Qtenon: Towards Low-Latency Architecture Integration for Accelerating Hybrid Quantum-Classical Computing
Chenning Tao, Liqiang Lu, Size Zheng, Li-Wen Chang, Minghua Shen, Hanyu Zhang, Fangxin Liu, Kaiwen Zhou, Jianwei Yin
Abstract
Hybrid quantum-classical algorithms have shown great promise in leveraging the computational potential of quantum systems.However, the efficiency of these algorithms is severely constrained by the limitations of current quantum hardware architectures.These architectures, which typically feature a decoupled design, lack both hardware support for low-latency communication and software support for fine-grained optimization.In this paper, we propose Qtenon, a tightly coupled system for efficient hybrid quantum-classical algorithm acceleration.Qtenon is composed of both hardware part and software part.To enable efficient communication and computation, the hardware part provides a unified memory hierarchy, an efficient quantum controller, as well as a multi-stage processing pipeline.The unified memory hierarchy functions as a communication buffer between host and quantum accelerators, with dedicated data paths and interfaces provided by the quantum controller.The multi-stage pipeline leverages hardware pipelines to fully exploit parallelism.To program hybrid quantum-classical algorithms on the hardware, our software part provides a set of instructions for data communication and computation.The instructions also enable fine-grained synchronization and efficient scheduling for quantum-host interaction.We design Qtenon as a RISC-V extended chip and implement it using Chisel.In evaluation, we achieve up to 14.9× end-to-end speedup compared to state-of-the-art work for hybrid quantum-classical algorithms.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get cad9a9f4-147c-4a45-9431-9ebab30c0b8bRelated papers
- qTPU: Hybrid Tensor Networks for Quantum-Classical AccelerationNathaniel Tornow, Emmanouil Giortamis, Dennis Sprokholt, Christian Mendl et al.OSDI 2026 · 1 citation
- Qonductor: A Cloud Orchestrator for Quantum ComputingEmmanouil Giortamis, Francisco Romão, Nathaniel Tornow, Dmitry Lugovoy et al.SC 2025 · 4 citations
- UFC: A Unified Accelerator for Fully Homomorphic EncryptionMinxuan Zhou, Yujin Nam, Xuan Wang, Youhak Lee et al.MICRO 2024 · 19 citations
- QUILT: Effective Multi-Class Classification on Quantum Computers Using an Ensemble of Diverse Quantum ClassifiersDaniel Silver, Tirthak Patel, Devesh TiwariAAAI 2022 · 35 citations
- QIsim: Architecting 10+K Qubit QC Interfaces Toward Quantum SupremacyDongmoon Min, Junpyo Kim, Junhyuk Choi, Ilkwon Byun et al.ISCA 2023 · 14 citations
