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QSRA: A QPU Scheduling and Resource Allocation Approach for Cloud-Based Quantum Computing

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arxiv 2411.05283 v1 pith:ZYAJKJM3 submitted 2024-11-08 quant-ph

QSRA: A QPU Scheduling and Resource Allocation Approach for Cloud-Based Quantum Computing

classification quant-ph
keywords quantumqubitqsraallocationschedulingapproachchallengesprograms
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Quantum cloud platforms, which rely on Noisy Intermediate-Scale Quantum (NISQ) devices, face significant challenges in efficiently managing quantum programs. This paper proposes a QPU Scheduling and Resource Allocation (QSRA) approach to address these challenges. QSRA enhances qubit utilization and reduces turnaround time by adapting CPU scheduling techniques to Quantum Processing Units (QPUs). It incorporates a subroutine for qubit allocation that takes into account qubit quality and connectivity, while also merging multiple quantum programs to further optimize qubit usage. Our evaluation of QSRA against existing methods demonstrates its effectiveness in improving both qubit utilization and turnaround time.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Quantum Fidelity-per-Cost: A Metric for Evaluation of Quantum Computing Systems

    quant-ph 2026-07 conditional novelty 5.5

    Cost-aware ranking of cloud QPUs via QFC disagrees with fidelity-only ranking; billing model, not hardware, fixes how the score scales with shot count.