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What is Gpu 2 about?
The document discusses the challenges and limitations of GPU memory and utilization estimation for training-aware resource management in deep learning. It categorizes existing estimation methods into analytical, library-based, and ML-based approaches, highlighting their respective drawbacks such as reliance on detailed model specifications and poor generalization. The authors introduce their own ML-based estimators, GPUMemNet and GPUUtilNet, and provide a comprehensive analysis of these methods while releas
- Author
- 2405723
- Language
- EN