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The paper proposes a reference architecture for Quantum-Centric Supercomputing (QCSC) systems, integrating QPUs, GPUs, and CPUs to accelerate quantum-classical algorithms. It addresses the current limitations of isolated quantum and classical systems by outlining three evolutionary phases towards fully co-designed heterogeneous quantum-HPC systems. The proposed architecture aims to streamline workflow orchestration, job scheduling, and data transfer, thereby enhancing productivity and enabling rapid algorithmic exploration.
Quantum-Centric Supercomputers promise to break down the barriers between quantum and classical computing, enabling seamless hybrid algorithms and accelerating discovery across applications.
Quantum computers have demonstrated utility in simulating quantum systems beyond brute-force classical approaches. As the community builds on these demonstrations to explore using quantum computing for applied research, algorithms and workflows have emerged that require leveraging both quantum computers and classical high-performance computing (HPC) systems to scale applications, especially in chemistry and materials, beyond what either system can simulate alone. Today, these disparate systems operate in isolation, forcing users to manually orchestrate workloads, coordinate job scheduling, and transfer data between systems -- a cumbersome process that hinders productivity and severely limits rapid algorithmic exploration. These challenges motivate the need for flexible and high-performance Quantum-Centric Supercomputing (QCSC) systems that integrate Quantum Processing Units (QPUs), Graphics Processing Units (GPUs), and Central Processing Units (CPUs) to accelerate discovery of such algorithms across applications. These systems will be co-designed across quantum and classical HPC infrastructure, middleware, and application layers to accelerate the adoption of quantum computing for solving critical computational problems. We envision QCSC evolution through three distinct phases: (1) quantum systems as specialized compute offload engines within existing HPC complexes; (2) heterogeneous quantum and classical HPC systems coupled through advanced middleware, enabling seamless execution of hybrid quantum-classical algorithms; and (3) fully co-designed heterogeneous quantum-HPC systems for hybrid computational workflows. This article presents a reference architecture and roadmap for these QCSC systems.
