OPTIMIZATION OF NEURAL NETWORKS ENERGY CONSUMPTION: EFFICIENT APPROACHES TO REDUCING ENERGY USE WITHOUT SACRIFICING PERFORMANCE
Abstract
This article discusses effective approaches to reducing the energy consumption of neural networks without sacrificing performance and speed. Optimizing the energy consumption of neural networks is a crucial task in machine learning, as it directly impacts the cost and environmental sustainability of machine learning systems. The article will cover various aspects of optimizing the energy consumption of neural networks, including reducing precision, using low-power devices, and energy-efficient algorithms.
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