Authors: Gabriel Hautreux (CINES), Etienne Malaboeuf (CINES)
Abstract: This paper shows a parametric approach on how to reduce your energy footprint of an HPC system driven by GPUs at a large scale. Frequency capping as well as power capping approaches are tested and compared.
This study is performed on Adastra at CINES, the #11 system in top500 and #3 system in Green500.
We hope the results of this study will be of help to accelerators enabled HPC centers seeking to reduce their energy footprint by applying policies on either accelerators frequency or power capping at the node level.
Long Description: This paper shows a parametric approach on how to reduce your energy footprint of an HPC system driven by GPUs at a large scale. Frequency capping as well as power capping approaches are tested and compared.
This study is performed on Adastra at CINES, the #11 system in top500 and #3 system in Green500.
We hope the results of this study will be of help to accelerators enabled HPC centers seeking to reduce their energy footprint by applying policies on either accelerators frequency or power capping at the node level.
Paper: PDF