ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2021, Vol. 58 ›› Issue (9): 1856-1874.doi: 10.7544/issn1000-1239.2021.20210314

Special Issue: 2021量子计算专题

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An Investigation into Quantum Program Mapping on Superconducting Quantum Computers

Dou Xinglei, Liu Lei, Chen Yuetao   

  1. (State Key Laboratory of Computer Architecture (Institute of Computing Technology, Chinese Academy of Sciences), Beijing 100190) (Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190)
  • Online:2021-09-01
  • Supported by: 
    This work was supported by the National Natural Science Foundation of China (62072432, 61502452).

Abstract: Errors occur due to noise when quantum programs are running on a quantum computer. Previous quantum program mapping solutions map a specific quantum program onto the most reliable region on a quantum computer for higher fidelity. Mapping multiple quantum programs onto a specific quantum computer simultaneously improves the throughput and resource utilization of the quantum computer. However, due to the scarcity of robust resources and resource allocation conflict, multi-programming on quantum computers leads to a decline in overall fidelity. We introduce quantum program mapping, classify the related studies, and analyze their characteristics and differences. Furthermore, we propose a new mapping solution for mapping concurrent quantum programs, including three key designs. 1) We propose a community detection assisted qubit partition (CDAQP) algorithm, which partitions physical qubits for concurrent quantum programs according to both physical topology and the error rates, improving the reliability of initial mapping and avoiding the waste of robust resources. 2) We introduce inter-program SWAPs, reducing the mapping overheads of concurrent quantum programs. 3) A framework for scheduling quantum program mapping tasks is proposed, which dynamically selects concurrent quantum programs to be executed, improving the throughput while ensuring the fidelity of the quantum computers. Our approach improves the fidelity by 8.6% compared with the previous solution while reducing the mapping overheads by 11.6%. Our system is a prototype of the OS for quantum computers—QuOS.

Key words: quantum computing, multi-programming, mapping, fidelity, task scheduling

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