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.
开发大规模和实用的量子计算机是许多国家,行业和研究人员的优先事项。大规模展示量子计算机将永远改变目前已知的计算模型,使科学发现以前所未有的速度进行。该项目的新颖之处在于将未来的量子系统设计为异构量子计算机的集群。这种方法与所有现有的努力都有很大的不同,因为它具有成本效益,可扩展性,更可用,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,吸引社区参与,并描述为此类异构量子计算集群构建完整软件堆栈的计划。该项目还将通过三个受邀研讨会吸引多学科量子计算社区的参与,为解决所概述挑战的潜在途径提供信息。通过骨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,并扩大对计算目标,成果和影响的参与。此外,项目人员有一个强有力的承诺,以增加代表性不足的群体(包括妇女,少数民族和残疾人)在计划的actives.This项目的参与探讨了设计一个完整的软件堆栈的异构噪声中间规模量子(NISQ)机器集群的可行性。该项目将有助于:(a)实现异质NISQ机器集群,作为一个量子计算平台,在真实的平台上进行大规模模拟和评估;(B)编程环境和用户界面,为理解量子噪声提供可视界面;(c)编译技术,以说明NISQ机器的异质性和时间误差;(d)在资源监测机制的帮助下,考虑到真实的排队时间和噪声条件,实现容错、资源管理和调度,以查询所有可用量子计算机的校准信息;(f)利用来自多个现有量子机的系统校准数据,然后对每个噪声属性应用保真度退化检测以生成保真度退化矩阵,该保真度退化矩阵用于定义多个新的评估度量以比较量子机的量子比特拓扑之间的保真度;以及(g)通过三个应邀举办的讲习班,让多学科量子计算界参与进来,为解决所概述的挑战提供可能的途径。教育、劳动力发展(WFD)和扩大参与计算(BPC)是该项目的主要优先事项。这些将实现为:(a)通过骨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,成果和规模影响。项目计划充分利用了项目负责人的广泛专业知识,并制定了一项总体战略,以覆盖越来越多的利益相关者群体(从项目成员开始,更广泛的系统社区,最后到K-12和非附属专业人员);(B)此外,项目人员坚决致力于增加代表性不足群体的参与(c)研究人员将把研究成果纳入多门课程;以及(d)该项目将促进系统研究人员之间的合作和协同作用,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(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
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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
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$ 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
- 资助金额:
$ 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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Research on Quantum Field Theory without a Lagrangian Description
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- 批准号:10774081
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