Energy-Aware GPU Programming at Source-Code Levels |
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Authors: | Changyou Zhang Kun Huang Xiang Cui Yifeng Chen |
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Institution: | ** Key Laboratory of High Confidence Software Technologies (Peking University) School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China |
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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. |
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Keywords: | GPU power-aware source-code primitive |
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