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.

铁道车辆能耗的简易计算方法

评估列车能量消耗对促进铁道车辆节能十分重要。列车能量消耗可由全面的测量或数值仿真进行评估,但这些方法需要耗费大量的时间和精力。因此,我们开发出一种不用数值仿真评估能量消耗的简易计算方法。将测量结果与计算结果进行比较后表明,这种计算方法误差低于9%。