Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/169020
Title: Design of CMOS Ising machine for combinatorial optimization problems
Authors: Su, Yuqi
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Su, Y. (2022). Design of CMOS Ising machine for combinatorial optimization problems. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/169020
Abstract: Combinatorial optimization problems (COPs), a subfield of mathematics, have significant importance in various fields, including artificial intelligence, machine learning, and software engineering. However, some COPs are ill-suited to conventional computers, as no efficient algorithms could provide their solution within polynomial time. A new computer architecture, the Ising machine, has been seen as a potential accelerator for solving COPs thanks to its high efficiency and straightforward hardware mapping. Compared to the quantum or optical Ising machine, the CMOS technology based Ising machine recently attracted much attention as a low-cost alternative. Nevertheless, there is significant room for improvement in this emerging area. In our works, we first built a digital compute-in-memory Ising machine, achieved 22 times speed up and more than 10x energy efficiency. Secondly, we built a reconfigurable Ising machine for solving a more general class of COPs. However, such circuits suffer from high area overhead due to complex multipliers and adders. To address the above issues, we proposed a memory centralized Ising machine with 8bit interaction coefficients and 12bit multiply-and-accumulate operators. It achieves 5-10 times area reduction and features chip-to-chip interfaces.
URI: https://hdl.handle.net/10356/169020
DOI: 10.32657/10356/169020
Schools: School of Electrical and Electronic Engineering 
Research Centres: Centre for Integrated Circuits and Systems 
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
Fulltext Permission: embargo_20250627
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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  Until 2025-06-27
This file is the thesis authored by Yuqi Su9.69 MBAdobe PDFUnder embargo until Jun 27, 2025

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