发表机构
Barcelona Supercomputing Center (BSC); Universitat Politècnica de Catalunya - BarcelonaTech (UPC)（巴塞罗那超级计算中心（BSC）; 加泰罗尼亚理工大学-巴塞罗那理工（UPC））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对分布式量子电路模拟中节点间通信开销大的问题，提出通信感知的量子比特布局优化框架，集成于QuCSLO库，支持动态节点分配，在合成与真实基准上实现超2倍加速。
AI 中文摘要
分布式量子电路模拟通过将量子比特划分到多个计算节点上，使得大规模量子算法的执行成为可能。然而，低效的量子比特布局常常导致节点间通信过度，严重限制了性能和可扩展性。本工作引入了一种通信感知的量子比特布局优化框架，该框架系统地最小化节点间的数据交换，同时动态选择最优的计算资源数量。集成到QuCSLO库中，我们的方法支持动态节点扩展、OpenQASM解析以及与QuEST模拟器的无缝集成。在合成基准和真实世界的QASMBench电路上的广泛评估表明，与恒等布局相比，优化后的布局显著减少了通信切割，并在高度纠缠的电路中实现了超过2倍的运行时加速。我们的结果强调了战略性量子比特布局对分布式模拟效率的关键影响，并为量子工作负载提供了一种实用、资源可扩展的解决方案。
英文摘要
Distributed quantum circuit simulation enables the execution of large-scale quantum algorithms by partitioning qubits across multiple computational nodes. However, inefficient qubit placement frequently leads to excessive inter-node communication, severely limiting performance and scalability. This work introduces a communication-aware qubit layout optimization framework that systematically minimizes data exchange among nodes while dynamically selecting the optimal number of computational resources. Integrated into the QuCSLO library, our approach supports dynamic node scaling, OpenQASM parsing, and seamless integration with the QuEST simulator. Extensive evaluations on both synthetic benchmarks and real-world QASMBench circuits demonstrate that optimized layouts significantly reduce communication cuts and yield runtime speedups of over 2x compared to identity layouts, particularly in highly entangled circuits. Our results underscore the critical impact of strategic qubit placement on distributed simulation efficiency and provide a practical, resource-scalable solution for quantum workloads.
