Performance Evaluation of CMOS Annealing with Support Vector Machine
Ryoga Fukuhara, Makoto Morishita, Takahiro Katagiri +3 more
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.
arXiv:2404.15752•IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)•Dec 16, 2024•1 citation