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Dynamic GPU Energy Optimization for Machine Learning Training Workloads. (arXiv:2201.01684v1 [cs.DC])
cs.LG updates on arXiv.org arxiv.org
GPUs are widely used to accelerate the training of machine learning
workloads. As modern machine learning models become increasingly larger, they
require a longer time to train, leading to higher GPU energy consumption. This
paper presents GPOEO, an online GPU energy optimization framework for machine
learning training workloads. GPOEO dynamically determines the optimal energy
configuration by employing novel techniques for online measurement,
multi-objective prediction modeling, and search optimization. To characterize
the target workload behavior, GPOEO utilizes GPU performance counters. To …
arxiv energy gpu learning machine machine learning optimization training