Exploring Cloud Paradigm and Practices for Science and Engineering

探索科学与工程的云范式和实践

• 批准号: 1339036
• 负责人: Manish Parashar
• 金额: $ 30万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-06-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1339036&HistoricalAwards=false
• 关键词: Exploring; Cloud; Paradigm; Practices; Science

Clouds abstractions and infrastructure are rapidly becoming part of the advanced research cyber-infrastructure (ACI) providing viable platforms for scientific exploration and discovery. As a result, it is important to understand how emerging data and compute intensive application workflows can effectively utilize a hybrid ACI integrating Cloud abstractions and services, and how such a hybrid ACI can enable new paradigms and practices in science and engineering. This EAGER explores innovative science and engineering application formulations that are enabled by a hybrid federated ACI that includes Clouds and HPC resources, as well as programming and middleware support for these new application formulations. Specifically, the project focuses on three key research thrusts: (1) application formulation; (2) programming models, abstractions and systems; and (3) middleware stacks and management services, and explore two applications use cases -- (i) an oil reservoir modeling application based on an Ensemble Kalman Filter (EnKF), and (ii) molecular dynamics simulations using asynchronous replica exchange. In each of these use cases activities explore how the capabilities provided by resources and services in a federated ACI can be leveraged to optimize metrics such as time-to-science, cost-to-science and/or energy-to-science.Cloud services are integral to the NSF ACI vision. Clouds are also rapidly becoming an integral part of the ACI available to science and engineering applications, and provide complementary capabilities that can have a significant impact on a range of applications. As a result, this research can have a significant impact on a diverse set of application domains by identifying new paradigms and practices that can make effective use of a hybrid ACI to accelerate science. Furthermore, the results of this research will provide resource providers information about how to best meet the needs of science and engineering applications and how current ACI can achieve broader accessibility and higher efficiencies and productivity. The development of human resources, including the training of students, researchers and software professions, as well as outreach to minorities and underrepresented group, is integral to all aspects of this effort.

云抽象和基础设施正在迅速成为先进研究网络基础设施（ACI）的一部分，为科学探索和发现提供可行的平台。因此，重要的是要了解新兴的数据和计算密集型应用程序工作流如何有效地利用集成云抽象和服务的混合ACI，以及这种混合ACI如何实现科学和工程中的新范式和实践。EAGER探索了创新的科学和工程应用公式，这些公式由混合联邦ACI实现，包括云和HPC资源，以及对这些新应用公式的编程和中间件支持。具体而言，该项目侧重于三个关键研究方向：（1）应用程序制定;（2）编程模型，抽象和系统;（3）中间件堆栈和管理服务，并探索两个应用程序用例-（i）基于EnklemanKalman滤波器（EnKF）的油藏建模应用程序，以及（ii）使用异步副本交换的分子动力学模拟。在每个用例中，活动将探索如何利用联合ACI中的资源和服务提供的功能来优化诸如科学时间、科学成本和/或科学能源等指标。云服务是NSF ACI愿景的组成部分。云也正在迅速成为可用于科学和工程应用的ACI的组成部分，并提供可对一系列应用产生重大影响的补充功能。因此，这项研究可以通过确定新的范例和实践，可以有效地利用一个混合ACI，以加速科学的应用领域的一组不同的显着影响。此外，这项研究的结果将提供有关如何最好地满足科学和工程应用的需求，以及如何当前ACI可以实现更广泛的可访问性和更高的效率和生产力的资源提供商信息。开发人力资源，包括培训学生、研究人员和软件专业人员，以及与少数群体和代表性不足的群体进行外联，是这一努力的所有方面的组成部分。

项目成果

Runtime Management of Data Quality for Scientific Observatories Using Edge and In-Transit Resources

使用边缘和传输中资源对科学观测站的数据质量进行运行时管理

• DOI: 10.1109/sbac-pad.2018.00053
• 发表时间: 2018
• 期刊: 2018 30th International Symposium on Computer Architecture and High Performance Computing
• 作者: Zamani, Ali Reza;Balouek-Thomert, Daniel;Villalobos, J. J.;Rodero, Ivan;Parashar, Manish
• 通讯作者: Parashar, Manish

Persistent Data Staging Services for Data Intensive In-situ Scientific Workflows

适用于数据密集型原位科学工作流程的持久数据暂存服务

• DOI: 10.1145/2912152.2912157
• 发表时间: 2016
• 期刊: Proceedings of the ACM International Workshop on Data-Intensive Distributed Computing
• 作者: Romanus, Melissa;Klasky, Scott;Chang, Choong-Seock;Rodero, Ivan;Zhang, Fan;Jin, Tong;Sun, Qian;Bui, Hoang;Parashar, Manish;Choi, Jong
• 通讯作者: Choi, Jong

Leveraging Renewable Energy in Edge Clouds for Data Stream Analysis in IoT

• DOI: 10.1109/ccgrid.2017.92
• 发表时间: 2017-05
• 期刊: 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
• 作者: Yunbo Li;Anne-Cécile Orgerie;I. Rodero;M. Parashar;Jean-Marc Menaud

An edge-aware autonomic runtime for data streaming and in-transit processing

用于数据流和传输中处理的边缘感知自主运行时

• DOI: 10.1016/j.future.2020.03.037
• 发表时间: 2020
• 期刊: Future Generation Computer Systems
• 作者: Zamani, Ali Reza;Balouek-Thomert, Daniel;Villalobos, J.J.;Rodero, Ivan;Parashar, Manish
• 通讯作者: Parashar, Manish

Submarine: A subscription‐based data streaming framework for integrating large facilities and advanced cyberinfrastructure

Submarine：基于订阅的数据流框架，用于集成大型设施和先进的网络基础设施

• DOI: 10.1002/cpe.5256
• 发表时间: 2019
• 期刊: Concurrency and Computation: Practice and Experience
• 作者: Zamani, Ali Reza;AbdelBaky, Moustafa;Balouek‐Thomert, Daniel;Villalobos, J. J.;Rodero, Ivan;Parashar, Manish
• 通讯作者: Parashar, Manish