Abstract: With its superposition and entanglement properties,quantum computing has a powerful parallel computing capacity.However,current quantum computers cannot ensure stable superposition states of large-scale qubits while performing quantum operations such as interference and entanglement.Therefore,the current approach to promote quantum computing is to simulate quantum computing using classical computers.The Grover quantum search algorithm is designed for the problem of searching unsorted databases,reducing the time complexity to square root level,and accelerating principal component analysis in machine learning.Therefore,studying and simulating the Grover algorithm can promote the development of quantum computing combined with machine learning and lay the foundation for its application as well as the simulation of Grover quantum search algorithm in the “Songshan” supercomputer system.By studying the Grover quantum search algorithm,the quantum circuit of the algorithm is simulated.The Toffoli quantum gate is used to optimize the quantum circuit,proposing a universal quantum circuit for the Grover algorithm while reducing two auxiliary qubits.The experiment is based on the CPU+DCU heterogeneous system of the “Song-shan” supercomputer system,using a two-level parallel strategy of MPI multiprocessing and HIP multithreading.By adjusting the position of the auxiliary qubits in the quantum circuit,the communication between MPI processes is reduced,and the data-depen-dent quantum states are transmitted using a fragmentation method.Compared to the serial version,the parallelized simulation algorithm achieves a maximum speedup of 560.33 times,realizing for the first time the Grover quantum search algorithm with a scale of 31 qubits.

Key words: Grover's quantum search algorithm, Heterogeneous architecture, MPI, HIP, Fragment-based transmission