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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.14955 |
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| _version_ | 1866913038274134016 |
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| author | Cipollini, Marco Rizzo, Simone Iserte, Sergio Viviani, Paolo Vitali, Giacomo Barbieri, Matteo Bettonte, Gabriella Boella, Elisabetta Ganz, Fulvio Rocco, Roberto Spina, Orazio Peña, Antonio J. Sandås, Petter Colonnelli, Iacopo Scionti, Alberto Vercellino, Chiara Dri, Emanuele Frassineti, Jonathan Marzella, Sara Muratori, Andrea Ottaviani, Daniele Terzo, Olivier Montrucchio, Bartolomeo Gregori, Daniele |
| author_facet | Cipollini, Marco Rizzo, Simone Iserte, Sergio Viviani, Paolo Vitali, Giacomo Barbieri, Matteo Bettonte, Gabriella Boella, Elisabetta Ganz, Fulvio Rocco, Roberto Spina, Orazio Peña, Antonio J. Sandås, Petter Colonnelli, Iacopo Scionti, Alberto Vercellino, Chiara Dri, Emanuele Frassineti, Jonathan Marzella, Sara Muratori, Andrea Ottaviani, Daniele Terzo, Olivier Montrucchio, Bartolomeo Gregori, Daniele |
| contents | As quantum computing (QC) technologies mature, their integration into established high-performance computing (HPC) infrastructures is becoming a central objective for next-generation computing systems. However, unlocking the potential of hybrid platforms for computationally demanding workloads remains challenging. The mismatch between quantum and classical programming models, the limited maturity of quantum software stacks, and the scarcity of quantum processing units (QPUs) above all, necessitate scheduling strategies that go beyond standard HPC mechanisms to manage such heterogeneous and constrained resources.
To address this issue, we investigate three distinct methodologies for HPC-QC resource scheduling: time-based multiplexing, dynamic resource management, and workflow decomposition. Experimental validation on production HPC clusters and real quantum hardware demonstrates the effectiveness of these approaches under different workload scenarios. Malleability and workflow strategies significantly optimize classical resource utilization, reducing consumption by up to 45.7% and 64% respectively, proving to be best fitted for hybrid jobs where quantum and classical workloads are evenly balanced. Conversely, time-multiplexing enhances QPU utilization and reduces execution time at the cluster level, making it the optimal strategy for the opposite context, which is characterized by high classical-quantum workload imbalances. These findings underscore the practical viability of tailored scheduling strategies for hybrid HPC-QC environments and highlight their complementarity in building efficient, scalable software stacks for next-generation quantum-accelerated facilities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_14955 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Three ways to share a QPU: Scheduling strategies for hybrid Quantum-HPC applications Cipollini, Marco Rizzo, Simone Iserte, Sergio Viviani, Paolo Vitali, Giacomo Barbieri, Matteo Bettonte, Gabriella Boella, Elisabetta Ganz, Fulvio Rocco, Roberto Spina, Orazio Peña, Antonio J. Sandås, Petter Colonnelli, Iacopo Scionti, Alberto Vercellino, Chiara Dri, Emanuele Frassineti, Jonathan Marzella, Sara Muratori, Andrea Ottaviani, Daniele Terzo, Olivier Montrucchio, Bartolomeo Gregori, Daniele Quantum Physics As quantum computing (QC) technologies mature, their integration into established high-performance computing (HPC) infrastructures is becoming a central objective for next-generation computing systems. However, unlocking the potential of hybrid platforms for computationally demanding workloads remains challenging. The mismatch between quantum and classical programming models, the limited maturity of quantum software stacks, and the scarcity of quantum processing units (QPUs) above all, necessitate scheduling strategies that go beyond standard HPC mechanisms to manage such heterogeneous and constrained resources. To address this issue, we investigate three distinct methodologies for HPC-QC resource scheduling: time-based multiplexing, dynamic resource management, and workflow decomposition. Experimental validation on production HPC clusters and real quantum hardware demonstrates the effectiveness of these approaches under different workload scenarios. Malleability and workflow strategies significantly optimize classical resource utilization, reducing consumption by up to 45.7% and 64% respectively, proving to be best fitted for hybrid jobs where quantum and classical workloads are evenly balanced. Conversely, time-multiplexing enhances QPU utilization and reduces execution time at the cluster level, making it the optimal strategy for the opposite context, which is characterized by high classical-quantum workload imbalances. These findings underscore the practical viability of tailored scheduling strategies for hybrid HPC-QC environments and highlight their complementarity in building efficient, scalable software stacks for next-generation quantum-accelerated facilities. |
| title | Three ways to share a QPU: Scheduling strategies for hybrid Quantum-HPC applications |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2604.14955 |