SW_Qsim: A Minimize-Memory Quantum Simulator with High-Performance on a New Sunway Supercomputer

Authors: Fang Li, Xin Liu, Yong Liu, Pengpeng Zhao, and Yuling Yang (National Supercomputing Center in Wuxi); Honghui Shang (Institute of Computing Technology, Chinese Academy of Sciences); Weizhe Sun, Zhen Wang, and Enming Dong (National Supercomputing Center in Wuxi); and Dexun Chen (Tsinghua University, China)

Abstract: Classical simulation of quantum computation plays a critical role in numerical studies of quantum algorithms and the validation of quantum devices. Here, we introduce SW_Qsim, a tensor-network-based quantum simulator, which is designed with a two-level parallel structure for efficient implementation on the many-core New Sunway Supercomputer. We propose a minimize-memory contraction path algorithm for rectangular quantum grids to reduce the memory overhead, and provide the memory-limited simulation capacity of SW26010pro. Moreover, tensor operations are carefully optimized on the SW processor to achieve high performance. We design a fault tolerance mechanism to improve the extreme-scale parallel stability. We benchmark SW_Qsim’s simulation of RQCs up to 400-qubits, achieving near-linear strong and weak scaling with up to 28.75 million cores, far beyond the previous state of the art. Our work sheds light on the development of efficient quantum algorithms for use in the physical, chemical, and engineering science fields.


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