Energy optimization of representative barrier algorithms

Too high energy consumption is widely recognized to be a critical problem in large-scale parallel computing systems.The LogP-based energy-saving model and the frequency scaling method were proposed to reduce energy consumption analytically and systematically for other two representative barrier algorithms:tournament barrier and central counter barrier.Furthermore,energy optimization methods of these two barrier algorithms were implemented on parallel computing platform The experimental results validate the effectiveness of the energy optimization methods.67.12％ and 70.95％ energy savings are obtained respectively for tournament barrier and central counter barrier on platforms with 2048 processes with 1.55％-8.80％ performance loss.Furthermore,LogP-based energy-saving analytical model for these two barrier algorithms is highly accurate as the predicted energy savings are within 9.67％ of the results obtained by simulation.