4.6 A 144Kb Annealing System Composed of 9× 16Kb Annealing Processor Chips with Scalable Chip-to-Chip Connections for Large-Scale Combinatorial Optimization Problems
4.6 A 144Kb Annealing System Composed of 9× 16Kb Annealing Processor Chips with Scalable Chip-to-Chip Connections for Large-Scale Combinatorial Optimization Problems
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4.6 由 9 个 16Kb 退火处理器芯片组成的 144Kb 退火系统,具有可扩展的芯片到芯片连接,用于解决大规模组合优化问题
DOI:
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发表时间:
2021
期刊:
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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:
Takashi Takemoto;Kasho Yamamoto;C. Yoshimura;Masato Hayashi;Masafumi Tada;Hiroaki Saito;Mayumi Mashimo;M. Yamaoka
Substantial progress has been made on a new computer architecture, known as an annealing processor (AP) [1–4]. The AP can effectively solve NP-hard combinatorial optimization problems by providing a fast method for finding the grand state of an Ising model. In particular, various types of APs based on a CMOS process (CMOS-AP) significantly improve the scalability and power efficiency of the annealing system by utilizing fast parallel spin updates on the basis of simulated annealing (SA) [2] –[4]. Further development of CMOS-APs requires overcoming two challenges: improving the accuracy of the annealing processing by expanding the bitwidth of coefficients and attaining a multi-chip annealing system consisting of AP chips with 8-way connectivity. In this work, we developed a scalable CMOS-AP with two key technologies: (i) A flip-flop (FF)-based spin circuit allowing expandable bitwidth by reproducing the Metropolis algorithm, which is SA with a fixed temperature, and (ii) an inter-chip interface (I/F) with a data-compression method utilizing annealing characteristics to obtain multi-chip operation without degrading annealing speed and accuracy. The CMOS-AP demonstrated multi-chip operation of the $9 imes16k$ spin system with an annealing speed $233 imes$ faster and a calculation energy $972 imes$ lower than running SG3 on a CPU.