Collaborative Research: CNS Core: Large: Systems and Verifiable Metrics for Sustainable Data Centers

合作研究:CNS 核心:大型:可持续数据中心的系统和可验证指标

基本信息

项目摘要

Data centers already contribute significantly to the global carbon footprint. However, the rise in popularity of resource-intensive Big Data and Machine Learning workloads is poised to make data center operations unsustainable. This project designs a suite of Sustainability Aware Software SYstems (SASSY) to enable "sustainable-by-design" data centers. SASSY focuses on sustainability holistically, considering the lifecycle carbon footprint of computing equipment, cleanliness of energy source, and device reliability. To measure per-job end-to-end sustainability costs, a full-stack measurement framework is developed. To involve end-users in sustainability efforts, new programming models and tools are designed to enable users to specify their sustainability and performance objectives. The metrics and models together guide SASSY to make wise data-center-wide sustainable management choices.The adoption of SASSY solutions leads to sustainability savings that benefit the society at large. Further, the SASSY programming models and tools allow developers to build more sustainable applications, enabling "sustainable-by-design" software development. Data center operators and industry partners can directly benefit from SASSY's open-source software and models, which are made public through the project Website: https://www.pace.cs.stonybrook.edu/sassy.html. The next generation of practitioners and researchers are taught to consider sustainability as a first-class metric via educational and mentoring opportunities that the project generates.This project was in response to and partially funded by Design for Sustainability in Computing (NSF-22-060)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.
数据中心已经对全球碳足迹做出了重大贡献。然而,资源密集型大数据和机器学习工作负载的普及将使数据中心运营变得不可持续。该项目设计了一套可持续性意识软件系统(SASSY),以实现“可持续设计”的数据中心。SASSY从整体上关注可持续性,考虑计算设备的生命周期碳足迹,能源清洁度和设备可靠性。为了衡量每项工作的端到端的可持续性成本,开发了一个全栈测量框架。为了让最终用户参与可持续性工作,设计了新的方案编制模式和工具,使用户能够具体说明其可持续性和业绩目标。这些指标和模型共同指导SASSY做出明智的数据中心范围的可持续管理选择。采用SASSY解决方案可以节省可持续性成本,造福整个社会。此外,SASSY编程模型和工具使开发人员能够构建更可持续的应用程序,从而实现“设计可持续”的软件开发。数据中心运营商和行业合作伙伴可以直接从SASSY的开源软件和模型中受益,这些软件和模型通过项目网站https://www.pace.cs.stonybrook.edu/sassy.html公开。通过该项目提供的教育和指导机会,下一代从业者和研究人员被教导将可持续性视为一流的指标。该项目是对计算可持续性设计的回应,并由该项目提供部分资金。(NSF-22-060)该奖项反映了NSF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进行评估,被认为值得支持审查标准。

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)
Verifiable Sustainability in Data Centers
  • DOI:
    10.48550/arxiv.2307.11993
  • 发表时间:
    2023-07
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Syed Rafiul Hussain;P. Mcdaniel;Anshul Gandhi;K. Ghose;Kartik Gopalan;Dongyoon Lee;Yu Liu;Zhen Liu-Zhe
  • 通讯作者:
    Syed Rafiul Hussain;P. Mcdaniel;Anshul Gandhi;K. Ghose;Kartik Gopalan;Dongyoon Lee;Yu Liu;Zhen Liu-Zhe
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Syed Rafiul Hussain其他文献

ProChecker: An Automated Security and Privacy Analysis Framework for 4G LTE Protocol Implementations
ProChecker:用于 4G LTE 协议实施的自动安全和隐私分析框架
RBP: Reliable Broadcasting Protocol in Large Scale Mobile Ad Hoc Networks
RBP:大规模移动自组织网络中的可靠广播协议
A Systematic Framework For Analyzing the Security and Privacy of Cellular Networks
  • DOI:
    10.25394/pgs.7347371.v1
  • 发表时间:
    2020-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Syed Rafiul Hussain
  • 通讯作者:
    Syed Rafiul Hussain
BLEDiff: Scalable and Property-Agnostic Noncompliance Checking for BLE Implementations
BLEDiff:BLE 实现的可扩展且与属性无关的不合规性检查

Syed Rafiul Hussain的其他文献

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{{ truncateString('Syed Rafiul Hussain', 18)}}的其他基金

CAREER: Principled Approaches to Securing Next-Generation Cellular Networks
职业:保护下一代蜂窝网络的原则性方法
  • 批准号:
    2145631
  • 财政年份:
    2022
  • 资助金额:
    $ 20.66万
  • 项目类别:
    Continuing Grant

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Cell Research
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    专项基金项目
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    10774081
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