Empowering the Quantum Cloud User with QRIO
Shmeelok Chakraborty, Yuewen Hou, Ang Chen, Gokul Subramanian Ravi
TL;DR
QRIO addresses the challenge of long queues and suboptimal resource use in cloud-accessible quantum devices by delivering a Kubernetes-based, open-source Quantum Resource Infrastructure Orchestrator. The approach combines a four-component architecture (Visualizer, Master Server, Meta Server, Scheduler) with fidelity-based (Clifford Canary) and topology-based (Mapomatic) ranking to allocate heterogeneous quantum and classical resources efficiently. Key contributions include end-to-end orchestration, customizable user specifications, and empirical evaluation on simulated 100-backend environments demonstrating improved device selection and scheduling fidelity. The work aims to democratize quantum cloud access, enable hybrid quantum-classical workflows, and lay groundwork for scalable, HPC-like quantum cloud infrastructure.
Abstract
Quantum computing is moving swiftly from theoretical to practical applications, making it crucial to establish a significant quantum advantage. Despite substantial investments, access to quantum devices is still limited, with users facing issues like long wait times and inefficient resource management. Unlike the mature cloud solutions for classical computing, quantum computing lacks effective infrastructure for resource optimization. We propose a Quantum Resource Infrastructure Orchestrator (QRIO), a state-of-the-art cloud resource manager built on Kubernetes that is tailored to quantum computing. QRIO seeks to democratize access to quantum devices by providing customizable, user-friendly, open-source resource management. QRIO's design aims to ensure equitable access, optimize resource utilization, and support diverse applications, thereby speeding up innovation and making quantum computing more accessible and efficient to a broader user base. In this paper, we discuss QRIO's various features and evaluate its capability in several representative usecases.