Energy Measurement of Compressed Deep Learning Models: A Literature Review
Model compression — quantization, pruning, and knowledge distillation — is widely adopted on the premise that a smaller model costs less energy to run. This review examines the measurement layer beneath that premise and finds it less settled than its adoption suggests. Drawing on a purposively assembled corpus of 53 wo...