National Key Laboratory of Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha 410073, China 在期刊界中查找 在百度中查找 在本站中查找
National Key Laboratory of Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha 410073, China 在期刊界中查找 在百度中查找 在本站中查找
National Key Laboratory of Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha 410073, China 在期刊界中查找 在百度中查找 在本站中查找
National Key Laboratory of Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha 410073, China 在期刊界中查找 在百度中查找 在本站中查找
National Key Laboratory of Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha 410073, China 在期刊界中查找 在百度中查找 在本站中查找
Based on the OpenMP-like parallel program, a loop scheduling and dynamic voltage scaling technology is coordinated to optimize system power consumption under the given performance constraint. First, the basic model for power-aware loop scheduling on the heterogeneous system is presented. After that, through theoretical analysis, it has been concluded that the lower bound of energy consumption for parallel loop scheduling on heterogeneous systems, can be used as a baseline to evaluate the efficiency of optimization technology. Furthermore, this paper induces the scheduling problem as a typical integer programming problem and proposes inner-processor loop re-scheduling method to further reduce power consumption. Finally, 10 typical kernel programs on a CPU-GPU heterogeneous system are created. The experimental results demonstrate that the proposed method can effectively reduce the total energy consumption of the whole system and improve the system energy efficiency.