousand error-prone. It is also currently impossible to verify ifpublished data analyses are correctly calculated. I will extend theautomated generation of simulation software to allow for an automateddata query language. This make this form of data science far less labour-intensive, will allow data science with properly published methods, will reduce sources of error and will allow scientists to work effectively with the massive data sets of the future.

该项目将革命性地提高地球科学家实施计算机模拟（特别是新兴并行硬件）以及处理模拟结果的能力。地球系统过程的计算机模拟已成为科学的关键工具之一。在大气和海洋中，从冰原到地幔的熔岩，流体和固体的模拟是无处不在且必不可少的工具。这些都是关键过程：世界上许多最大的计算机都在模拟它们。用于生成这些模型的数值方法正在迅速变得更加复杂。与此同时，大规模并行计算机硬件的出现为实现前所未有的分辨率水平提供了机会。然而，数值和新硬件的复杂性使得研究人员编写正确的、足够高性能和足够可用的计算机代码变得非常困难。传统的软件开发本质上需要超人的开发人员，他们同时是地球科学家、数学家和计算机科学家。本质上，这些困难的发生是因为传统的计算机代码混合了数字和并行实现。相反，可以通过用类似于数学的高级计算机语言指定数值方法来开发模型，并且可以自动生成并行实现。这将使数值建模专家能够指定他们的算法，并以当前开发成本的一小部分来获得正确的并行代码。如今，对于处理较小规模和简化模拟问题的科学家和工程师来说，自动生成模型已成为现实。然而，地球的曲率、地球物理领域的极端平坦度以及所涉及领域的规模意味着地球科学家有额外的需求，需要对模拟代码生成系统进行深入的改变。我将扩展代码生成技术来应对这些特殊挑战，从而为地球科学模型开发提供自动化。许多科学不仅仅依赖于模拟过程：它还依赖于研究系统的敏感性、优化输入和参数、稳定性分析和误差分析。所有这些过程都需要一个伴随模型：本质上是原始模拟的梯度。开发伴随模型非常复杂，通常只有最大的国家中心才有能力开发它们。通过使用代码生成，我已经证明对于某些类型的模型来说，这几乎可以自动化。我将把这种能力扩展到地球科学中更常见的其他离散化，从而将伴随物的强大工具交到进行大部分前沿地球科学的科学家和学生手中。最大的模拟，特别是气候系统，会产生如此多的复杂数据，以至于通过研究存档模拟的输出来产生许多重要的科学。对于来自许多模型的大量数据集合，即使是计算统计数据的过程也是费力且容易出错的。目前也无法验证已发布的数据分析是否计算正确。我将扩展模拟软件的自动生成，以允许自动数据查询语言。这使得这种形式的数据科学的劳动密集度大大降低，将使数据科学能够采用正确发布的方法，减少错误来源，并使科学家能够有效地处理未来的海量数据集。

项目成果

TSFC: a structure-preserving form compiler

• DOI: 10.1137/17m1130642
• 发表时间: 2017-05
• 期刊: SIAM J. Sci. Comput.
• 作者: Miklós Homolya;L. Mitchell;F. Luporini;D. Ham

A Parallel Edge Orientation Algorithm for Quadrilateral Meshes

四边形网格的平行边方向算法

• DOI: 10.1137/15m1021325
• 发表时间: 2016
• 期刊: SIAM Journal on Scientific Computing
• 影响因子: 3.1
• 作者: Homolya M

On-the-Fly Data Synopses Efficient Data Exploration in the Simulation Sciences

动态数据概要模拟科学中的高效数据探索

• DOI: 10.1145/2814710.2814715
• 发表时间: 2015
• 期刊: ACM SIGMOD Record
• 作者: Heinis T

Automated shape differentiation in the Unified Form Language

• DOI: 10.1007/s00158-019-02281-z
• 发表时间: 2019-11-01
• 期刊: STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
• 影响因子: 3.9
• 作者: Ham, David A.;Mitchell, Lawrence;Wechsung, Florian
• 通讯作者: Wechsung, Florian

Modelling of Nonlinear Wave-Buoy Dynamics Using Constrained Variational Methods

使用约束变分方法进行非线性波浪浮标动力学建模

• DOI: 10.1115/omae2017-61966
• 发表时间: 2017
• 作者: Kalogirou A