Solution of Multi-Physics Flow Problems in Performance Portable Frameworks

计算流体动力学（CFD）已经成为高性能计算（HPC）所瞄准的最重要的应用类别之一。在高性能计算中使用CFD是出于解决具有挑战性的多物理场问题的需要。航空航天、核电、石油和天然气等行业经常大规模使用这些代码，需要灵活地调整计算以适应特定问题。随着近年来摩尔定律的收益递减，加速器，特别是gpu，已经成为提高应用程序性能的重要技术。加速器现在可以在许多顶级超级计算机中找到，包括Summit （ORNL）和Sierra （LLNL）以及欧洲的Piz paint（苏黎世联邦理工学院）。加速器的使用引起了编程复杂性和性能可移植性方面的关注。这在已经拥有针对cpu优化的大型已建立的生产代码库的CFD应用程序中更加明显。此外，过去的算法选择，如低阶隐式方法和非结构化网格数据布局，导致需要大量的努力来适应现有的软件，以适应日益异构的计算机体系结构。为了应对这些挑战，人们正在积极开发新的算法、编程范式和框架，努力创建一个更灵活的未来软件生态系统。近年来出现的一项潜在的颠覆性技术是领域特定语言（dsl），它可以为结构化或非结构化网格操作提供高效的代码生成。dsl的设计目的是提供高级抽象，其中包含一组指令和定义良好的语义，工程师或科学家可以使用这些指令和语义快速定义他们的模型。它们充当构建块，隐藏特定架构的模板和实现细节。华威大学与牛津大学、匈牙利PPCU和伦敦帝国理工学院合作，在dsl的性能可移植性方面做出了重要贡献。戴尔斯伯里实验室的IBM研究小组正在与几个利用HPC的英国行业合作，帮助他们充分利用不断发展的硬件和软件堆栈。基于当前计算机建模的局限性，IBM-R有兴趣构建一个流求解器的原型实现，作为新算法和灵活数据结构的测试平台。Warwick和IBM-R过去曾合作过，双方都致力于将DSL方法提升到一个新的水平。通过与IBM研究院的合作，该项目将致力于开发对多材料加速器友好的算法，并创建用户友好的抽象，以便在DSL中演示它们，从而使其得到更广泛的采用。这些算法将需要持续地暴露更多的计算，这是加速器擅长的，同时减少数据的移动和集体操作的数量，这是许多异构系统的主要瓶颈。作为该项目的一部分，学生将在IBM实习。

Computational fluid dynamics (CFD) has been one of the most important classes of applications targeted by high-performance computing (HPC). Use of CFD in HPC is motivated by the need for solving challenging multi-physics problems. Industries such as aerospace, nuclear power, oil and gas regularly employ these codes at scale requiring flexibility to adapt the computations to a specific problem.With diminishing returns from Moore's Law in recent years, accelerators, in particular GPUs, have become an important technology to boost application performance. Accelerators can now be found in many top-tier supercomputers, including Summit (ORNL) and Sierra (LLNL) as well as Europe's Piz Daint (ETH Zurich). The use of accelerators raises concerns in terms of programming complexity and performance portability. This is even more noticeable in CFD applications that already have large established production code bases optimized for CPUs. Moreover, algorithmic choices made in the past, such as low order implicit methods and unstructured mesh data-layouts, lead to a substantial effort being required to adapt existing software to increasingly heterogeneous computer architectures. To address these challenges new algorithms, programming paradigms and frameworks are being actively developed in the effort to create a more flexible software ecosystem of the future.A potentially disruptive technology that has emerged in recent years are domain-specific languages (DSLs) that enable efficient code generation for structured or unstructured mesh operations. DSLs are designed to provide a high-level abstraction with a set of directives and well-defined semantics that the engineer or scientist can use to quickly define their model. They serve as a building block, hiding boiler plate and implementation details for specific architectures. Warwick University in collaboration with the University of Oxford, PPCU Hungary and Imperial College London have made important contributions in performance portability with DSLs in the past.IBM Research group at Daresbury Laboratory is working with several UK industries that leverage HPC, helping them to take full advantage of constantly evolving hardware and software stacks. Based on the current limitations in computer modelling, IBM-R is interested to build a prototype implementation of a flow solver that would serve as a testbed for novel algorithms and flexible data structures. Warwick and IBM-R have worked together in the past and both are committed to taking the DSL approach to the next level. In collaboration with IBM Research, this project will target the development of multi-material accelerator-friendly algorithms and the creation of user-friendly abstractions to demonstrate them in a DSL in order to enable wider adoption. These algorithms will need to consistently expose more compute, which accelerators excel at, while reducing the movement of data and amount of collective operations which are the main bottleneck in many heterogeneous systems. As part of this project, the student will undertake a placement at IBM.