Experimental Evaluation of Performance Improvement by Sparse Operation in Ising Spin Computing

A. Yoshida, T. Miki, M. Shimada, Yuri Yoneda, J. Shirakashi
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Abstract

The ability to quickly solve combinatorial optimization problems is essential for improving society and industry. For solving the problems, we present extraction-type majority voting logic (E-MVL) that purposely discards the interaction between the spins by scheduling a parameter, called sparsity. In this paper, the intrinsic computation time of E-MVL is estimated by using step-to-solution (STS) which evaluates the performance independent of implementation. We show that the E-MVL can explore the ground state to the Sherrington-Kirkpatrick model essentially faster than highly optimized simulated annealing (SA). These results indicate that E-MVL is more effective for optimization problems than SA.
利用稀疏运算改进Ising自旋计算性能的实验评价
快速解决组合优化问题的能力对于改善社会和工业是必不可少的。为了解决这些问题,我们提出了抽取型多数投票逻辑(E-MVL),该逻辑通过调度一个称为稀疏性的参数来有意地放弃自旋之间的相互作用。本文采用与实现无关的逐步求解方法估计了E-MVL的固有计算时间。研究表明,E-MVL可以比高度优化的模拟退火(SA)更快地探索谢林顿-柯克帕特里克模型的基态。这些结果表明,E-MVL在优化问题上比SA更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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