计算机科学 ›› 2023, Vol. 50 ›› Issue (6): 74-80.doi: 10.11896/jsjkx.220500108

• 高性能计算 • 上一篇    下一篇

基于“嵩山”超级计算机系统下HHL算法的模拟实现

谢浩山1, 刘晓楠1, 赵晨言1, 刘正煜2   

  1. 1 数学工程与先进计算国家重点实验室(信息工程大学) 郑州 450000
    2 郑州大学计算机与人工智能学院 郑州 450000
  • 收稿日期:2022-05-12 修回日期:2022-10-10 出版日期:2023-06-15 发布日期:2023-06-06
  • 通讯作者: 刘晓楠(prof.liu.xn@foxmail)
  • 作者简介:(15237933568@163.com)
  • 基金资助:
    国家自然科学基金(61972413,61701539)

Simulation Implementation of HHL Algorithm Based on Songshan Supercomputer System

XIE Haoshan1, LIU Xiaonan1, ZHAO Chenyan1, LIU Zhengyu2   

  1. 1 State Key Laboratory of Mathematical Engineering,Advanced Computing,Information Engineering University,Zhengzhou 450000,China
    2 School of Computer and Artificial Intelligence,Zhengzhou University,Zhengzhou 450000,China
  • Received:2022-05-12 Revised:2022-10-10 Online:2023-06-15 Published:2023-06-06
  • About author:XIE Haoshan,born in 1998,postgra-duate.His main research interest is quantum computer.LIU Xiaonan,born in 1977,Ph.D,associate professor,master supervisor,is a member of China Computer Federation.His main research interests include quantum computer and high-perfor-mance parallel computation.
  • Supported by:
    National Natural Science Foundation of China(61972413,61701539).

摘要: 量子计算是一种遵循量子力学规律来调控量子信息单元进行计算的新型计算模式,而量子算法由一系列量子门组合而成,其实现形式为量子线路。量子线路是对量子比特进行操作的线路,以量子比特为基本的存储单元,将量子逻辑门连接在一起来实现特定的计算功能。文中在“嵩山”超级计算机上利用MPI+OpenMP混合并行编程模型,实现了将大规模量子线路拆分到不同节点上进行构建,加快了线路的构建速度,并且在CPU集群系统上具有良好的可拓展性。针对节点间通信问题,设计了序列化和反序列化函数,以保证节点间数据的传输,并且根据各节点所分配任务量间存在的指数级差异,设计了一种拆分任务量、各节点轮循处理的优化方式,实现了节点间的负载均衡。最后在超级计算机CPU集群上成功实现了大规模的量子相位估计线路的构造,相较于单节点取得了8.63的加速比,并通过HHL算法验证了所设计的并行相位估计子模块的正确性,为大规模HHL算法在超算平台上的实现提供了参考。

关键词: 量子相位估计, CPU集群, MPI, HHL算法, 负载均衡

Abstract: Quantum computing is a new computing mode that follows the laws of quantum mechanics to regulate and control quantum information units to perform calculations,while the quantum algorithm is composed of a series of quantum gates whose realized form is quantum circuit.Quantum circuits are circuits that operate on qubits,using qubits as the basic storage unit to connect quantum logic gates to achieve specific computing functions.This paper uses the MPI+OpenMP hybrid parallel programming model on the “Songshan” supercomputer to realize the construction of large-scale quantum circuits by splitting them into different nodes,which speeds up the construction of circuits.For the communication problem between nodes,serialization and deserialization functions are designed to ensure the transmission of data between nodes.Aiming at the exponential difference in the amount of tasks allocated by each node,an optimized method of splitting the task amount and round-robin processing of each node is designed to achieve load balance between nodes.Finally,the construction of a large-scale quantum phase estimation circuit is successfully implemented on the supercomputer CPU cluster.Compared with a single node,the speedup ratio of 8.63 is achieved.The HHL algorithm is used to verify the correctness of the designed parallel phase estimation sub-module,which provides a reference for the implementation of large-scale HHL algorithm on the supercomputing platform.

Key words: Quantum phase estimation, CPU cluster, MPI, HHL algorithm, Load balancing

中图分类号: 

  • TP385
[1]DEUTSCH D.Quantum theory the Church-Turing principle and the universal quantum computer[J].Proceedings of the Royal Society of London.Series A,Mathematical and Physical Sciences,1985,400(1818):97-117.
[2]SHOR P W.Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer[J].SIAM Review,1999:41(2),303-332.
[3]GROVER L K.A fast quantum mechanical algorithm for database search[C]//Proceedings of the twenty-eighth annual ACM symposium on Theory of computing.1996:212-219.
[4]HARROW A W,HASSIDIM A,LLOYD S.Quantum Algo-rithm for Linear Systems of Equations[J].Physical Review Letters,2009:103(15):150502.
[5]HUANG C J,ZHANG F,NEWMAN M,et al.Classical simulation of quantum supremacycircuits[J].arXiv:2005.06787,2020.
[6]PEDNAULT E,GUNNELS J A,NANNICINI G,et al.Pareto-Efficient Quantum Circuit Simulation Using Tensor Contraction Deferral[J].arXiv:1710.05867,2017.
[7]LI R L,WU B J,YM S,et al.Quantum supremacy circuit simulation on Sunway TaihuLight[J].IEEE Transactions on Parallel and Distributed Systems,2019,31(4):805-816.
[8]MAUCH V,KUNZE M,HILLENBRAND M.High perfor-mance cloud computing[J].Future Generation Computer Systems,2013,29(6):1408-1416.
[9]LAROSE R.Quantum Physics,Computer Science-Distributed,Parallel,and Cluster Computing[J].arXiv:1801.01037,2018.
[10]HNER T.Steiger D S.0.5 petabyte simulation of a 45-qubitquantum circuit[C]//the International Conference for High Performance Computing,Networking,Storage and Analysis.2017:1-10.
[11]ZHAO Y Q,LI R G,JIANG J Z,et al.Simulation of quantum computing on classical supercomputers with tensor-network edge cutting[J].Physical Review A,2021,104(3):032603.
[12]YU Z C,LI Y Z,LIU L,FENG S Z.A review of quantum computing simulation and optimization methods[J].Computer Engineering,2022,48(1):1-11.
[13]ILIAS K,VASSILIOS V D.Experiences with task-based pro-gramming using cluster nodes as OpenMP devices[J].arXiv:2205.10656,2022.
[14]YU Q X.A Unified Programming Model for HeterogeneousComputing with CPU and Accelerator Technologies[J].arXiv:2204.06864,2022.
[15]LU F X.Research on key technology of parallel Computing for CPU/GPU Heterogeneous Architecture[D].Changsha:Natio-nal University of Defense Technology,2014.
[16]WOSSNING L,ZHAO Z,PRAKASH A.Quantum linear system algorithm for dense matrices[J].Physical Review Letters,2018,120(5):050502.
[17]NIELSEN M A,CHUANG I L.Quantum Computation andQuantum Information[J].Mathematical Structures in Computer Science,2002,17(6):1115-1116.
[18]SOMMA,ROLANDO D.A Trotter-Suzuki approximation forLie groups with applications to Hamiltonian simulation[J].Journal of Mathematical Physics,2016,57(6):467-488.
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