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QIR-EE

Elaine Wong, Vicente Leyton‐Ortega, S. R. Johnson, Daniel Claudino, Austin S. Adams, Sharmin Afrose, Meenambika Gowrishankar, Travis S. Humble

Published Jan 1, 2025• 1 citation
Publisher

Abstract

The QIR Execution Engine library provides interfaces for easily processing Quantum Intermediate Representation code using the LLVM execution engine.
DOI
10.11578/qiree/dc.20250114.1

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Intermediate representations (IRs) play a crucial role in the software stack of a quantum computer to facilitate efficient optimizations for executing an application on hardware. One of those IRs is the Quantum Intermediate Representation (QIR), which builds on the classical LLVM compiler infrastructure. In this article, we outline different approaches to how QIR can be adopted. This exploration culminates in a demonstration of what it takes to turn an existing quantum circuit simulator into a QIR runtime and that such a transition is less daunting than it might seem at first. We further show that switching to QIR does not entail any performance deficits compared to the original simulator. On the contrary, the presented steps effortlessly allow adding support for arbitrary classical control flow to any classical simulator. We conclude with an outlook on future directions using QIR. The implemented QIR runtime is available under https://github.com/munich-quantum-toolkit/core.
Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.
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