Collaborative Research: PPoSS: Planning: Software Stack for Scalable Heterogeneous NISQ Cluster
协作研究:PPoSS:规划:可扩展异构 NISQ 集群的软件堆栈
基本信息
- 批准号:2216898
- 负责人:
- 金额:$ 3.5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-07-15 至 2024-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Development of large-scale and practical quantum computers is a priority for many countries, industries, and researchers. Demonstrating quantum computers at scale will change the computing model as it is currently known forever, enabling scientific discoveries at an unprecedented pace. This project’s novelties are in designing future quantum systems as a cluster of heterogeneous quantum computers. Such an approach is significantly different from all existing endeavors, as it will be cost effective, scalable, more usable, and more reliable. The project’s impacts include outlining the challenges in such systems, proposing solutions, engaging the community, and describing a plan to build a full software stack for such heterogeneous quantum-computing-based clusters. The project will also engage the multidisciplinary quantum computing community through three invited workshops to inform the potential path towards solutions for the challenges outlined. Through a backbone stakeholder committee, the project will ensure sustainable and sustained workforce development and broadening participation in computing objectives, outcomes, and impact at scale. In addition, the project personnel have a strong commitment to increasing participation of underrepresented groups (including women, racial minorities, and persons with disabilities) in planned activities.This project explores the feasibility of designing a full software stack for a cluster of heterogeneous Noisy Intermediate-Scale Quantum (NISQ) machines. The project will make contributions to the: (a) Realization of cluster of heterogeneous NISQ machines as a quantum-computing platform with large-scale simulation and evaluation on a real platform; (b) Programming environment and user interface to provide a visual interface to understand quantum noise; (c) Compilation techniques to account for heterogeneity of NISQ machines and temporal errors; (d) Runtime to enable fault-tolerance, resource management and scheduling considering the queuing time and noise condition in real time with the help of a resource monitoring mechanism to query the calibration information from all available quantum computers; (e) Co-design of the stack with quantum machine learning and quantum chemistry applications; (f) Utilization of the system calibration data from the multiple existing quantum machines, then apply fidelity degradation detection on each noise attributes to generate the fidelity degradation matrix which is used to define multiple new evaluation metrics to compare the fidelity between the qubit topology of the quantum machines; and (g) Engagement of the multidisciplinary quantum computing community through three invited workshops to inform the potential path towards solutions for the challenges outlined. Education, workforce development (WFD) and broadening participation in computing (BPC) are a major priority of this project. These will be realized as: (a) Through a backbone stakeholder committee, the investigators will ensure sustainable and sustained WFD and BPC objectives, outcomes, and impact at scale. The project plan capitalizes on the breadth of expertise of the PIs with an overall strategy organized to reach increasingly larger stakeholder groups (starting from project members, the broader systems community, and finally to K-12 and non-affiliated professionals); (b) In addition, the project personnel have a strong commitment to increasing participation of underrepresented groups (including women, racial minorities, and persons with disabilities) in planned activities; (c) The investigators will incorporate research outcomes in multiple courses; and (d) The project will facilitate collaboration and synergy among systems researchers, and engage and partner with industry for technology transfer and commercialization.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.
大型和实用量子计算机的开发是许多国家,行业和研究人员的优先事项。大规模演示量子计算机将改变计算模型,因为它目前是永远众所周知的,从而在前所未有的空间中实现了科学发现。该项目的新颖性在于将未来的量子系统设计为一组异质量子计算机群。这种方法与所有现有的努力都有明显不同,因为它将具有成本效益,可扩展,更可用且更可靠。该项目的影响包括概述此类系统中的挑战,提出解决方案,吸引社区,并描述一项计划,为这种异构量子计算的群集构建完整的软件堆栈。该项目还将通过三个邀请的研讨会来吸引多学科量子计算社区,以告知有关概述挑战解决方案的潜在途径。通过主干利益相关者委员会,该项目将确保可持续和持续的劳动力发展,并扩大参与计算对象,成果和大规模影响的参与。此外,项目人员在计划中的活动中增加代表性不足的群体(包括妇女,种族少数群体和残疾人)的参与有坚定的承诺。该项目探讨了设计完整的软件堆栈的可行性,用于一群异构嘈杂的中间量表量子(Nisq)机器。该项目将为:(a)实现异质NISQ机器的群集作为一个量子计算平台,并在真实平台上进行大规模模拟和评估; (b)编程环境和用户界面,以提供视觉界面以了解量子噪声; (c)汇编技术,以说明NISQ机器和临时错误的异质性; (d)运行时借助资源监控机制,可以实时考虑排队时间和噪声状况,以查询所有可用量子计算机的校准信息; (e)与量子机学习和量子化学应用的共同设计; (f)利用来自多个现有量子机的系统校准数据,然后在每个噪声属性上应用保真度降解检测来生成保真度降解矩阵,该降解矩阵用于定义多个新的评估指标以比较量子机的量子拓扑之间的忠诚度; (g)通过三个邀请的研讨会来参与多学科量子计算社区,以告知解决概述挑战的解决方案的潜在途径。教育,劳动力发展(WFD)和扩大计算的参与(BPC)是该项目的主要优先事项。这些将被实现为:(a)通过主干利益相关者委员会,调查人员将确保可持续和持续的WFD和BPC目标,成果和大规模影响。该项目计划利用了PI的专业知识的广度,并组织了一项整体战略,该战略旨在达到越来越大的利益相关者群体(从项目成员,更广泛的系统社区开始,最后是K-12和非伴随的专业人员); (b)此外,项目人员致力于增加代表性不足的团体(包括妇女,少数民族和残疾人)的参与计划; (c)调查人员将在多个课程中纳入研究成果; (d)该项目将促进系统研究人员之间的协作和协同作用,并与行业进行技术转移和商业化合作。该奖项反映了NSF的法定任务,并被认为是值得通过基金会的知识分子和更广泛影响的评估审查标准来通过评估来获得支持的。
项目成果
期刊论文数量(0)
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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Samee Khan其他文献
Samee Khan的其他文献
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{{ truncateString('Samee Khan', 18)}}的其他基金
REU Site: Intelligent Edge Computing Systems
REU 站点:智能边缘计算系统
- 批准号:
2348711 - 财政年份:2024
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
FET: Medium: A Quantum Computing Based Approach to Undirected Generative Machine Learning Models
FET:中:基于量子计算的无向生成机器学习模型方法
- 批准号:
2211841 - 财政年份:2022
- 资助金额:
$ 3.5万 - 项目类别:
Continuing Grant
Workshop on Quantum Computing, Information, Science, and Engineering
量子计算、信息、科学与工程研讨会
- 批准号:
2202377 - 财政年份:2022
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
Travel: NSF Student Travel Grant for 2022 IEEE Cloud Summit
旅行:2022 年 IEEE 云峰会 NSF 学生旅行补助金
- 批准号:
2243579 - 财政年份:2022
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Small: HARMONIA: New Methods for Colocating Multiple QoS-Sensitive Jobs
协作研究:CNS 核心:小型:HARMONIA:共置多个 QoS 敏感作业的新方法
- 批准号:
2124908 - 财政年份:2021
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$ 3.5万 - 项目类别:
Standard Grant
EAGER: From Theory to Practice of Elastic Interval Runtime Schedulers
EAGER:弹性间隔运行时调度器从理论到实践
- 批准号:
2135439 - 财政年份:2021
- 资助金额:
$ 3.5万 - 项目类别:
Standard Grant
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协作研究:PPoSS:大型:大规模声明性分析的全栈方法
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