Energy-aware high performance computing with graphic processing units

The use of Graphics Processing Units (GPUs) in general purpose computing has been shown to incur significant performance benefits, for applications ranging from scientific computing to database sorting and search. The emergence of high-level APIs facilitates GPU programming to the point that general purpose computing with GPUs is now considered a viable system design and programming option. Nevertheless, the inclusion of a GPU in general purpose computing results in an associated increase in the system's power budget. This paper presents an experimental investigation into the power and energy cost of GPU operations and a cost/performance comparison versus a CPU-only system. Through real-time energy measurements obtained using a novel platform called LEAP-Server, we show that using a GPU results in energy savings if the performance gain is above a certain bound. We show this bound for an example experiment tested by LEAP-Server.