Collaborative Research: CC-NIE Integration: Transforming Computational Science with ADAMANT (Adaptive Data-Aware Multi-Domain Application Network Topologies)

工作流，特别是数据驱动的工作流和工作流集成正在成为现代计算科学的核心。然而，科学家缺乏将工作流驱动的科学应用的操作集成到动态基础设施之上的工具，这些基础设施将校园、机构和国家资源连接到旨在解决特定问题的连接安排中。这些工具必须(a)根据应用程序需求编排基础设施，(b)通过监控各种工作流步骤并根据应用程序需求修改片段来管理基础设施之上的应用程序生命周期，以及(c)将数据移动与工作流集成以优化性能。项目ADAMANT（自适应数据感知多领域应用网络拓扑）汇集了来自RENCI/UNC教堂山分校，杜克大学和USC/ISI的研究人员和两个成功的软件工具来解决这些问题：为NSF GENI开发的Pegasus工作流管理系统和ORCA资源控制框架。Pegasus和ORCA的集成使强大的应用和数据驱动的虚拟拓扑嵌入到多个机构和国家基板（网络资源提供商，如计算，存储和网络）。ADAMANT利用ExoGENI -一个nsf资助的GENI测试平台，以及国家按需带宽服务提供商（NLR, I2, ESnet）和现有的OSG计算资源来创建弹性，隔离的环境来执行复杂的分布式任务。这种方法提高了这些应用程序的性能，并且通过显式地将数据移动计划包含到应用程序工作流中，为分布式数据驱动的“大科学”应用程序提供了新的独特功能。

Workflows, especially data-driven workflows and workflow ensembles are becoming a centerpiece of modern computational science. However, scientists lack the tools that integrate the operation of workflow-driven science applications on top of dynamic infrastructures that link campus, institutional and national resources into connected arrangements targeted at solving a specific problem. These tools must (a) orchestrate the infrastructure in response to application demands, (b) manage application lifetime on top of the infrastructure by monitoring various workflow steps and modifying slices in response to application demands, and (c) integrate data movement with the workflows to optimize performance. Project ADAMANT (Adaptive Data-Aware Multi-domain Application Network Topologies) brings together researchers from RENCI/UNC Chapel Hill, Duke University and USC/ISI and two successful software tools to solve these problems: Pegasus workflow management system and ORCA resource control framework, developed for NSF GENI. The integration of Pegasus and ORCA enables powerful application- and data-driven virtual topology embedding into multiple institutional and national substrates (providers of cyber-resources, like computation, storage and networks). ADAMANT leverages ExoGENI - an NSF-funded GENI testbed, as well as national providers of on-demand bandwidth services (NLR, I2, ESnet) and existing OSG computational resources to create elastic, isolated environments to execute complex distributed tasks. This approach improves the performance of these applications and, by explicitly including data movement planning into the application workflow, enables new unique capabilities for distributed data-driven "Big Science" applications.