TY - GEN
T1 - An Automated Toolchain for QUBO-based Optimization with Quantum-inspired Annealers
AU - Zhang, Yun Ting
AU - Nien, Chin Fu
AU - Lin, Chia Wei
AU - Chao, Wen Jui
AU - Liu, Chen Yu
AU - Yu, Lien Po
AU - Chen, Yuan Ho
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Recently, quantum computers have drawn attention to their potential to solve problems faster than classical computers. However, quantum hardware's limited practicality and scalability have led to an interest in alternative approaches to solving optimization problems. One such approach is classical quantum-inspired annealers, which provide efficient and scalable solutions for combinatorial optimization problems (COPs) using classical hardware. To use annealers, COPs must be formulated as quadratic unconstrained binary optimization (QUBO) forms. Current tools require coding expertise and manual parameter tuning, posing barriers to entry. To address these challenges, we developed a user-friendly software toolchain that offers several advantages. Our toolchain features a friendly input and output interface, an automated parameter tuner, and a library of commonly encountered COPs. Our software toolchain's accessibility promotes the use of quantum-inspired annealers and accelerates the development of practical solutions for real-world problems.
AB - Recently, quantum computers have drawn attention to their potential to solve problems faster than classical computers. However, quantum hardware's limited practicality and scalability have led to an interest in alternative approaches to solving optimization problems. One such approach is classical quantum-inspired annealers, which provide efficient and scalable solutions for combinatorial optimization problems (COPs) using classical hardware. To use annealers, COPs must be formulated as quadratic unconstrained binary optimization (QUBO) forms. Current tools require coding expertise and manual parameter tuning, posing barriers to entry. To address these challenges, we developed a user-friendly software toolchain that offers several advantages. Our toolchain features a friendly input and output interface, an automated parameter tuner, and a library of commonly encountered COPs. Our software toolchain's accessibility promotes the use of quantum-inspired annealers and accelerates the development of practical solutions for real-world problems.
KW - Ising machines
KW - quadratic unconstrained binary optimization (QUBO)
KW - Quantum-inspired annealers
UR - http://www.scopus.com/inward/record.url?scp=85184828846&partnerID=8YFLogxK
U2 - 10.1109/ISOCC59558.2023.10396459
DO - 10.1109/ISOCC59558.2023.10396459
M3 - Conference contribution
AN - SCOPUS:85184828846
T3 - Proceedings - International SoC Design Conference 2023, ISOCC 2023
SP - 171
EP - 172
BT - Proceedings - International SoC Design Conference 2023, ISOCC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th International SoC Design Conference, ISOCC 2023
Y2 - 25 October 2023 through 28 October 2023
ER -