CC* Integration: Delivering a Dynamic Network-Centric Platform for Data-Driven Science (DyNamo)

今天的计算科学依赖于许多复杂的、数据密集型的应用程序，这些应用程序对来自各种科学仪器和数据存储的数据集进行操作。数据驱动科学应用的一个主要挑战是将数据集成到科学家的工作流程中。动态、网络化云基础设施的最新进展为构建集成的、可重构的端到端基础设施提供了构建模块，这些基础设施具有提高科学生产力的潜力。然而，应用程序和工作流很少利用这些高级功能。Dynamo将使大气科学家和水文学家能够改进短期和长期天气预报，并帮助海洋学社区改进关键的科学过程，如海洋-大气交换，湍流混合等，这两者都对我们的社会有直接影响。Dynamo项目将开发创新的以网络为中心的算法、策略和机制，以实现从科学数据存储库到国家网络基础设施的高带宽、可配置网络路径的可编程、按需访问，并帮助满足科学工作流程的数据、计算和存储需求。这将使研究人员能够使用实时流数据实时测试新的算法和模型，这在许多科学领域目前是不可能的。通过Pegasus、以网络为中心的平台和新的网络感知工作流调度算法之间的增强交互，科学工作流将受益于工作流自动化和动态配置基础设施上的数据管理。该系统将透明地将应用级、网络服务质量期望映射到可编程软件定义基础设施上的行动。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Computational science today depends on many complex, data-intensive applications operating on datasets that originate from a variety of scientific instruments and data stores. A major challenge for data-driven science applications is the integration of data into the scientist's workflow. Recent advances in dynamic, networked cloud infrastructures provide the building blocks to construct integrated, reconfigurable, end-to-end infrastructure that has the potential to increase scientific productivity. However, applications and workflows have seldom taken advantage of these advanced capabilities.Dynamo will allow atmospheric scientists and hydrologists to improve short- and long-term weather forecasts, and aid the oceanographic community to improve key scientific processes like ocean-atmosphere exchange, turbulent mixing etc., both of which have direct impact on our society. The Dynamo project will develop innovative network-centric algorithms, policies and mechanisms to enable programmable, on-demand access to high-bandwidth, configurable network paths from scientific data repositories to national CyberInfrastructure facilities, and help satisfy data, computational and storage requirements of science workflows. This will enable researchers to test new algorithms and models in real time with live streaming data, which is currently not possible in many scientific domains. Through enhanced interactions between Pegasus, the network-centric platform, and new network-aware workflow scheduling algorithms, science workflows will benefit from workflow automation and data management over dynamically provisioned infrastructure. The system will transparently map application-level, network Quality of Service expectations to actions on programmable software defined infrastructure.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.