What is it about?
Deep learning is revolutionizing numerous industries, but its growing energy consumption raises concerns. This research introduces FECoM, a tool that measures the energy usage of deep learning code at a fine-grained level. FECoM helps developers identify energy-hungry parts of their code, enabling targeted optimizations without compromising performance. By promoting energy-efficient AI development, FECoM contributes to reducing the environmental impact and costs of deep learning systems across various applications.
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This page is a summary of: Enhancing Energy-Awareness in Deep Learning through Fine-Grained Energy Measurement, ACM Transactions on Software Engineering and Methodology, July 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3680470.
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