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arXiv · 2404.15752

Performance Evaluation of CMOS Annealing with Support Vector Machine

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

In this paper, support vector machine (SVM) performance was assessed utilizing a quantum-inspired complementary metal-oxide semiconductor (CMOS) annealer. The primary focus during performance evaluation was the accuracy rate in binary classification problems. A comparative analysis was conducted between SVM running on a CPU (classical computation) and executed on a quantum-inspired annealer. The performance outcome was evaluated using a CMOS annealing machine, thereby obtaining an accuracy rate of 93.7% for linearly separable problems, 92.7% for non-linearly separable problem 1, and 97.6% for non-linearly separable problem 2. These results reveal that a CMOS annealing machine can achieve an accuracy rate that closely rivals that of classical computation.

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Ryoga Fukuhara, Makoto Morishita, Takahiro Katagiri, Masatoshi Kawai, Toru Nagai, Tetsuya Hoshino. 2024-04-24. Performance Evaluation of CMOS Annealing with Support Vector Machine. https://doi.org/10.1109/mcsoc64144.2024.00094

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