research-article

Research on task scheduling scheme for quantum computing cloud platform

Authors:

Junsen LaiAuthors Info & Claims

ICCBDC '22: Proceedings of the 2022 6th International Conference on Cloud and Big Data Computing

Pages 7 - 11

https://doi.org/10.1145/3555962.3555964

Published: 18 October 2022 Publication History

Abstract

Quantum computing devices are usually demanding on the environment, with high operating conditions and maintenance costs. The supporting quantum computing operation software also has a high professional threshold. These make it more difficult to deploy and use locally. Cloud based quantum computing services will play an important role in computing power in the quantum era. At present, high-quality quantum computing QPU is scarce, which brings access needs of a large number of users. The computing tasks of a single user are too large, resulting in a large number of resources being occupied by a single user for a period of time, affecting the use of other users or tasks. A new quantum computing cloud platform task scheduling scheme is proposed to classify users and tasks and provide differentiated service opportunities. This scheme will enable high priority users to reduce waiting time and get a better experience.

References

[1]

CAICT.2021. Research Report on the Development and Application of Quantum Information Technology (2021). Technical Report No. 202127. China Academy of Information and Communications Technology.

[2]

CAICT.2021. Research Report on the development trend of quantum cloud computing (2021). China Academy of Information and Communications Technology.

[3]

Schaden, Martin. "Quantum finance." Physica A: Statistical Mechanics and Its Applications 316.1-4 (2002): 511-538. https://doi.org/10.1016/S0378-4371(02)01200-1.

[4]

Bouland, Adam, "Prospects and challenges of quantum finance." arXiv preprint arXiv:2011.06492 (2020). https://arxiv.org/pdf/2011.06492

[5]

Orús, Román, Samuel Mugel, and Enrique Lizaso. "Quantum computing for finance: Overview and prospects." Reviews in Physics 4 (2019): 100028. https://doi.org/10.1016/j.revip.2019.100028

[6]

Biamonte, Jacob, "Quantum machine learning." Nature 549.7671 (2017): 195-202. https://doi.org/10.1038/nature23474

[7]

Schuld, Maria, Ilya Sinayskiy, and Francesco Petruccione. "An introduction to quantum machine learning." Contemporary Physics 56.2 (2015): 172-185. https://doi.org/10.1080/00107514.2014.964942

[8]

Huang, Hsin-Yuan, "Power of data in quantum machine learning." Nature communications 12.1 (2021): 1-9. https://doi.org/10.1038/s41467-021-22539-9

[9]

Cao, Yudong, "Quantum chemistry in the age of quantum computing." Chemical reviews 119.19 (2019): 10856-10915. https://doi.org/10.1021/acs.chemrev.8b00803.

[10]

Lanyon, Benjamin P., "Towards quantum chemistry on a quantum computer." Nature chemistry 2.2 (2010): 106-111. https://doi.org/10.1038/nchem.483.

[11]

Epifanovsky, Evgeny, "Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package." The Journal of chemical physics 155.8 (2021): 084801. https://doi.org/10.1063/5.0055522.

[12]

Motta, Mario, and Julia E. Rice. "Emerging quantum computing algorithms for quantum chemistry." Wiley Interdisciplinary Reviews: Computational Molecular Science 12.3 (2022): e1580. https://doi.org/10.1002/wcms.1580.

[13]

Quantinuum. Quantinuum H1, Powered by Honeywell. Retrieved July 6,2022 from https://www.quantinuum.com/products/h1.

[14]

IBM. IBM Quantum. Retrieved July 6,2022 from https://quantum-computing.ibm.com.

[15]

OQC. OQC available on Amazon Braket. Retrieved July 6,2022 from https://oxfordquantumcircuits.com/oqc-on-aws.

[16]

Origin. Origin quantum computer. Retrieved July 6,2022 from https://qcloud.originqc.com.cn/computing/wuyuan.

Cited By

Huang JEmeakaroha V(2024)Performing Distributed Quantum Calculations in a Multi-cloud Architecture Secured by the Quantum Key Distribution ProtocolSN Computer Science10.1007/s42979-024-02761-05:4Online publication date: 8-Apr-2024
https://dl.acm.org/doi/10.1007/s42979-024-02761-0
Khare TMajumdar RSangle RRay ASeshadri PSimmhan Y(2023)Parallelizing Quantum-Classical Workloads: Profiling the Impact of Splitting Techniques2023 IEEE International Conference on Quantum Computing and Engineering (QCE)10.1109/QCE57702.2023.00113(990-1000)Online publication date: 17-Sep-2023
https://doi.org/10.1109/QCE57702.2023.00113

Index Terms

Research on task scheduling scheme for quantum computing cloud platform

Recommendations

A Conceptual Platform of SLA in Cloud Computing
DASC '11: Proceedings of the 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing

Cloud computing is a promising technology, where the infrastructure, developing platform, software and storage are delivered as a service. With the development of cloud computing, more and more cloud service providers emerge. However, there are no ...
Analysis and Research of Cloud Computing System Instance
ICFN '10: Proceedings of the 2010 Second International Conference on Future Networks

As a kind of emerging business computational model, Cloud Computing distribute computation task on the resource pool which consists of massive computers, accordingly ,the application systems can gain the computation strength, the storage space and ...
Research on Cloud Computing Security Platform
ICCIS '12: Proceedings of the 2012 Fourth International Conference on Computational and Information Sciences

As a kind of new technology, cloud computing has become a study highlight in both industrial field and academic field. As the users have to save their data in the cloud to use cloud computing, the security of cloud could affect users' trust in cloud ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

ICCBDC '22: Proceedings of the 2022 6th International Conference on Cloud and Big Data Computing

August 2022

88 pages

ISBN:9781450396578

DOI:10.1145/3555962

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 October 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Research-article
Research
Refereed limited

Conference

ICCBDC 2022

ICCBDC 2022: 2022 6th International Conference on Cloud and Big Data Computing

August 18 - 20, 2022

Birmingham, United Kingdom

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
98
Total Downloads

Downloads (Last 12 months)39
Downloads (Last 6 weeks)9

Reflects downloads up to 01 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Huang JEmeakaroha V(2024)Performing Distributed Quantum Calculations in a Multi-cloud Architecture Secured by the Quantum Key Distribution ProtocolSN Computer Science10.1007/s42979-024-02761-05:4Online publication date: 8-Apr-2024
https://dl.acm.org/doi/10.1007/s42979-024-02761-0
Khare TMajumdar RSangle RRay ASeshadri PSimmhan Y(2023)Parallelizing Quantum-Classical Workloads: Profiling the Impact of Splitting Techniques2023 IEEE International Conference on Quantum Computing and Engineering (QCE)10.1109/QCE57702.2023.00113(990-1000)Online publication date: 17-Sep-2023
https://doi.org/10.1109/QCE57702.2023.00113

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten