Abstract
To improve the performance of the GPU, more parallelism should be exploited and the GPU should be operated at higher clock frequency. However, high parallelism and high clock frequency cause serious memory contention problems, resulting in significant power consumption and increased idle cycles in the GPU. This paper proposes a new memory contention aware (MC-aware) power management scheme to reduce the power consumption of the GPU with little impact on the performance. When serious memory contention problems occur in the GPU, the proposed MC-aware scheme changes the mode of the SM (Streaming Multiprocessor) to power saving mode with little performance degradation. The proposed scheme monitors the degree of memory contention, since severe memory contention causes serious performance degradation. The proposed GPU architecture includes SM management unit that generates the control signals based on the estimated degree of memory contention. According to our simulation results, the proposed MC-aware scheme can increase the power efficiency, IPC per watt, by up to 31.4% compared to the conventional architecture.
This study was financially supported by Chonnam National University. (Grant number: 2017-2727).
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This study was financially supported by Chonnam National University (Grant number: 2017-2727).
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Choi, H.J., Son, D.O., Kim, C.H. (2019). Memory Contention Aware Power Management for High Performance GPUs. In: Park, J., Shen, H., Sung, Y., Tian, H. (eds) Parallel and Distributed Computing, Applications and Technologies. PDCAT 2018. Communications in Computer and Information Science, vol 931. Springer, Singapore. https://doi.org/10.1007/978-981-13-5907-1_23
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DOI: https://doi.org/10.1007/978-981-13-5907-1_23
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