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Quantum annealing for ICT system design automation

机译:ICT系统设计自动化的Quantum退火

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摘要

In this paper, we propose a novel architecture for a (quasi) optimization problem solver for system designing automation that combines a problem generator and general problem solver. It efficiently generates the number of constraints from a simple description about system requirements, and solves the optimization problem at high speed by utilizing a powerful problem solver. Our challenge is to apply quantum annealing for this purpose. However, we faced the following technical problems caused by the fundamental properties of a quantum annealer: P1) a quantum annealer does not accept a constraint with inequality, which is necessary to describe system design problems, and P2) digit overflow of the coefficient value in the constraints. In this paper, we illustrate the overall architecture of our problem solver and clarify the aforementioned issues. Then, we present solutions to each problem: S1) a conversion method from inequality to equation by the augmented Lagrange method, and S2) a problem conversion method that reduces the number of digits of the coefficient without changing the meaning of the problem. Through experiments with a number of example problems, we evaluated the performance and accuracy of our scheme in comparison with a traditional rigorous problem solver. We show that our scheme outperforms the solver at least in a number of situations, and discuss its future utility.
机译:在本文中,我们提出了一种新的架构(准)优化问题解决者,用于组合问题发生器和一般问题解算器的系统设计自动化。它有效地从关于系统要求的简单描述中产生约束的数量,并通过利用强大的问题求解器来高速解决优化问题。我们的挑战是为此目的应用量子退火。但是,我们面临着由量子退火器的基本特性引起的以下技术问题:P1)量子退化器不接受不等式的约束,这是描述系统设计问题的必要条件,并且P2)数字值溢出约束。在本文中,我们说明了我们问题解决者的整体架构,并阐明了上述问题。然后,我们向每个问题提出解决方案:S1)通过增强拉格朗日方法的不等式的转换方法,以及S2)一个问题转换方法,其减少了系数的数字数而不改变问题的含义。通过具有多个示例问题的实验,我们评估了与传统严格问题的解决者相比我们方案的性能和准确性。我们表明,我们的计划至少在许多情况下表现出求解器,并讨论其未来的实用程序。

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