Award Abstract # 2216923
Collaborative Research: PPoSS: Planning: Software Stack for Scalable Heterogeneous NISQ Cluster

NSF Org: CCF
Division of Computing and Communication Foundations
Recipient: CASE WESTERN RESERVE UNIVERSITY
Initial Amendment Date: July 13, 2022
Latest Amendment Date: July 13, 2022
Award Number: 2216923
Award Instrument: Standard Grant
Program Manager: Damian Dechev
CCF
 Division of Computing and Communication Foundations
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: July 15, 2022
End Date: June 30, 2024 (Estimated)
Total Intended Award Amount: $143,156.00
Total Awarded Amount to Date: $143,156.00
Funds Obligated to Date: FY 2022 = $143,156.00
History of Investigator:
  • Vipin Chaudhary (Principal Investigator)
    vipin@case.edu
  • shuai xu (Co-Principal Investigator)
Recipient Sponsored Research Office: Case Western Reserve University
10900 EUCLID AVE
CLEVELAND
OH  US  44106-4901
(216)368-4510
Sponsor Congressional District: 11
Primary Place of Performance: Case Western Reserve University
OH  US  44106-7614
Primary Place of Performance
Congressional District:
11
Unique Entity Identifier (UEI): HJMKEF7EJW69
Parent UEI:
NSF Program(s): PPoSS-PP of Scalable Systems
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 026Z
Program Element Code(s): 042Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

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.

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

This project has made significant advancements in quantum computing techniques, education, and collaboration. Key achievements include the development of advanced quantum circuit cutting methods, which have been refined to reduce complexity, as well as novel scheduling techniques that account for noise and enable efficient execution of multiple quantum jobs. Enhanced visualization methods were introduced to provide deeper insights into quantum states, and these innovations have been integrated into quantum computing courses as project ideas, enriching student learning.

The team successfully conducted three workshops on quantum applications, hardware, and software stacks, fostering robust engagement from academia, industry, and national laboratories. Numerous papers were published in high-impact peer-reviewed conferences and journals, showcasing the project's contributions to the field. Additionally, a strategic partnership with Cleveland Clinic and IBM was established through the Discovery Accelerator program, providing access to IBM’s 127-qubit quantum computer. These outcomes underscore the project's impact on advancing quantum computing research, education, and collaboration.

The project also fostered a vibrant, multi-institutional research group in quantum computing, including two graduate students and one undergraduate student funded by this project, with a total of ten students actively participating in research activities. These students have presented their work in weekly group meetings and at international conferences, significantly contributing to the project's success. This collective effort highlights the project's significant contributions to advancing quantum computing research, fostering educational growth, and promoting collaboration, while equipping the next generation of scientists and engineers with invaluable skills and training.

 


Last Modified: 12/10/2024
Modified by: Vipin Chaudhary

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