Energy-Aware GPU Programming at Source-Code Levels

作     者：Changyou Zhang Kun Huang Xiang Cui Yifeng Chen 

作者机构：Key Laboratory of High Confidence Software Technologies(Peking University)School of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2012年第17卷第3期

页      面：278-286页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 081201[工学-计算机系统结构] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by the National Natural Science Foundation of China (No. 61170053) the Natural Science Foundation of Beijing (No. 4112027) the China HGJ Significant Project (No. 2009ZX01036-001-002-4) 

主　　题：GPU power-aware source-code primitive 

摘      要：To enhance the energy efficiency and performance of algorithms with Graphics Processing Unit （GPU） accelerators in source-code development, we consider the power efficiency based on data transfer bandwidth and power consumption in key situations. First, a set of primitives is abstracted from program statements. Then, data transfer bandwidth and power consumption in different granularity sizes are consid- ered and mapped into proper primitives. With these mappings, a programmer can intuitively determine the power efficiency and performance in different running states of a thread. Finally, this intuition enables the programmer to tune the algorithm in order to achieve the best energy efficiency and performance. Using these power-aware principles, two Fast Fourier Transform （FFT） methods are compared. The mapping be- tween power consumption and primitives is helpful for algorithm tuning in source-code levels.