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P2 MECH: Multi-Entry Communication Highway for Superconducting Quantum Chiplets

MECH:面向超导量子芯粒的多入口通信高速公路
ASPLOS Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 22024匹配度 2/10 · 该论文研究超导量子芯片间的通信机制与量子程序编译,属于量子体系结构和编译方向,与用户关注的“PL与AI/LLM结合、静态分析、浮点程序分析、贝叶斯程序分析”核心方向基本无关;仅在“编译与代码生成”这一宽泛标签上存在弱关联。引用 21 inbox
Hezi Zhang, Keyi Yin, Anbang Wu, Hassan Shapourian, Alireza Shabani, Yufei Ding
crossref: 2026-09-12dblp: 2026-09-12arxiv: 2026-09-12

AI 速览

一句话:提出多入口通信高速公路机制,用辅助量子比特换取程序并发度,并构建编译框架高效管理该资源。

量子芯粒(chiplet)架构凭借可扩展性与模块化有望大幅增加量子比特资源,但计算规模增大后,量子比特间的通信因路由距离过长而成为严重瓶颈。本文提出多入口通信高速公路(MECH)机制,通过牺牲辅助量子比特来换取程序并发度,并构建配套编译框架以高效管理与利用高速公路资源。评估表明,在典型量子基准程序上,该框架在电路深度与操作数量两方面均显著优于基线方法,这意味着量子程序编译可以更高效且更不易出错。

问题
量子芯粒架构虽能提升量子比特资源的可扩展性,但随着计算规模增大,长路由距离导致量子比特间通信成为严重瓶颈。
方法
提出多入口通信高速公路(MECH)机制,以辅助量子比特换取程序并发度,并构建编译框架来管理与利用高速公路资源。
评估
在典型量子基准程序上,将所提编译框架与基线方法对比,考察电路深度与操作数量两项指标,结果显示显著优于基线。
原文摘要(Abstract)

Chiplet architecture is an emerging architecture for quantum computing that could significantly increase qubit resources with its great scalability and modularity. However, as the computing scale increases, communication between qubits would become a more severe bottleneck due to the long routing distances. In this paper, we propose a multi-entry communication highway (MECH) mechanism to trade ancillary qubits for program concurrency, and build a compilation framework to efficiently manage and utilize the highway resources. Our evaluation shows that this framework significantly outperforms the baseline approach in both the circuit depth and the number of operations on typical quantum benchmarks. This implies a more efficient and less error-prone compilation of quantum programs.

链接与引用

DOI 原文 · arXiv · PDF(开放获取) · DBLP

BibTeX
@inproceedings{ZhangYWSSD24,
  title = {MECH: Multi-Entry Communication Highway for Superconducting Quantum Chiplets},
  author = {Hezi Zhang and Keyi Yin and Anbang Wu and Hassan Shapourian and Alireza Shabani and Yufei Ding},
  booktitle = {ASPLOS},
  year = {2024},
  doi = {10.1145/3620665.3640377}
}