Automatic energy tuning of parallel applications on a hybrid supercomputer (2016–2019)
Energy efficiency is a critical challenge in building next generation supercomputers. While hardware components play a dominant role in saving energy, heterogeneous systems offer the opportunity to exploit the extremely high
concurrency with modest energy consumption using accelerators. Accordingly, the future of parallel computing must consider the tradeoff between obtaining the optimal performance and the allowed power budget. In this proposal, we plan to design parallel programming environments that support energy analysis and tuning. The project aims to provide a new energy-tuning tool integrated with Cray¿s systems, to simplify the process of tuning
hybrid applications and managing efficient energy utilization.