Hungarian qubit assignment for optimized mapping of quantum circuits on multi-core architectures
Modular quantum computing architectures offer a promising alternative to monolithic designs for overcoming the scaling limitations of current quantum computers. To achieve scalability beyond small prototypes, quantum architectures are expected to adopt a modular approach, featuring clusters of tight...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/395386 |
| Acceso en línea: | https://hdl.handle.net/2117/395386 https://dx.doi.org/10.1109/LCA.2023.3318857 |
| Access Level: | acceso abierto |
| Palabra clave: | Quantum computing -- Scalability Computer algorithms Mapping of quantum algorithms Multi-core quantum computing architectures Quantum computing Computació quàntica -- Escalabilitat Algorismes computacionals Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors |
| Sumario: | Modular quantum computing architectures offer a promising alternative to monolithic designs for overcoming the scaling limitations of current quantum computers. To achieve scalability beyond small prototypes, quantum architectures are expected to adopt a modular approach, featuring clusters of tightly connected quantum bits with sparser connections between these clusters. Efficiently distributing qubits across multiple processing cores is critical for improving quantum computing systems’ performance and scalability. To address this challenge, we propose the Hungarian Qubit Assignment (HQA) algorithm, which leverages the Hungarian algorithm to improve qubit-to-core assignment. The HQA algorithm considers the interactions between qubits over the entire circuit, enabling fine-grained partitioning and enhanced qubit utilization. We compare the HQA algorithm with state-of-the-art alternatives through comprehensive experiments using both real-world quantum algorithms and random quantum circuits. The results demonstrate the superiority of our proposed approach, outperforming existing methods, with an average improvement of 1.28×. |
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