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Main Authors: Zhou, Ruilin, Gan, Yuhang, Liu, Yi, Qian, Chen
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2504.20389
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author Zhou, Ruilin
Gan, Yuhang
Liu, Yi
Qian, Chen
author_facet Zhou, Ruilin
Gan, Yuhang
Liu, Yi
Qian, Chen
contents Distributed quantum computing (DQC) that allows a large quantum circuit to be executed simultaneously on multiple quantum processing units (QPUs) becomes a promising approach to increase the scalability of quantum computing. It is natural to envision the near-future DQC platform as a multi-tenant cluster of QPUs, called a Quantum Cloud. However, no existing DQC work has addressed the two key problems of running DQC in a multi-tenant quantum cloud: placing multiple quantum circuits to QPUs and scheduling network resources to complete these jobs. This work is the first attempt to design a circuit placement and resource scheduling framework for a multi-tenant environment. The proposed framework is called CloudQC, which includes two main functional components, circuit placement and network scheduler, with the objectives of optimizing both quantum network cost and quantum computing time. Experimental results with real quantum circuit workloads show that CloudQC significantly reduces the average job completion time compared to existing DQC placement algorithms for both single-circuit and multi-circuit DQC. We envision this work will motivate more future work on network-aware quantum cloud.
format Preprint
id arxiv_https___arxiv_org_abs_2504_20389
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle CloudQC: A Network-aware Framework for Multi-tenant Distributed Quantum Computing
Zhou, Ruilin
Gan, Yuhang
Liu, Yi
Qian, Chen
Distributed, Parallel, and Cluster Computing
Quantum Physics
Distributed quantum computing (DQC) that allows a large quantum circuit to be executed simultaneously on multiple quantum processing units (QPUs) becomes a promising approach to increase the scalability of quantum computing. It is natural to envision the near-future DQC platform as a multi-tenant cluster of QPUs, called a Quantum Cloud. However, no existing DQC work has addressed the two key problems of running DQC in a multi-tenant quantum cloud: placing multiple quantum circuits to QPUs and scheduling network resources to complete these jobs. This work is the first attempt to design a circuit placement and resource scheduling framework for a multi-tenant environment. The proposed framework is called CloudQC, which includes two main functional components, circuit placement and network scheduler, with the objectives of optimizing both quantum network cost and quantum computing time. Experimental results with real quantum circuit workloads show that CloudQC significantly reduces the average job completion time compared to existing DQC placement algorithms for both single-circuit and multi-circuit DQC. We envision this work will motivate more future work on network-aware quantum cloud.
title CloudQC: A Network-aware Framework for Multi-tenant Distributed Quantum Computing
topic Distributed, Parallel, and Cluster Computing
Quantum Physics
url https://arxiv.org/abs/2504.20389