A GPU-Based Ising Machine With a Multi-Spin-Flip Capability for Constrained Combinatorial Optimization

A GPU-Based Ising Machine With a Multi-Spin-Flip Capability for Constrained Combinatorial Optimization

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Ising machines are domain-specific computers that solve combinatorial optimization problems (COPs).They utilize an Ising model to represent a COP and search for the optimal spin configuration of the Ising model to solve metabo 15-gauge finish nailer cordless the COP.Most Ising machines are based on simulated annealing (SA) and update the spin configuration according to single-spin-flip Markov Chain Monte Carlo methods.

However, supporting a multi-spin flip is important to enhance the search performance of SA-based Ising machines when constrained COPs are solved.In this paper, we extend the merge method, which was introduced to provide a multi-spin-flip capability for SA-based Ising machines, and formulate it as a series of matrix multiplications that can be executed on a graphics processing unit (GPU) efficiently.We then construct a GPU-based Ising machine that implements the GPU-oriented merge silver lining herbs kidney support method together with an extended SA algorithm.

We finally demonstrate its superiority over the state-of-the-art GPU-based Ising machine for quadratic knapsack problems.