Enhancing the Solution Quality of Hardware Ising-Model Solver via Parallel Tempering

Abstract

We propose an efficient Ising processor with approximated parallel tempering (IPAPT) implemented on an FPGA. Hardware-friendly approximations of the components of parallel tempering (PT) are proposed to enhance solution quality with low hardware overhead. Multiple replicas of Ising states having different temperatures run in parallel by sharing a single network structure, and the replicas are exchanged based on the approximated energy evaluation. The application of PT substantially improves the quality of optimization solutions. The experimental results on the various max-cut problems have shown that utilization of PT significantly increases the probability of obtaining optimal solutions, and IPAPT obtains optimal solutions two orders magnitude faster than a software solver.