Lightning Talk: Energy-Efficient Deep Learning with PyTorch and Zeus - Jae-Won Chung

Lightning Talk: Energy-Efficient Deep Learning with PyTorch and Zeus - Jae-Won Chung, University of Michigan Until now, we just wanted to make things faster and faster. However, especially with the recent growth of GenAI, Deep Learning has become one of the primary workloads of cloud datacenters, which already take up 2-3% of the world's electricity usage. Therefore we ask: How much room are there for energy optimization? Can we get free energy reduction without slowdown? What knobs do we have available? How do we even measure energy consumption? In this talk, I aim to persuade the audience of the importance of regarding energy as a first-class metric for deep learning, and present the current state of deep learning energy optimization with Zeus (https://ml.energy/zeus). Integrated with PyTorch, Zeus provides convenient tools for GPU time and energy measurement inside user training scripts and transparently profile and optimize GPU-side knobs to maximize energy efficiency. Finally, I'll share our vision towards making sustainable deep learning as easy as possible while being mindful of existing important metrics such as speed and model quality.