Енергоспоживання та продуктивність моделей ші

Abstract

The increasing computational complexity of modern artificial intelligence (AI) models has led to a significant rise in energy consumption. The training and deployment of large-scale neural networks require substantial computational power, raising concerns about environmental sustainability. This paper examines energy efficiency issues in deep learning, the role of optical processors in AI acceleration, and the comparative performance of GPU and TPU architectures in training neural networks.