Multi-level scheduling supports scalable quantum computing

Quantum computing architectures have expanded to systems with quantum processing units (QPU) that operate hundreds of qubits. Over the next years, these systems will increasingly be combined with cloud-based access and integrated into readily available high-performance computing (HPC) clusters. To achieve such goals, there are several critical points that need to be addressed: First, the quantum computing resource should be efficiently distributed between multiple users. Second, the shared QPU resource should have minimal downtime, i.e. duty cycle should be maximized. Here, we present how our open-source control software framework (LabOne Q) addresses these challenges by introducing quantum job scheduling on multiple levels. Efficient scheduling of jobs in both the hardware and the software levels optimizes queues and priorities among jobs submitted by multiple users, making LabOne Q an ideal platform for HPC integration. Additionally, through this job scheduler functionality, we achieve a significant decrease in QPU idle time. Finally, the hardware level abstraction in LabOne Q enables a framework for automated QPU tune-up/maintenance, which in combination with job scheduling further reduces QPU idle time.