STATICA: A 512-Spin 0.25M-Weight Annealing Processor with an All-Spin-Updates-at-Once Architecture for Combinatorial Optimization with Complete Spin-Spin Interactions,
STATICA: A 512-Spin 0.25M-Weight Annealing Processor with an All-Spin-Updates-at-Once Architecture for Combinatorial Optimization with Complete Spin-Spin Interactions,
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STATICA：具有全自旋一次更新架构的 512 次自旋 0.25M 重量退火处理器，用于具有完整自旋-自旋交互的组合优化，
DOI：
10.1109/jssc.2020.3027702
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发表时间：
2021
影响因子：
5.4
通讯作者：
and Masato Motomura
中科院分区：
文献类型：
--
作者：
Kasho Yamamoto;Kazushi Kawamura;Kota Ando;Normann Mertig;Takashi Takemto;Masanao Yamaoka;Hiroshi Teramoto;Akira Sakai;Shinya Takamaeda-Yamazaki;and Masato Motomura
本文提出了一种高性能退火处理器——随机元胞自动机退火处理器（STATICA），用于求解全连通图表示的组合优化问题。在处理实际优化问题时，强烈要求支持完全连通图。与以往遵循Glauber动力学的退火处理器不同，我们提出的退火处理器可以通过引入随机元胞自动机退火来同时更新完全连接自旋的多个状态。它允许我们利用管道级和内存库级并行化，除了pe级并行化最初在以前的退火器中采用。支持512自旋全连接图的STATICA原型芯片采用65纳米CMOS技术制作，实现为3mm芯片。利用已制备的512自旋芯片和2048自旋芯片的数值投影，我们进行了实验，揭示了STATICA的退火性能，并研究了如何有效地控制其退火过程。
This article presents a high-performance annealing processor named STochAsTIc Cellular automata Annealer (STATICA) for solving combinatorial optimization problems represented by fully connected graphs. Supporting fully connected graphs is strongly required for dealing with realistic optimization problems. Unlike previous annealing processors that follow Glauber dynamics, our proposed annealer can update multiple states of fully connected spins simultaneously by introducing different dynamics called stochastic cellular automata annealing. It allows us to utilize the pipeline-level and memory-bank-level parallelization in addition to the PE-level parallelization originally adopted in the previous annealers. The STATICA prototype chip, which supports 512-spin fully connected graph, has been fabricated with the 65-nm CMOS technology and realized as a 3 mmmm chip. Using the fabricated 512-spin chip and numerical projections for a 2048-spin chip, we have conducted experiments to reveal the annealing performance of STATICA and examined how to control its annealing process efficiently.