Simulated Annealing is an optimization algorithm inspired by the annealing process in metallurgy. NEC Labs America applies simulated annealing to scheduling, network routing, and machine learning model training. This method efficiently finds near-optimal solutions in large, complex search spaces. By integrating simulated annealing with AI, NEC researchers improve decision-making in areas such as optical networking, infrastructure monitoring, and distributed computing systems.

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Accelerating Distributed Machine Learning with AllReduce Reconfiguration Based on Optical Circuit Switching

We propose to apply optical circuit switching to enable dynamic AllReduce reconfiguration for accelerating distributed machine learning. With simulated annealing-based optimization, theproposed AllReduce reconfiguration approach achieves 31% less average training time than existing solutions.