arXiv:2404.15752 · IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)

Performance Evaluation of CMOS Annealing with Support Vector Machine

Ryoga Fukuhara, Makoto Morishita, Takahiro Katagiri, Masatoshi Kawai, Toru Nagai, Tetsuya Hoshino

Published Dec 16, 2024• 1 citation

Abstract

In this study, support vector machine (SVM) performance was assessed using a quantum-inspired complementary metal-oxide semiconductor (CMOS) annealer. During performance evaluation, the accuracy rate in binary classification problems was the primary focus. SVM performance, when running on a CPU (classical computation) and quantum-inspired annealer, was comparatively analyzed. The performance outcome was evaluated using a CMOS annealing machine, and accuracy rates of 93.7%, 92.7%, and 97.6% were obtained for linearly separable problem and nonlinearly separable problems 1 and 2, respectively. According to these results, a CMOS annealing machine can achieve an accuracy rate that closely rivals that of classical computation.

DOI: 10.1109/mcsoc64144.2024.00094

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