18 citations · 21 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 18 cited
Reducing Energy Bloat in Large Model Training
Jae-Won Chung, Yile Gu, Insu Jang +3
Training large AI models on numerous GPUs consumes a massive amount of energy, making power delivery one of the largest limiting factors in building and operating datacenters for A…
cs.LG2023★ 3 cited
Chasing Low-Carbon Electricity for Practical and Sustainable DNN Training
Zhenning Yang, Luoxi Meng, Jae-Won Chung +1
Deep learning has experienced significant growth in recent years, resulting in increased energy consumption and carbon emission from the use of GPUs for training deep neural networ…