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程序的操作整合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相互关联的安排中。这些工具必须(A)协调基础架构以响应应用程序需求，(B)通过监控各种工作流步骤并根据应用程序需求修改切片来管理基础架构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。Adamant(自适应数据感知多域应用网络拓扑)项目汇集了来自RENCI/UNC Chapel Hill、Duke University和USC/ISI的研究人员以及两个成功的软件工具：Pegasus工作流管理系统和为NSF Geni开发的ORCA资源控制框架。Pegasus和ORCA的集成使强大的应用程序和数据驱动的虚拟拓扑嵌入到多个机构和国家基础(计算、存储和网络等网络资源提供商)中。Adamant利用ExoGENI-一个由NSF资助的Geni试验台，以及按需带宽服务的国家提供商(NLR、I2、ESnet)和现有的OSG计算资源来创建弹性、隔离的环境，以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，并通过明确地将数据移动规划纳入应用程序工作流程，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.