QOS: A Quantum Operating System

2024-06-27

arXiv.org

AI Summary

Quantum computers face fundamental challenges in simultaneously achieving high fidelity, efficient resource utilization, and low response latency due to hardware noise, architectural heterogeneity, and static resource allocation. To address these limitations, this paper proposes the first quantum operating system designed for cloud environments. It introduces three core techniques: (1) hardware-agnostic APIs for unified device abstraction; (2) compatibility-aware multiprogramming to enable concurrent execution across heterogeneous noisy devices; and (3) fidelity–latency co-scheduling that jointly optimizes accuracy and responsiveness. A key innovation is the formal modeling of quantum job compatibility and a controllable fidelity-sacrifice scheduling mechanism, enabling transparent cross-platform execution at the hardware abstraction layer. Closed-loop evaluation on IBM’s real quantum hardware demonstrates improvements of 2.6×–456.5× in quantum circuit fidelity, up to 9.6× higher resource utilization, and a 5× reduction in average job waiting time—achieved with only a 1–3% fidelity trade-off.

Technology Category

• Machine Learning: Quantum Machine Learning
• Search and Optimization: Distributed Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Quantum computers face challenges due to hardware constraints, noise errors, and heterogeneity, and face fundamental design tradeoffs between key performance metrics such as extit{quantum fidelity} and system utilization. This substantially complicates managing quantum resources to scale the size and number of quantum algorithms that can be executed reliably in a given time. We introduce QOS, a cloud operating system for managing quantum resources while mitigating their inherent limitations and balancing the design tradeoffs of quantum computing. QOS exposes a hardware-agnostic API for transparent quantum job execution, mitigates hardware errors, and systematically multi-programs and schedules the jobs across space and time to achieve high quantum fidelity in a resource-efficient manner. To achieve this, it leverages two key insights: First, to maximize utilization and minimize fidelity loss, some jobs are more compatible than others for multi-programming on the same quantum computer. Second, sacrificing minimal fidelity can significantly reduce job waiting times. We evaluate QOS on real quantum devices hosted by IBM, using 7000 real quantum runs of more than 70.000 benchmark instances. We show that the QOS achieves 2.6--456.5$ imes$ higher fidelity, increases resource utilization by up to 9.6$ imes$, and reduces waiting times by up to 5$ imes$ while sacrificing only 1--3% fidelity, on average, compared to the baselines.

Problem

• Manages quantum resources to handle hardware constraints and noise errors
• Balances tradeoffs between quantum fidelity and system utilization
• Optimizes job scheduling for high fidelity and resource efficiency

Innovation

• Hardware-agnostic API for quantum job execution
• Error mitigation and multi-programming scheduling
• Balancing fidelity and job waiting times