Enabling Hybrid HPCQC Workflows with a Heterogeneous Software Stack

Abstract:In this work, we demonstrate hybrid High Performance Computing-Quantum Computing (HPCQC) workflows on a production petascale system. The demonstration combines three components: the SuperMUC-NG supercomputer at the Leibniz Supercomputing Centre (LRZ), a 20-qubit superconducting quantum processor provided by IQM Quantum Computers (IQM), and Munich Quantum Valley (MQV)'s Munich Quantum Software Stack (MQSS). Integrating quantum processors into High Performance Computing (HPC) systems requires a heterogeneous software stack capable of orchestrating classical and quantum resources within established supercomputing workflows. MQSS treats Quantum Processing Units (QPUs) as scheduler-managed accelerators and it performs resource coordination following a two-level scheduling scheme. Slurm performs system-level allocation by exposing QPUs as Generic RESources (GRES), while the MQSS Quantum Resource Manager & Compiler Infrastructure (QRM&CI) performs just-in-time compilation and subsequent dispatch of quantum circuits. To integrate with existing HPC operations without modifying the scheduler core, MQSS introduces an open-source SLURM Plugin Suite based on Prolog/Epilog scripts and SPANK modules. Experimental results show that hybrid HPCQC workflows can be executed without significant latency overhead compared to conventional workloads. The presented architecture provides a portable integration model for quantum accelerators on large-scale HPC systems and is directly applicable to next-generation Hewlett Packard Enterprise (HPE) Cray platforms, including LRZ's upcoming 'Blue Lion' supercomputer.

Presented at the Cray User Group conference (CUG26). Conditionally accepted for the ACM International Conference Proceedings Series (ICPS)

Quantum Physics (quant-ph); Distributed, Parallel, and Cluster Computing (cs.DC); Software Engineering (cs.SE)

arXiv:2608.14827 [quant-ph]

(or arXiv:2608.14827v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2608.14827 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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