CCRI: Planning: Collaborative Research: Infrastructure for Enabling Systematic Development and Research of Scientific Workflow Management Systems

CCRI:规划:协作研究:支持科学工作流程管理系统系统开发和研究的基础设施

基本信息

  • 批准号:
    2016682
  • 负责人:
  • 金额:
    $ 1.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-10-01 至 2021-09-30
  • 项目状态:
    已结题

项目摘要

Scientific workflows are used almost universally across research and engineering disciplines and have underpinned some of the most significant discoveries of the past several decades (e.g., first detection of gravitational waves from colliding black holes, the discovery of the Higgs boson, and the detection of an exotic nuclear decay). Workflow management systems (WMSs) are software systems that provide abstraction and automation for facilitating access to and management of distributed and heterogeneous compute and storage resources. They enable a broad range of researchers to easily define sophisticated computational processes and to then execute them efficiently on parallel and distributed computing platforms. Unfortunately, in spite of widespread adoption of workflows, the technology landscape is segmented and presents significant barriers to entry due to the existence of dozens of seemingly comparable, yet incompatible, systems. The research landscape is also disjoint, making it difficult to compare and contrast approaches, verify and reproduce results, and build upon existing work.This project will engage with representatives from the workflows community – including researchers, developers, science and engineering users, and cyberinfrastructure experts. Through targeted community surveys and focused workshops, the project will gather a diverse set of perspectives, create a community-owned WMS inventory and common knowledge taxonomy, define an experimental methodology for measuring WMS capabilities, and develop a blueprint for a community research infrastructure. This proposed infrastructure has the potential to truly democratize workflows research, enabling researchers, postdocs, and students, irrespective of their institutions, to access cutting-edge infrastructure for comparison, evaluation, and verification of workflows research results.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.
科学工作流程几乎普遍应用于研究和工程学科,并为过去几十年中一些最重大的发现奠定了基础(例如,首次探测到来自碰撞黑洞的引力波,发现了希格斯玻色子,以及探测到了奇异的核衰变)。工作流管理系统(WMS)是提供抽象和自动化以促进对分布式和异类计算和存储资源的访问和管理的软件系统。它们使广泛的研究人员能够轻松地定义复杂的计算过程,然后在并行和分布式计算平台上高效地执行它们。不幸的是,尽管工作流被广泛采用,但由于存在数十个看似可比但却不兼容的系统,技术版图被分割开来,并构成了巨大的进入壁垒。研究领域也是不连续的,这使得比较和对比方法、核实和复制结果以及在现有工作的基础上再接再厉变得困难。该项目将与工作流界的代表接触-包括研究人员、开发人员、科学和工程用户以及网络基础设施专家。通过有针对性的社区调查和有重点的研讨会,该项目将收集一系列不同的观点,创建社区拥有的WMS清单和共同知识分类,定义衡量WMS能力的实验方法,并为社区研究基础设施制定蓝图。这一拟议的基础设施有可能真正实现工作流研究的民主化,使研究人员、博士后和学生能够访问尖端基础设施,以便对工作流研究结果进行比较、评估和验证。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Kyle Chard其他文献

Walking the cost-accuracy tightrope: balancing trade-offs in data-intensive genomics
走成本准确性钢丝:平衡数据密集型基因组学的权衡
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    K. Leung;M. Kimball;Jason Pitt;A. Woodard;Kyle Chard
  • 通讯作者:
    Kyle Chard
GreenFaaS: Maximizing Energy Efficiency of HPC Workloads with FaaS
GreenFaaS:利用 FaaS 最大限度提高 HPC 工作负载的能源效率
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alok V. Kamatar;Valerie Hayot;Y. Babuji;André Bauer;Gourav Rattihalli;Ninad Hogade;D. Milojicic;Kyle Chard;Ian Foster
  • 通讯作者:
    Ian Foster
Enabling real-time multi-messenger astrophysics discoveries with deep learning
利用深度学习实现实时多信使天体物理学发现
  • DOI:
    10.1038/s42254-019-0097-4
  • 发表时间:
    2019-10-03
  • 期刊:
  • 影响因子:
    39.500
  • 作者:
    E. A. Huerta;Gabrielle Allen;Igor Andreoni;Javier M. Antelis;Etienne Bachelet;G. Bruce Berriman;Federica B. Bianco;Rahul Biswas;Matias Carrasco Kind;Kyle Chard;Minsik Cho;Philip S. Cowperthwaite;Zachariah B. Etienne;Maya Fishbach;Francisco Forster;Daniel George;Tom Gibbs;Matthew Graham;William Gropp;Robert Gruendl;Anushri Gupta;Roland Haas;Sarah Habib;Elise Jennings;Margaret W. G. Johnson;Erik Katsavounidis;Daniel S. Katz;Asad Khan;Volodymyr Kindratenko;William T. C. Kramer;Xin Liu;Ashish Mahabal;Zsuzsa Marka;Kenton McHenry;J. M. Miller;Claudia Moreno;M. S. Neubauer;Steve Oberlin;Alexander R. Olivas;Donald Petravick;Adam Rebei;Shawn Rosofsky;Milton Ruiz;Aaron Saxton;Bernard F. Schutz;Alex Schwing;Ed Seidel;Stuart L. Shapiro;Hongyu Shen;Yue Shen;Leo P. Singer;Brigitta M. Sipocz;Lunan Sun;John Towns;Antonios Tsokaros;Wei Wei;Jack Wells;Timothy J. Williams;Jinjun Xiong;Zhizhen Zhao
  • 通讯作者:
    Zhizhen Zhao
Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis
揭示时间性能偏差:在微服务性能分析中利用集群
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    André Bauer;Timo Dittus;Martin Straesser;Alok V. Kamatar;Matt Baughman;Lukas Beierlieb;Marius Hadry;Daniel Grillmeyer;Yannik Lubas;Samuel Kounev;Ian Foster;Kyle Chard
  • 通讯作者:
    Kyle Chard
A terminology for scientific workflow systems
科学工作流系统的术语
  • DOI:
    10.1016/j.future.2025.107974
  • 发表时间:
    2026-01-01
  • 期刊:
  • 影响因子:
    6.100
  • 作者:
    Frédéric Suter;Tainã Coleman;İlkay Altintaş;Rosa M. Badia;Bartosz Balis;Kyle Chard;Iacopo Colonnelli;Ewa Deelman;Paolo Di Tommaso;Thomas Fahringer;Carole Goble;Shantenu Jha;Daniel S. Katz;Johannes Köster;Ulf Leser;Kshitij Mehta;Hilary Oliver;J.-Luc Peterson;Giovanni Pizzi;Loïc Pottier;Rafael Ferreira da Silva
  • 通讯作者:
    Rafael Ferreira da Silva

Kyle Chard的其他文献

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{{ truncateString('Kyle Chard', 18)}}的其他基金

Collaborative Research: Frameworks: Diamond: Democratizing Large Neural Network Model Training for Science
合作研究:框架:钻石:科学大型神经网络模型训练的民主化
  • 批准号:
    2311769
  • 财政年份:
    2023
  • 资助金额:
    $ 1.5万
  • 项目类别:
    Standard Grant
Collaborative Research: REU Site: BigDataX: From theory to practice in Big Data computing at eXtreme scales
合作研究:REU 网站:BigDataX:极限规模大数据计算从理论到实践
  • 批准号:
    2150501
  • 财政年份:
    2022
  • 资助金额:
    $ 1.5万
  • 项目类别:
    Standard Grant
Collaborative Research: Sustainability: A Community-Centered Approach for Supporting and Sustaining Parsl
合作研究:可持续性:以社区为中心的支持和维持 Parsl 的方法
  • 批准号:
    2209919
  • 财政年份:
    2022
  • 资助金额:
    $ 1.5万
  • 项目类别:
    Standard Grant
Frameworks: Collaborative Research: ChronoLog: A High-Performance Storage Infrastructure for Activity and Log Workloads
框架:协作研究:ChronoLog:用于活动和日志工作负载的高性能存储基础架构
  • 批准号:
    2104008
  • 财政年份:
    2021
  • 资助金额:
    $ 1.5万
  • 项目类别:
    Standard Grant
Collaborative Research: OAC Core: Enabling Extremely Fine-grained Parallelism on Modern Many-core Architectures
合作研究:OAC Core:在现代多核架构上实现极其细粒度的并行性
  • 批准号:
    2107283
  • 财政年份:
    2021
  • 资助金额:
    $ 1.5万
  • 项目类别:
    Standard Grant
CSR: Small: Cost-Aware Cloud Profiling, Prediction, and Provisioning as a Service
CSR:小:具有成本意识的云分析、预测和配置即服务
  • 批准号:
    1816611
  • 财政年份:
    2018
  • 资助金额:
    $ 1.5万
  • 项目类别:
    Standard Grant
REU Site: Collaborative Research: BigDataX: From theory to practice in Big Data computing at eXtreme scales
REU 网站:协作研究:BigDataX:极限规模大数据计算从理论到实践
  • 批准号:
    1757970
  • 财政年份:
    2018
  • 资助金额:
    $ 1.5万
  • 项目类别:
    Standard Grant
Collaborative Research: SI2-SSI: Swift/E: Integrating Parallel Scripted Workflow into the Scientific Software Ecosystem
协作研究:SI2-SSI:Swift/E:将并行脚本工作流程集成到科学软件生态系统中
  • 批准号:
    1550588
  • 财政年份:
    2016
  • 资助金额:
    $ 1.5万
  • 项目类别:
    Standard Grant

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