计算机科学
复制品
云计算
马尔可夫链
组合优化
最优化问题
多样性(控制论)
并行计算
算法
人工智能
操作系统
机器学习
艺术
视觉艺术
作者
Satoshi Matsubara,Motomu Takatsu,Toshiyuki Miyazawa,Takayuki Shibasaki,Yasuhiro Watanabe,Kazuya Takemoto,Hirotaka Tamura
标识
DOI:10.1109/asp-dac47756.2020.9045100
摘要
A Digital Annealer (DA) is a dedicated architecture for high-speed solving of combinatorial optimization problems mapped to an Ising model. With fully coupled bit connectivity and high coupling resolution as a major feature, it can be used to express a wide variety of combinatorial optimization problems. The DA uses Markov Chain Monte Carlo as a basic search mechanism, accelerated by the hardware implementation of multiple speed-enhancement techniques such as parallel search, escape from a local solution, and replica exchange. It is currently being offered as a cloud service using a second-generation chip operating on a scale of 8,192 bits. This paper presents an overview of the DA, its performance against benchmarks, and application examples.
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