Hybrid Computing and Orchestration

Qonductor: A Cloud Orchestrator for Quantum Computing

SC2025Hybrid Computing and Orchestration
Best Student Paper Award finalist

Abstract

We describe Qonductor, a cloud orchestrator for hybrid quantum-classical applications that run on heterogeneous hybrid resources. Qonductor abstracts away the complexity of hybrid programming and resource management by exposing the Qonductor API, a high-level and hardware-agnostic API. The resource estimator strategically balances quantum and classical resources to mitigate resource contention and the effects of hardware noise. The hybrid scheduler automates job scheduling on hybrid resources and balances the tradeoff between users' objectives of QoS and the cloud operator's objective of resource efficiency. We implement an open-source prototype and evaluate Qonductor using more than 7000 real quantum runs on the IBM quantum cloud to simulate real cloud workloads. Qonductor achieves up to 54% lower job completion times (JCTs) while sacrificing 3% execution quality, balances the load across QPU, which increases quantum resource utilization by up to 66%, and scales with growing system sizes and loads.

Abstract source

Publication

Qonductor paper, first page
Title
Qonductor: A Cloud Orchestrator for Quantum Computing
Venue
SC
Year
2025
Status
Publication

BibTeX

@inproceedings{Giortamis_2025,
  series={SC '25},
  title={Qonductor: A Cloud Orchestrator for Quantum Computing},
  url={http://dx.doi.org/10.1145/3712285.3759785},
  DOI={10.1145/3712285.3759785},
  booktitle={Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis},
  publisher={ACM},
  author={Giortamis, Emmanouil and Romao, Francisco and Tornow, Nathaniel and Lugovoy, Dmitry and Bhatotia, Pramod},
  year={2025},
  month=Nov,
  pages={728--745},
  collection={SC '25}
}
Citation source