EAR is an energy management framework for data centers. It offers a complete set of coordinated components covering different layers of the software stack: the EAR runtime, the EAR daemons running in compute nodes, EAR DB manager, taking care of DB accesses, the EAR global manager, controlling the total energy/power consumption, and the EAR plugin, taking care of notifications for job submissions.
The EAR Daemon and job submission plugin make EAR transparent to users offering the first, and probably main, goal of EAR: It must be EASY to use. By adding the EAR runtime to the equation, we add the second main capability: Energy efficiency.
EAR runtime offers energy optimization for mpi applications. It is driven by a highly efficient algorithm to automatically detect application loops. Once detected the application structure, application signature is computed per-iteration and used to apply energy models and policies. The output of the energy policy is the optimal CPU frequency for this region of code.
The presentation will provide an EAR overview but focussing on EAR runtime and EAR utilization by data center users. Given EAR reports data to a DB, using simple command line programs, EAR-aware users can easily collect advanced information from their jobs without having to use multiple external tools that many times needs root privileges or are difficult to understand.