EAGER: Collaborative Research: Using PDE Descriptions to Generate Code Precisely Tailored to Energy-Constrained Systems Including Large GPU Accelerated Clusters

现代计算机系统体系结构迫使计算科学家将科学应用程序从传统的基于同构CPU的系统转移到不同的多核/加速器体系结构。在加速器存在的情况下获得性能需要密切关注内存层次结构和芯片级并行性，才能达到潜在性能的一小部分。因此，曾经只有一门学科的研究生才能完成的编程任务现在需要跨学科的团队来完成。Chemora项目将探索一种新的应用程序框架的设计，以自动为高端计算机器创建高度优化的代码。系统将使用一组描述问题的偏微分方程(PDE)作为输入，然后它将构建特定于机器的抽象性能模型，并使用这些模型为不同规模的加速(例如，混合CPU/GPU)计算集群生成经过良好调整的代码和执行配置。Chemora将通过在高水平上分离科学和计算机科学来提高可编程性，从而降低科学家需要集体理解的复杂性和问题的数量，并允许团队中的个别科学家专注于他们的专业领域。Chemora将通过利用描述问题和机器的详细信息来提高具有简单和复杂方程组的系统的性能(挂钟时间和能量)，并将通过AMPI框架提供改进的负载平衡。Chemora项目选择爱因斯坦方程作为主要的科学驱动因素，因为这些方程是更复杂的PDE系统之一，具有数百个项，并且问题规模对于大多数编译器来说是具有挑战性的优化。对于一个一般的科学问题，实现这一愿景确实是计算科学中的一项“巨大挑战”，但为了使研究更有针对性，该项目将专注于对中等质量比双黑洞(IBBH)系统的模拟。这种系统由一个质量为100到1000个太阳质量的黑洞和一个质量为5到20个太阳质量的较小黑洞组成，有望成为先进激光干涉仪引力波天文台(LIGO)和爱因斯坦望远镜(ET)的重要引力波来源。为了利用模板匹配数据分析技术提取引力波信号，必须对IBBH系统的波形进行精确建模。

Modern computer system architectures are forcing computational scientists to move scientific applications from traditional homogeneous cpu-based systems to heterogeneous multi-core/accelerator architectures. Obtaining performance in the presence of accelerators requires close attention to the memory hierarchy and chip-level parallelism to reach even a modest fraction of the potential performance. As a result, coding tasks which were once the province of lone graduate students in a single discipline now require interdisciplinary teams of people. Project Chemora will explore the design of a new application framework for automatically creating highly optimized code for high-end computational machines. The system will use as input a set of partial differential equations (PDEs) that describe a problem, it will then construct a machine-specific abstract performance model, and using these it will generate well-tuned code and execution configurations for accelerated (e.g., hybrid CPU/GPU) computing clusters at various scales. Chemora will improve programmability by decoupling the science and computer science at a high level, thereby reducing the complexity and number of issues scientists need to collectively understand and allowing individual scientists in the team to focus on their area of specialty. Chemora will improve performance (both wallclock time and energy) for systems with both simple and complex sets of equations by making use of detailed information describing the problem and machine, and will provide improved load balancing through the AMPI framework.The Chemora project has chosen the Einstein equations as the primary science driver because these equations are one of the more complex PDE systems, one with many hundreds of terms, and a problem scale that is challenging to optimize for most compilers. Achieving this vision for a general scientific problem would indeed be a "Grand Challenge" in computational science, but in order to give the research a sharper focus the project will focus on the simulation of Intermediate mass ratio Binary Black Hole (IBBH) systems. Such systems, consisting of a black hole of mass 100 to 1,000 solar masses orbited by a smaller black hole of mass 5 to 20 solar masses are expected to be important sources of gravitational waves for advanced Laser Interferometer Gravitational Wave Observatory (LIGO) and the Einstein Telescope (ET). Accurate modeling of the waveforms from IBBH systems will be necessary in order to extract gravitational wave signals using template-matching data analysis techniques.