most citedMeasuring the Energy Consumption and Efficiency of Deep Neural Networks: An Empirical Analysis and Design Recommendations

9 citations · 9 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2024★ 9 cited

Measuring the Energy Consumption and Efficiency of Deep Neural Networks: An Empirical Analysis and Design Recommendations

Charles Edison Tripp, Jordan Perr-Sauer, Jamil Gafur +4

Addressing the so-called ``Red-AI'' trend of rising energy consumption by large-scale neural networks, this study investigates the actual energy consumption, as measured by node-le…