Skip to Main content Skip to Navigation
Conference papers

DVFS governor for HPC: Higher, Faster, Greener

Abstract : In High Performance Computing, being respectful of the environment is usually secondary compared to performance: The faster, the better. As Exascale computing is in the spotlight, electric power concerns arise as current exascale projects might need too much power to even boot. A recent incentive (Exascale at maximum 20MW) shows that reality is catching up with HPC center designers. Beyond classical works on hardware infrastructure or at the middleware level, we do believe that system-level solutions have great potential for energy reduction. Moreover energy-reduction has often been neglected by the HPC community that focus mainly on raw computing performance. In the literature, energy savings is achieved mainly by two means: Either processor load is the only metric taken into account to reduce processors frequency and to ensure no impact on raw performances, Or processor frequency is managed only at task level outside the critical path. In this article we show that designing and implementing a DVFS (Dynamic Voltage and Frequency Scaling) mechanism based on instantaneous system values (here network activity) can save up to 25% of energy consumption while reducing marginally performance. In several cases, reducing energy consumption also leads to an increase in performances because of the thermal budget of recent processors. This work is validated with real experiments on a Linux cluster using the NAS Parallel Benchmark (NPB).
Complete list of metadata

Cited literature [30 references]  Display  Hide  Download
Contributor : Open Archive Toulouse Archive Ouverte (OATAO) Connect in order to contact the contributor
Submitted on : Wednesday, October 26, 2016 - 10:56:22 AM
Last modification on : Wednesday, June 1, 2022 - 4:35:50 AM


Files produced by the author(s)



Georges da Costa, Jean-Marc Pierson. DVFS governor for HPC: Higher, Faster, Greener. 23rd Euromicro International Conference on Parallel, Distributed and network-based Processing (PDP 2015), Mar 2015, Turku, Finland. pp.533-540, ⟨10.1109/PDP.2015.73⟩. ⟨hal-01387826⟩



Record views


Files downloads