Collaborative Research: SI2-SSE: WRENCH: A Simulation Workbench for Scientific Worflow Users, Developers, and Researchers

协作研究：SI2-SSE：WRENCH：面向科学 Worflow 用户、开发人员和研究人员的模拟工作台

• 批准号: 1642369
• 负责人: Henri Casanova
• 金额: $ 25.8万
• 依托单位: University of Hawaii
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1642369&HistoricalAwards=false
• 关键词: Collaborative; Research; SI2; SSE; WRENCH

Many scientific breakthroughs can only be achieved by performing complex processing of vast amounts of data efficiently. In domains as crucial to our society as climate modeling, oceanography, particle physics, seismology, or computational biology (and in fact in most fields of physics, chemistry, and biology today), scientists nowadays routinely define "scientific workflows". These workflows are complex descriptions of scientific processes as data and inter-dependent computations on these data. When executed, typically with great expenses of computing, storage, and networking hardware, these workflows can produce groundbreaking results. A famous and recent example is the workflow that was used as part of the LIGO project to confirm the first detection of gravitational waves from colliding black holes. Scientific workflows are mainstays in today's science. Their efficient execution (in terms of speed, reliability, and cost) is thus crucial. This project seeks to provide a software framework, called WRENCH (Workflow Simulation Workbench), that will make it possible to simulate large-scale hypothetical scenarios quickly and accurately on a single computer, obviating the need for expensive and time-consuming trial and error experiments. WRENCH potentially enables scientists to make quick and informed choices when executing their workflows, software developers to implement more efficient software infrastructures to support workflows, and researchers to develop novel efficient algorithms to be embedded within these software infrastructures. In addition, WRENCH makes it possible to bring scientific workflow content into undergraduate and graduate computer science curricula. This is because meaningful knowledge can be gained by students using a single computer and the WRENCH software stack, making such learning possible even at institutions without access to high-end computing infrastructures, such as many non-Ph.D.-granting and minority-serving institutions. As a result, this work will contribute to producing computer science graduates better equipped to take an active role in the advancing of science. Due to its potentially transformative impact on scientific workflow usage, development, research, and education, this project promises to promote the progress of science across virtually all its fields, ultimately resulting in broad and numerous benefits to our society.Scientific workflows have become mainstream for conducting large-scale scientific research. As a result, many workflow applications and Workflow Management Systems (WMSs) have been developed as part of the cyberinfrastructure to allow scientists to execute their applications seamlessly on a range of distributed platforms. In spite of many success stories, building large-scale workflows and orchestrating their executions efficiently (in terms of performance, reliability, and cost) remains a challenge given the complexity of the workflows themselves and the complexity of the underlying execution platforms. A fundamental necessary next step is the establishment of a solid "experimental science" approach for future workflow technology development. Such an approach is useful for scientists who need to design workflows and pick execution platforms, for WMS developers who need to compare alternate design and implementation options, and for researchers who need to develop novel decision-making algorithms to be implemented as part of WMSs. The broad objective of this work is to provide foundational software, the Workflow Simulation Workbench (WRENCH), upon which to develop the above experimental science approach. Capitalizing on recent advances in distributed application and platform simulation technology, WRENCH makes it possible to (i) quickly prototype workflow, WMS implementations, and decision-making algorithms; and (ii) evaluate/compare alternative options scalably and accurately for arbitrary, and often hypothetical, experimental scenarios. This project will define a generic and foundational software architecture, that is informed by current state-of-the-art WMS designs and planned future designs. The implementation of the components in this architecture when taken together form a generic "scientific instrument" that can be used by workflow users, developers, and researchers. This scientific instrument will be instantiated for several real-world WMSs and used for a range of real-world workflow applications. In a particular case-study, it will be used with a popular WMS (Pegasus) to revisit published results and scheduling algorithms in the area of workflow planning optimizations. The objective is to demonstrate the benefit of using an experimental science approach for WMS research. Another impact of this project is that it makes it possible to include scientific workflow content pervasively in undergraduate and graduate computer science curricula, even for students without any access to computing infrastructure, by defining meaningful pedagogic activities that only require a computer and the WRENCH software stack. This educational impact will be demonstrated in the classroom in both undergraduate and graduate courses at our institutions.

许多科学突破只能通过有效地对大量数据进行复杂处理才能实现。 在气候建模、海洋学、粒子物理学、地震学或计算生物学等对我们社会至关重要的领域（事实上在当今物理、化学和生物学的大多数领域），科学家们现在通常会定义“科学工作流程”。这些工作流程是将科学过程复杂地描述为数据以及对这些数据的相互依赖的计算。当执行时，通常需要花费大量的计算、存储和网络硬件费用，这些工​​作流程可以产生突破性的结果。最近一个著名的例子是 LIGO 项目的工作流程，该项目用于确认首次检测到来自碰撞黑洞的引力波。科学工作流程是当今科学的支柱。因此，它们的高效执行（在速度、可靠性和成本方面）至关重要。该项目旨在提供一个名为 WRENCH（工作流模拟工作台）的软件框架，使在单台计算机上快速准确地模拟大规模假设场景成为可能，从而避免进行昂贵且耗时的试错实验。 WRENCH 可能使科学家在执行工作流程时做出快速、明智的选择，使软件开发人员能够实施更高效的软件基础设施来支持工作流程，并使研究人员能够开发嵌入这些软件基础设施中的新型高效算法。 此外，WRENCH 还可以将科学工作流程内容引入本科生和研究生计算机科学课程。这是因为学生可以使用单台计算机和 WRENCH 软件堆栈获得有意义的知识，即使在无法访问高端计算基础设施的机构（例如许多非博士学位授予者和少数族裔）也可以进行此类学习。服务机构。因此，这项工作将有助于培养计算机科学毕业生更好地在科学进步中发挥积极作用。 由于其对科学工作流程的使用、开发、研究和教育具有潜在的变革性影响，该项目有望促进几乎所有领域的科学进步，最终为我们的社会带来广泛而众多的利益。科学工作流程已成为主流开展大规模科学研究。 因此，许多工作流应用程序和工作流管理系统 (WMS) 已被开发为网络基础设施的一部分，使科学家能够在一系列分布式平台上无缝执行其应用程序。 尽管有许多成功案例，但鉴于工作流本身的复杂性以及底层执行平台的复杂性，构建大规模工作流并有效地编排其执行（在性能、可靠性和成本方面）仍然是一个挑战。 下一步的基本必要步骤是为未来工作流技术的开发建立可靠的“实验科学”方法。这种方法对于需要设计工作流程和选择执行平台的科学家、需要比较替代设计和实现选项的 WMS 开发人员以及需要开发作为 WMS 一部分实现的新颖决策算法的研究人员非常有用。 这项工作的主要目标是提供基础软件，即工作流程模拟工作台（WRENCH），在此基础上开发上述实验科学方法。 利用分布式应用程序和平台仿真技术的最新进展，WRENCH 可以 (i) 快速构建工作流程原型、WMS 实施和决策算法； (ii) 针对任意且通常是假设的实验场景，可扩展且准确地评估/比较替代方案。 该项目将定义一个通用的基础软件架构，该架构以当前最先进的 WMS 设计和计划的未来设计为基础。 该架构中组件的实现组合在一起形成了一个通用的“科学仪器”，可供工作流用户、开发人员和研究人员使用。 该科学仪器将针对多个现实世界的 WMS 进行实例化，并用于一系列现实世界的工作流程应用程序。在一个特定的案例研究中，它将与流行的 WMS (Pegasus) 一起使用，以重新审视工作流程规划优化领域已发布的结果和调度算法。目的是证明使用实验科学方法进行 WMS 研究的好处。 该项目的另一个影响是，通过定义只需要计算机和 WRENCH 软件堆栈的有意义的教学活动，即使对于无法访问计算基础设施的学生，也可以将科学工作流程内容普遍纳入本科生和研究生计算机科学课程中。这种教育影响将在我们机构的本科生和研究生课程的课堂上得到体现。

项目成果

Checkpointing Workflows for Fail-Stop Errors

• DOI: 10.1109/cluster.2017.14
• 发表时间: 2017-09
• 期刊: 2017 IEEE International Conference on Cluster Computing (CLUSTER)
• 作者: Li Han;Louis-Claude Canon;H. Casanova;Y. Robert;F. Vivien

WRENCH: Workflow Management System Simulation Workbench

WRENCH：工作流程管理系统模拟工作台

• 发表时间: 2018
• 期刊: Workshop on Workflows in Support of Large-Scale Science
• 作者: Casanova, H;Pandey, S;Oeth, J.;Tanaka, R.;Suter, F.;Ferreira da Silva, R.
• 通讯作者: Ferreira da Silva, R.

Computing the expected makespan of task graphs in the presence of silent errors

在存在无提示错误的情况下计算任务图的预期完工时间

• DOI: 10.1016/j.parco.2018.03.004
• 发表时间: 2018
• 期刊: Parallel Computing
• 影响因子: 1.4
• 作者: Casanova, Henri;Herrmann, Julien;Robert, Yves
• 通讯作者: Robert, Yves

SMPI Courseware: Teaching Distributed-Memory Computing with MPI in Simulation

SMPI 课件：在仿真中使用 MPI 教授分布式内存计算

• 发表时间: 2018
• 期刊: Proceedings of EduHPC
• 作者: Casanova, H.;Quinson, M.;Legrand, A.;Suter, F.
• 通讯作者: Suter, F.

Accurately Simulating Energy Consumption of I/O-Intensive Scientific Workflows

• DOI: 10.1007/978-3-030-22734-0_11
• 发表时间: 2019-06
• 作者: Rafael Ferreira da Silva;Anne-Cécile Orgerie;H. Casanova;Ryan Tanaka;E. Deelman;F. Suter