Multi-layered abstractions for PDEs

偏微分方程的多层抽象

• 批准号: EP/I00677X/1
• 负责人: Paul Kelly
• 金额: $ 62.67万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FI00677X%2F1
• 关键词: Multi; layered; abstractions; PDEs

Partial differential equations (PDEs) are the mathematical basis ofvast areas of science. From fluid problems such as flow past anaircraft or the circulation of the worlds oceans to structuralproblems in bridges or inside the bones of a body and even in theworld of financial options pricing, PDEs are the key description. Itis therefore unsurprising that computing solutions to PDEs consumes amassive proportion of high performance computing resources in bothindustry and academia.Hitherto, the software which solves PDEs has been written for specificsorts of hardware by people who had to be experts both in the sciencethey were modelling and in programming. This is an expensive anderror-prone process and, because it occurs in an informal way inengineering and science departments, has suffered from a lack of inputfrom modern computer science. However, what makes this proposalcritical for computational science are the large changes which areoccuring in hardware technology. The emergence of new massivelyparallel platforms, such as graphical processing units (GPUs) andmulticore CPU systems is requiring very different approaches tolow-level programming and, importantly, different approaches fordifferent hardware platforms. It also requires new research into thebest optimisation strategies for these platforms. The current approachto writing scientific software will not deliver the changes that arerequired within the industrial and government funding resources available.This project will break this paradigm by using multiple layers ofabstraction to present to scientists and engineers a way ofprogramming PDE problems which is independent of the hardware and tocomputer scientists, a program generation space in which they cangenerate optimal algorithms for PDEs on different hardware platformswithout becoming embroiled in domain science. In particular, we willdevelop a hardware abstraction layer (OP2) which will allow programsto be written by explicitly stating what is parallel. The OP2 layersoftware will then translate this into low-level code which utilisesthe parallelism in a particular hardware platform. For developersworking with the finite element method (FEM), an importantcomputational technique for PDEs, we will present an additional layerwhich will enable them to write the finite element problem in a highlevel language, UFL. This will then be translated to OP2 and thencedown to the hardware layer.We will demonstrate the effectiveness of this approach with two PhDprojects. One will look into the dispersion of polutants in urbansettings while the other will study the stress properties of surgicalbone implants. These are both important scientific questions whichcurrently suffer from a lack of resolution and therefore need to beable to employ the latest high performance hardware.

偏微分方程是众多科学领域的数学基础。从流体问题，如流过飞机或世界海洋的循环，到桥梁或身体骨骼内部的结构问题，甚至在金融期权定价领域，偏微分方程都是关键描述。因此，解决偏微分方程的计算方案在工业界和学术界都消耗了大量的高性能计算资源，这并不奇怪。然而，解决偏微分方程的软件是由那些必须是建模和编程科学专家的人为特定种类的硬件编写的。这是一个昂贵且容易出错的过程，而且由于它以非正式的方式发生在工程和科学部门，因此缺乏现代计算机科学的输入。然而，是什么让这个命题对计算科学至关重要的是发生在硬件技术的巨大变化。新的并行平台的出现，如图形处理单元（GPU）和多核CPU系统，要求采用非常不同的方法来进行低级编程，重要的是，不同的硬件平台需要不同的方法。它还需要对这些平台的最佳优化策略进行新的研究。目前编写科学软件的方法将无法在工业和政府可用的资金资源范围内提供所需的变化。该项目将通过使用多层抽象来打破这种范式，向科学家和工程师提供一种编程PDE问题的方法，这种方法独立于硬件和计算机科学家，一个程序生成空间，在这个空间中，他们可以在不同的硬件平台上为偏微分方程生成最佳算法，而不会卷入领域科学。特别是，我们将开发一个硬件抽象层（OP2），它将允许程序通过明确说明什么是并行来编写。然后OP2层软件将其转换为低级代码，该代码利用特定硬件平台中的并行性。对于使用有限元方法（FEM）（PDE的一种重要计算技术）的开发人员，我们将提供一个额外的层，使他们能够用高级语言UFL编写有限元问题。这将被转换到OP2，然后再转换到硬件层。我们将通过两个博士项目来证明这种方法的有效性。一个将研究污染物在城市环境中的扩散，另一个将研究骨植入物的应力特性。这些都是重要的科学问题，目前缺乏解决方案，因此需要能够采用最新的高性能硬件。

项目成果

OP2-Clang: A Source-to-Source Translator Using Clang/LLVM LibTooling

OP2-Clang：使用 Clang/LLVM LibTooling 的源到源转换器

• DOI: 10.1109/llvm-hpc.2018.8639205
• 发表时间: 2018
• 作者: Balogh G

Languages and Compilers for Parallel Computing

用于并行计算的语言和编译器

• DOI: 10.1007/978-3-540-85261-2_12
• 发表时间: 2008
• 作者: Cornwall J

Mesh independent loop fusion for unstructured mesh applications

适用于非结构化网格应用的网格独立循环融合

• DOI: 10.1145/2212908.2212917
• 发表时间: 2012
• 作者: Bertolli C

Performance Analysis and Optimization of the OP2 Framework on Many-Core Architectures

OP2框架在众核架构上的性能分析与优化

• DOI: 10.1093/comjnl/bxr062
• 发表时间: 2011
• 期刊: The Computer Journal
• 作者: Giles M

From h to p efficiently: Strategy selection for operator evaluation on hexahedral and tetrahedral elements

• DOI: 10.1016/j.compfluid.2010.08.012
• 发表时间: 2011-04-01
• 期刊: COMPUTERS & FLUIDS
• 影响因子: 2.8
• 作者: Cantwell, C. D.;Sherwin, S. J.;Kelly, P. H. J.
• 通讯作者: Kelly, P. H. J.