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.

翻译：本文介绍了Qonductor，一种用于在异构混合资源上运行量子-经典混合应用的云编排器。Qonductor通过提供Qonductor API——一种高层次且硬件无关的API——抽象了混合编程与资源管理的复杂性。其资源估算器策略性地平衡量子与经典资源，以缓解资源争用及硬件噪声的影响。混合调度器自动在混合资源上进行作业调度，并权衡用户对服务质量（QoS）的目标与云运营商对资源效率的目标之间的平衡。我们实现了一个开源原型，并利用IBM量子云上超过7000次真实量子运行来模拟实际云工作负载，对Qonductor进行了评估。Qonductor在仅牺牲3%执行质量的情况下，实现了作业完成时间（JCT）最高降低54%，均衡了量子处理单元（QPU）间的负载，使量子资源利用率最高提升66%，并能随系统规模与负载的增长而扩展。