Title :
Electrical cost savings and clean energy usage potential for HPC workloads
Author :
Aikema, David ; Simmonds, Rob
Author_Institution :
Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB, Canada
Abstract :
Data centres containing high-performance computing (HPC) clusters may be able to coordinate with the operation of wind farms for mutual benefit. Large data centres consume megawatts of power, typically accounting for a majority of life cycle carbon emissions and a significant portion of the total cost of ownership. We ran simulations to explore the potential for data centres to adapt to dynamic electrical prices, variation in carbon intensity within an electrical grid, or the availability of local renewables. Using workloads from the Parallel Workloads Archive alongside real-world pricing data, we demonstrate potential savings on the cost of electricity ranging typically between 10-50%. Adaptation to the variation in the electrical grid carbon intensity was not as successful, but adaptation to the availability of local renewables showed potential to significantly increase their use. In one example the fraction of power obtained from a local wind installation increased by 10-80%.
Keywords :
energy consumption; power markets; wind power; HPC workloads; clean energy usage potential; electrical cost savings; high-performance computing clusters; wind farms; Availability; Carbon; Electric potential; Electricity; Power demand; Wind power generation; Wind turbines; Adaptive Scheduling; Environmental Economics; High performance computing; Simulation;
Conference_Titel :
Sustainable Systems and Technology (ISSST), 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-61284-394-0
DOI :
10.1109/ISSST.2011.5936911