Q-IRIS: The Evolution of the IRIS Task-Based Runtime to Enable Classical-Quantum Workflows

• URL: http://arxiv.org/abs/2512.13931v1
• Date: Mon, 15 Dec 2025 22:11:00 GMT
• Title: Q-IRIS: The Evolution of the IRIS Task-Based Runtime to Enable Classical-Quantum Workflows
• Authors: Narasinga Rao Miniskar, Mohammad Alaul Haque Monil, Elaine Wong, Vicente Leyton-Ortega, Jeffrey S. Vetter, Seth R. Johnson, Travis S. Humble,
• Abstract summary: We present a proof-of-concept hybrid execution framework integrating the IRIS task-based runtime with the XACC quantum programming framework.<n>IRIS orchestrates multiple programs written in the quantum intermediate representation (QIR) across heterogeneous backends.<n>We demonstrate how task granularity can improve simulator throughput and reduce queueing behavior.
• Score: 1.0894174366773024
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Extreme heterogeneity in emerging HPC systems are starting to include quantum accelerators, motivating runtimes that can coordinate between classical and quantum workloads. We present a proof-of-concept hybrid execution framework integrating the IRIS asynchronous task-based runtime with the XACC quantum programming framework via the Quantum Intermediate Representation Execution Engine (QIR-EE). IRIS orchestrates multiple programs written in the quantum intermediate representation (QIR) across heterogeneous backends (including multiple quantum simulators), enabling concurrent execution of classical and quantum tasks. Although not a performance study, we report measurable outcomes through the successful asynchronous scheduling and execution of multiple quantum workloads. To illustrate practical runtime implications, we decompose a four-qubit circuit into smaller subcircuits through a process known as quantum circuit cutting, reducing per-task quantum simulation load and demonstrating how task granularity can improve simulator throughput and reduce queueing behavior -- effects directly relevant to early quantum hardware environments. We conclude by outlining key challenges for scaling hybrid runtimes, including coordinated scheduling, classical-quantum interaction management, and support for diverse backend resources in heterogeneous systems.

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