English

Bridging Paradigms: Designing for HPC-Quantum Convergence

Quantum Physics 2025-07-21 v2 Distributed, Parallel, and Cluster Computing

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.

Keywords

Cite

@article{arxiv.2503.01787,
  title  = {Bridging Paradigms: Designing for HPC-Quantum Convergence},
  author = {Amir Shehata and Peter Groszkowski and Thomas Naughton and Murali Gopalakrishnan Meena and Elaine Wong and Daniel Claudino and Rafael Ferreira da Silvaa and Thomas Beck},
  journal= {arXiv preprint arXiv:2503.01787},
  year   = {2025}
}

Comments

14 pages, 14 figures

R2 v1 2026-06-28T22:05:02.322Z