Enhancing Energy Efficiency with Multi-Site Scheduling Strategies

We analyze the energy efficiency of small application components across commodity resources. We demonstrate that 1) no single machine is ideal for all tasks examined, 2) the energy efficiency of an application varies by machine, and 3) runtime is insufficient to approximate energy consumption. These results illustrate that intelligent matching of tasks to machines has the potential to save without impacting performance.