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.

翻译：新兴高性能计算系统的极端异构性正开始纳入量子加速器，这推动了能够协调经典与量子工作负载的运行时系统的需求。我们提出了一种概念验证的混合执行框架，通过量子中间表示执行引擎（QIR-EE）将IRIS异步任务型运行时系统与XACC量子编程框架集成。IRIS可在异构后端（包括多个量子模拟器）上编排以量子中间表示（QIR）编写的多个程序，实现经典任务与量子任务的并发执行。尽管本研究并非性能评估，但我们通过成功异步调度和执行多个量子工作负载报告了可测量的成果。为阐明实际运行时影响，我们通过量子电路切割过程将一个四量子比特电路分解为更小的子电路，从而降低每个任务的量子模拟负载，并展示任务粒度如何提升模拟器吞吐量、减少排队行为——这些效应与早期量子硬件环境直接相关。最后，我们概述了扩展混合运行时系统的关键挑战，包括协调调度、经典-量子交互管理以及对异构系统中多样化后端资源的支持。