Energy-Efficient AI: Green computing approaches for sustainable deep learning

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Authors: Mohammad Quayes Bin Habib, Razibul Islam Khan, MD ABDUR RAHIM, Kazi Wasi Uddin Shad, Muhammad Nesar Uddin
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Abstract

This paper explores energy-efficient AI techniques that emphasize green computing approaches to achieve sustainable deep learning. It highlights the critical role of optimizing hardware architectures and algorithmic strategies to reduce the environmental impact of AI training and inference, particularly in resource-constrained settings. By integrating advances in low-power AI hardware, approximate computing, and intelligent energy management, this research aims to pave the way for eco-friendly AI solutions that maintain performance while minimizing energy consumption.

Fields of Study & Subjects

Green IT and Sustainability Energy Efficiency in Computing Low-power high-performance VLSI design

Publication details

Journal / source
International Journal of Science and Research Archive
Volume
18
Issue
1
Pages
287–295
Publication date
16 January 2026