DMapS: End-to-end Qubit Mapping and Routing for Distributed Quantum Computing Architectures

Distributed quantum computing (DQC) architectures offer a scalable solution for the computational demands of large-scale quantum computing. In near-term DQC architectures, the costly remote quantum communication and the execution cost within quantum chips together significantly limit the execution efficiency of quantum circuits. To comprehensively optimize both costs, we propose DMapS, which consists of end-to-end algorithms for qubit mapping and routing. The qubit mapping component, DMapS-M, adopts a two-stage mapping strategy that decomposes a large quantum circuit into smaller ones and parallelizes the qubit mapping on quantum chips. The qubit routing component, DMapS-R, reduces remote quantum communication overhead by prioritizing the insertion of local SWAP gates and further improves transpilation efficiency by exploiting parallelism within chips. Our experimental results show that DMapS-M reduces overall overhead (including both remote quantum communication overhead and local SWAP gate overhead) by an average of 43.44% and 59.72%, respectively, compared to two baseline algorithms, and achieves an average speedup of 87.05x. DMapS-R, compared to the baseline algorithm, reduces overall overhead by an average of 8.85% and achieves an average transpilation speedup of 2.78×. Moreover, compared to the DQC-oriented quantum compiler, DMapS reduces remote communication overhead by an average of 75.16%.

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Publication Details

Journal
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Published
2025-01-01
DOI
https://doi.org/10.1109/tcad.2025.3611153
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

DMapS: End-to-end Qubit Mapping and Routing for Distributed Quantum Computing Architectures

Yuxin Deng, Xiang Fu, Yuzhen Zheng, Tingyu Luo
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Quantum Computing Algorithms and Architecture
article

DMapS: End-to-end Qubit Mapping and Routing for Distributed Quantum Computing Architectures

Yuxin Deng, Xiang Fu, Yuzhen Zheng, Tingyu Luo
article en

Abstract

Distributed quantum computing (DQC) architectures offer a scalable solution for the computational demands of large-scale quantum computing. In near-term DQC architectures, the costly remote quantum communication and the execution cost within quantum chips together significantly limit the execution efficiency of quantum circuits. To comprehensively optimize both costs, we propose DMapS, which consists of end-to-end algorithms for qubit mapping and routing. The qubit mapping component, DMapS-M, adopts a two-stage mapping strategy that decomposes a large quantum circuit into smaller ones and parallelizes the qubit mapping on quantum chips. The qubit routing component, DMapS-R, reduces remote quantum communication overhead by prioritizing the insertion of local SWAP gates and further improves transpilation efficiency by exploiting parallelism within chips. Our experimental results show that DMapS-M reduces overall overhead (including both remote quantum communication overhead and local SWAP gate overhead) by an average of 43.44% and 59.72%, respectively, compared to two baseline algorithms, and achieves an average speedup of 87.05x. DMapS-R, compared to the baseline algorithm, reduces overall overhead by an average of 8.85% and achieves an average transpilation speedup of 2.78×. Moreover, compared to the DQC-oriented quantum compiler, DMapS reduces remote communication overhead by an average of 75.16%.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
National University of Defense Technology (CN), Shanghai Key Laboratory of Trustworthy Computing (CN), East China Normal University (CN)
Openalex Percentile: Top 87%
Quantum Computing Algorithms and Architecture
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