An Ising Computer Based on Simulated Quantum Annealing by Path Integral Monte Carlo Method
An Ising Computer Based on Simulated Quantum Annealing by Path Integral Monte Carlo Method
复制标题
基于路径积分蒙特卡罗方法模拟量子退火的Ising计算机
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
M. Yamaoka
中科院分区：
文献类型：
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作者：
Takuya Okuyama;Masato Hayashi;M. Yamaoka
在不久的将来，解决大型组合优化问题将是一个主要的过程。然而，冯诺依曼架构的性能增长将因半导体规模化的结束而放缓。为了解决这个问题，我们提出了一个伊辛计算机映射的优化问题的伊辛模型的基态搜索。我们以前提出了一个计算机，找到伊辛模型的基态模拟退火（SA）近似。虽然以前的原型的解决方案的质量是可比的SA，提高解决方案的质量将需要解决现实世界的应用程序。在本文中，我们提出了我们的基于FPGA的伊辛计算机，执行模拟量子退火通过使用路径积分量子蒙特卡罗方法伊辛模型上的48-48国王图与8位耦合。我们还提出了一个共享的随机数供应，这有助于减少随机数生成器的数量到两个。实验结果表明，建议的伊辛计算机是超过15倍的速度，以获得99.9%的解决方案的概率为99%比SA运行在一个国家的最先进的CPU。
In the near future, one of the main processes is solving large combinatorial optimization problems. However, the performance growth of von Neumann architecture will slow due to the end of semiconductor scaling. To resolve this problem, we propose an Ising computer that maps the optimization problems to the ground state search of Ising models. We previously proposed a computer that finds the ground state of Ising models by simulated annealing (SA) approximately. Though the solution quality of the previous prototype is comparable to that of SA, enhancing the solution quality will be required to solve real-world applications. In this paper, we present our FPGA-based Ising computer that executes simulated quantum annealing by using a path integral quantum Monte Carlo method for Ising models on a 48-by-48 king graph with 8-bit couplings. We also propose a shared random number supply, which contributes to decrease the number of random number generators to two. Experimental results indicate that the proposed Ising computer is more than 15 times faster to obtain 99.9%-solution with a probability of 99% than SA running on a state-of-the-art CPU.