SDCI HPC Improvement: Cactus Tools for Application Level Performance and Correctness Analysis (ALPACA)

SDCI HPC 改进：用于应用程序级性能和正确性分析的 Cactus 工具 (ALPACA)

• 批准号: 0721915
• 负责人: Peter Diener
• 金额: --
• 依托单位: Louisiana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0721915&HistoricalAwards=false
• 关键词: SDCI; HPC; Improvement; Cactus; Tools

Although the speed and performance of high end computers have increased dramatically over the last decade, the ease of programming such parallel computers has not progressed. The time and effort required to develop and debug scientific software has become the bottleneck in many areas of science and engineering. The difficulty of developing high-performance software is recognized as one of the most significant challenges today in the effective use of large scale computers.The Cactus framework for science applications has been developed over the last several years,tosimulate physical systems in many fields of science, such as black holes and neutron stars in general relativity. As in other software frameworks, applications are built from separately developed and tested components. The project SDCI HPC Improvement: Cactus Tools for Application Level Performance and Correctness Analysis (ALPACA) will provide high-level tools to allow developers and end-users to examine and validate the correctness of an application, and aid them in measuring and improving its performance in production environments. These tools will be components themselves, built into the application and interacting with it. The developed software will also help render applications tolerant against partial system failures, which is becoming a pressing need with tomorrow?s architectures consisting of hundreds of thousands of nodes. In contrast to existing debuggers and profilers, the ALPACA tools will work at a much higher level, at the level of the physical equations and their discretisations which are implemented by the application, not at the level of individual lines of code or variables. It is not enough for only the main kernels to be correct and show good scalability; the overall application ? which may contain many smaller modules ? must perform. Our integrative effort will lead to well-tested and highly efficient applications which are developed in a shorter time scale and execute more reliably. By providing interactive debugging abilities at the application level in production environments,and by allowing interactive experimentation at the algorithmic level on large HPC systems, the ALPACA tools will significantly reduce the time and effort required to take the steps from using isolated application components on single workstations to performing large-scale HPC calculations.The ALPACA tools will be developed in close conjunction with scientists from several scientific communities, ensuring their direct usefulness and applicability to real-world problems.Intellectual Merit: The issues addressed by ALPACA are critically important for the success ofHPC systems at all scales, and ALPACA tools will be highly valuable for algorithm development, performance analysis, and software engineering in many fields of science. The LSU group has beena leader in developing application level HPC tools, including the Cactus framework, in developing algorithms for adaptive scalability in HPC and distributed HPC environments, and in developing applications themselves; it is a world leader in applying HPC as a tool to solve Einstein?s equations.The ALPACA project simultaneously addresses problems in physics and computational science,and will provide scientists with radically improved tools to help them bringing their problems to the machine.Broader Impacts: ALPACA fundamentally involves several application areas important to NSF, and will impact many others. ALPACA has the potential to make a huge contribution to computational science by providing a software infrastructure that enables developers and users to create scalable applications and to use them in a correct and efficent manner. Through this tools, we expect groups to concentrate more on physics and numerics, and less on computational details in an ever more complex computing environment. At the same time, many other communities are emerging to solve complex problems, and our ideas and techniques, designed to help HPC software development in any disciplines, will have impact across many of these projects. The ALPACAtools will thus naturally spread out into the communities. This proposal includes a training workshop and the training of a postdoc and a graduate student.

虽然高端计算机的速度和性能在过去十年中显著提高，但编程这种并行计算机的容易性没有进步。开发和调试科学软件所需的时间和精力已经成为许多科学和工程领域的瓶颈。开发高性能软件的困难被认为是当今有效使用大规模计算机的最大挑战之一，Cactus框架在过去几年中已经发展起来，用于模拟许多科学领域的物理系统，例如广义相对论中的黑洞和中子星。与其他软件框架一样，应用程序是由单独开发和测试的组件构建的。SDCI HPC Improvement：Cactus Tools for Application Level Performance and Correctness Analysis（ALPACA）项目将提供高级工具，允许开发人员和最终用户检查和验证应用程序的正确性，并帮助他们测量和改进其在生产环境中的性能。这些工具本身将是组件，内置于应用程序中并与之交互。开发的软件还将有助于使应用程序能够容忍部分系统故障，这将成为未来的迫切需求。的体系结构，由数十万个节点组成。与现有的调试器和分析器相比，ALPACA工具将在更高的级别上工作，在应用程序实现的物理方程及其离散化的级别上，而不是在单个代码行或变量的级别上。仅仅主内核是正确的并显示出良好的可扩展性是不够的;整个应用程序？它可以包含许多更小的模块？必须执行。我们的综合努力将导致良好的测试和高效的应用程序，在较短的时间内开发和执行更可靠。通过在生产环境中提供应用程序级别的交互式调试能力，并允许在大型HPC系统上进行算法级别的交互式实验，ALPACA工具将大大减少从在单个工作站上使用独立的应用程序组件到执行大型大规模HPC计算。ALPACA工具将与来自多个科学团体的科学家密切合作开发，确保其对现实世界问题的直接有用性和适用性。ALPACA解决的问题对于HPC系统在所有规模上的成功至关重要，ALPACA工具对于许多科学领域的算法开发，性能分析和软件工程都具有很高的价值。LSU集团在开发应用级HPC工具（包括Cactus框架）、开发HPC和分布式HPC环境中的自适应可扩展性算法以及开发应用程序本身方面一直处于领先地位;在将HPC应用为解决爱因斯坦？ALPACA项目同时解决物理学和计算科学中的问题，并将为科学家提供彻底改进的工具，帮助他们将问题带到机器上。更广泛的影响：ALPACA从根本上涉及对NSF重要的几个应用领域，并将影响许多其他领域。ALPACA有潜力为计算科学做出巨大贡献，它提供了一个软件基础设施，使开发人员和用户能够创建可扩展的应用程序，并以正确有效的方式使用它们。通过这些工具，我们希望团队能够更多地关注物理和数值，而不是在越来越复杂的计算环境中关注计算细节。与此同时，许多其他社区正在出现，以解决复杂的问题，我们的想法和技术，旨在帮助任何学科的HPC软件开发，将在许多这些项目的影响。因此，ALPACA工具将自然地传播到社区。这项建议包括一个培训讲习班和培训一名博士后和一名研究生。