research-article

Adaptive Bulk Search: Solving Quadratic Unconstrained Binary Optimization Problems on Multiple GPUs

Authors:

Masaru Tatekawa,

Takashi Yazane,

Yoko InabaAuthors Info & Claims

ICPP '20: Proceedings of the 49th International Conference on Parallel Processing

Article No.: 62, Pages 1 - 11

https://doi.org/10.1145/3404397.3404423

Published: 17 August 2020 Publication History

Abstract

The quadratic unconstrained binary optimization (QUBO) is recently gathering attention in conjunction with quantum annealing (QA), since it is equivalent to finding the ground state of an Ising model. Due to the limitation of current QA systems, classical computers may outperform them. Researchers have thus been proposed to solve QUBO on FPGAs, GPUs, and special purpose processors. In this paper, we propose an adaptive bulk search (ABS), a framework for solving QUBO that can perform many searches in parallel on multiple GPUs. It supports fully-connected Ising models with up to 32k spins and 16-bit weights. In our ABS, a CPU host performs genetic algorithm (GA) while GPUs asynchronously perform local searches. A bottleneck for solving QUBO exists in the evaluation of the energy function, which requires computational cost for each solution. We show this can be reduced to in our ABS. The experimental results show that, with four NVIDIA GeForce RTX 2080 Ti GPUs, our framework can search up to 1.24 × 1012 solutions per second. We also show that our system quickly solves maximum cut and traveling salesman problems.

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Cited By

Chen YHua HNien CLin S(2024)VLSI Implementation of an Annealing Accelerator for Solving Combinatorial Optimization ProblemsIEEE Nanotechnology Magazine10.1109/MNANO.2024.337848318:3(23-30)Online publication date: Jun-2024
https://doi.org/10.1109/MNANO.2024.3378483
Li XNakano KTsukiyama SIto YKato TKawamata Y(2024)Generating hard quadratic unconstrained binary optimization instances via the method of combining bit reduction and duplication techniqueInternational Journal of Parallel, Emergent and Distributed Systems10.1080/17445760.2024.237692839:5(589-608)Online publication date: 9-Jul-2024
https://doi.org/10.1080/17445760.2024.2376928
Pauckert JDebevere PParizy MAyodele MSilva SPaquete L(2023)Comparing Solution Combination Techniques in Scatter Search for Quadratic Unconstrained Binary OptimizationProceedings of the Companion Conference on Genetic and Evolutionary Computation10.1145/3583133.3596319(2241-2249)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583133.3596319
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cover image ACM Other conferences

ICPP '20: Proceedings of the 49th International Conference on Parallel Processing

August 2020

844 pages

ISBN:9781450388160

DOI:10.1145/3404397

Copyright © 2020 ACM.

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Published: 17 August 2020

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ICPP '20

ICPP '20: 49th International Conference on Parallel Processing

August 17 - 20, 2020

AB, Edmonton, Canada

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Overall Acceptance Rate 91 of 313 submissions, 29%

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Cited By

Chen YHua HNien CLin S(2024)VLSI Implementation of an Annealing Accelerator for Solving Combinatorial Optimization ProblemsIEEE Nanotechnology Magazine10.1109/MNANO.2024.337848318:3(23-30)Online publication date: Jun-2024
https://doi.org/10.1109/MNANO.2024.3378483
Li XNakano KTsukiyama SIto YKato TKawamata Y(2024)Generating hard quadratic unconstrained binary optimization instances via the method of combining bit reduction and duplication techniqueInternational Journal of Parallel, Emergent and Distributed Systems10.1080/17445760.2024.237692839:5(589-608)Online publication date: 9-Jul-2024
https://doi.org/10.1080/17445760.2024.2376928
Pauckert JDebevere PParizy MAyodele MSilva SPaquete L(2023)Comparing Solution Combination Techniques in Scatter Search for Quadratic Unconstrained Binary OptimizationProceedings of the Companion Conference on Genetic and Evolutionary Computation10.1145/3583133.3596319(2241-2249)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583133.3596319
Yasudo R(2023)Bandit-based Variable Fixing for Binary Optimization on GPU Parallel Computing2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)10.1109/PDP59025.2023.00031(154-158)Online publication date: Mar-2023
https://doi.org/10.1109/PDP59025.2023.00031
Li XNakano KIto YTakafuji DYazane TYano JKato TOzaki SMori RKatsuki R(2023)Bit duplication technique to generate hard quadratic unconstrained binary optimization problems with adjustable sizesConcurrency and Computation: Practice and Experience10.1002/cpe.796736:10Online publication date: 20-Nov-2023
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Li XNakano KIto YTakafuji DYazane TYano JOzaki SKatsuki RMori R(2022)Bit duplication technique to generate hard QUBO problems2022 Tenth International Symposium on Computing and Networking Workshops (CANDARW)10.1109/CANDARW57323.2022.00029(180-184)Online publication date: Nov-2022
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Imanaga TNakano KYasudo RIto YKawamata YKatsuki ROzaki SYazane THamano K(2021)Solving the sparse QUBO on multiple GPUs for Simulating a Quantum Annealer2021 Ninth International Symposium on Computing and Networking (CANDAR)10.1109/CANDAR53791.2021.00011(19-28)Online publication date: Nov-2021
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Kagawa HIto YNakano KYasudo RKawamata YKatsuki RTabata YYazane THamano K(2021)High‐throughput FPGA implementation for quadratic unconstrained binary optimizationConcurrency and Computation: Practice and Experience10.1002/cpe.656535:14Online publication date: 19-Aug-2021
https://doi.org/10.1002/cpe.6565
Kagawa HIto YNakano KYasudo RKawamata YKatsuki RTabata YYazane THamano K(2020)Fully-Pipelined Architecture for Simulated Annealing-based QUBO Solver on the FPGA2020 Eighth International Symposium on Computing and Networking (CANDAR)10.1109/CANDAR51075.2020.00013(39-48)Online publication date: Nov-2020
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Imanaga TNakano KTao MYasudo RIto YKawamata YKatsuki RTabata YYazane THamano K(2020)Efficient GPU Implementation for Solving the Maximum Independent Set Problem2020 Eighth International Symposium on Computing and Networking (CANDAR)10.1109/CANDAR51075.2020.00012(29-38)Online publication date: Nov-2020
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