Energy Templates: Exploiting Application Information to Save Energy

In this work we consider a novel application centric approach for saving energy on large-scale parallel systems. By using a priori information on the expected application behavior we identify points at which processor-cores will wait for incoming data and thus may be placed in a low power state to save energy. The approach is general and complements many of the existing approaches that rely on saving energy at points of global synchronization. We capture the expected application behavior into an Energy Template whose purpose is to identify when cores are expected to be in an idle state and allow the runtime to use the template information and change the power state of the core. We prototype an Energy Template for a wave front algorithm that contains an complex processing pattern in which cores wait for incoming data before processing local data and whose wait-time varies from phase to phase. The implementation uses PMPI and requires minimal changes to the application code. Using a power instrumented cluster we demonstrate that using an Energy Template for the wave front application lowers the power requirements by 8% when using 216 cores, from the system maximum of 23%, and the energy requirements by 4%. We also show that the wave front's inherent parallel activity will lead to increased savings on larger systems.