@article{Zhang2012, 
author = {Changyou Zhang and Kun Huang and Xiang Cui and Yifeng Chen},
title = {Energy-Aware GPU Programming at Source-Code Levels},
year = {2012},
journal = {Tsinghua Science and Technology},
volume = {17},
number = {3},
pages = {278-286},
keywords = {GPU, power-aware, source-code, primitive},
url = {https://www.sciopen.com/article/10.1109/TST.2012.6216757},
doi = {10.1109/TST.2012.6216757},
abstract = {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 considered 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 between power consumption and primitives is helpful for algorithm tuning in source-code levels.}
}