Experimental evaluations of parallel tempering on an ising machine

Yosuke Mukasa, Shu Tanaka, Nozomu Togawa

Research output: Contribution to journalArticlepeer-review

Abstract

Ising machines have recently attracted much attention because they are expected to solve combinatorial optimization problems efficiently. We focus on an Ising machine whose algorithm is based on parallel tempering (PT), and experimentally evaluate the performance of the Ising machine for MIN-CUT problems. Experimental results show that the Ising machine outperforms a famous graph partitioning solver in terms of the quality of solution and the time-to-target-solution.

Original languageEnglish
Pages (from-to)27-29
Number of pages3
JournalIPSJ Transactions on System LSI Design Methodology
Volume14
DOIs
Publication statusPublished - 2021

Keywords

  • Combinatorial optimization problem
  • Ising machines
  • Ising model
  • Parallel tempering
  • Quadratic unconstrained binary optimization

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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