Efficient In-Situ Quantum Computing Simulation of Shor's and Grover's Algorithms

A. Avila, R. Reiser, A. Yamin, M. Pilla
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引用次数: 3

Abstract

Exponential increase and global access to read/write memory states in quantum computing simulation limit both the number of qubits and quantum transformations that can be currently simulated. Although quantum computing simulation is parallel by nature, spatial and temporal complexity are major performance hazards, making this an important application for HPC. A new methodology employing reduction and decomposition optimizations has shown great results, but its GPU implementation could be further improved. In this work, we intend to do a new implementation for in-situ GPU simulation that better explores its resources without requiring further HPC hardware. Shors and Grovers algorithms are simulated and compared to the previous version and to LIQUi|s simulator, showing better results with relative speedups up to 15.5x and 765.76x respectively.
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Shor和Grover算法的高效原位量子计算模拟
在量子计算模拟中,指数增长和对读写存储器状态的全局访问限制了当前可以模拟的量子位和量子变换的数量。虽然量子计算模拟本质上是并行的,但空间和时间的复杂性是主要的性能危害,使其成为高性能计算的重要应用。一种采用约简和分解优化的新方法已经显示出了很好的结果,但其GPU实现还有待进一步改进。在这项工作中,我们打算为原位GPU模拟做一个新的实现,在不需要进一步的HPC硬件的情况下更好地探索其资源。对Shors和Grovers算法进行了仿真,并与之前的版本和LIQUi的模拟器进行了比较,显示出更好的结果,相对速度分别达到15.5倍和765.76倍。
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