Abstract
This paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for scientific computing, their effective integration with classical HPC systems presents significant technical challenges. We propose a hardware-agnostic software framework that supports both current noisy intermediate-scale quantum devices and future fault-tolerant quantum computers, while maintaining compatibility with existing HPC workflows. The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms to handle both simultaneous and interleaved quantum–classical workloads. Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, (3) A Quantum Platform Manager API that simplifies the integration of various quantum hardware systems, and (4) a comprehensive tool chain for quantum circuit optimization and execution. We demonstrate our architecture through implementation of quantum–classical algorithms, including the variational quantum linear solver, showcasing the framework's ability to handle complex hybrid workflows while maximizing resource utilization. This work provides a foundational blueprint for integrating QC capabilities into existing HPC infrastructures, addressing critical challenges in resource management, job scheduling, and efficient data movement between classical and quantum resources.
| Original language | English |
|---|---|
| Article number | 107980 |
| Journal | Future Generation Computer Systems |
| Volume | 174 |
| DOIs | |
| State | Published - Jan 2026 |
Funding
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Research sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy. We thank Dr. Chao Lu (ORNL) for his contributions to the development of the VQLS application, which was used as a representative example in this work. The space exploring QC integration with existing HPC resources is relatively nascent, with a flurry of activity and collaborations surfacing only within the last few years. Some examples include conceptual renderings of QHPC middleware [34] , an effort at ORNL [35] integrating quantum runtimes in parallel with other accelerators onto CPUs and GPUs within an established task-based kernel framework IRIS [36] , and the Munich Quantum Valley [37] , a consortium of research institutions and universities in Bavaria focused on a unified software stack for the HPC-QC ecosystem [38,39] . However, other international teaming underscores the importance of pursuing robust integration efforts and providing frameworks for effectively enhancing conventional computing. For example, HPC-QS [40] , funded by the European Union, has intentions to integrate and couple two quantum simulators, with two existing European Tier-0 supercomputers, and to deploy an open European federated hybrid infrastructure. More recently, IBM joined forces with the Riken Quantum Computing Center [41] , where the IBM system powered by a 133-qubit IBM Quantum Heron processor, would be co-located and integrated with the Fugaku supercomputer. Additionally, with Pasqal [42] , they aim to develop a unified programming model built on Qiskit, aiming to integrate quantum and classical computing resources for HPC workflows. Lastly, IQM have partnered with Hewlett Packard Enterprise (HPE) for their version of quantum-HPC integration [43] . Other industry developments that can potentially enable effective hybrid QC-HPC include Nvidia’s Cuda-Q [44] and Riverlane’s Deltaflow [45] . This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).
Keywords
- High-performance computing
- Quantum applications
- Quantum computing
- System integration