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Power-Efficient Time-Sensitive Mapping in Heterogeneous Systems

Cong Liu, Jian Li, Wei Huang, Juan Rubio, Evan Speight, Xiaozhu Lin
University of North Carolina at Chapel Hill
University of North Carolina at Chapel Hill, 2012

@article{liu2012power,

   title={Power-Efficient Time-Sensitive Mapping in Heterogeneous Systems},

   author={Liu, C. and Li, J. and Huang, W. and Rubio, J. and Speight, E. and Lin, X.},

   year={2012}

}

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Heterogeneous systems that contain multiple types of resources, such as CPUs and GPUs, are becoming increasingly popular thanks to the potential of achieving high performance and energy efficiency. In such systems, the problem of data mapping and communication for time-sensitive applications while reducing power and energy consumption is more challenging, since applications may have varied data management and computing patterns on different types of resources. In this paper, we propose power-aware data mapping techniques for CPU/GPU heterogeneous system that are able to meet applications’ timing requirements while reducing power and energy consumption by applying DVFS on both CPUs and GPUs. We have implemented the proposed techniques in a real CPU/GPU heterogeneous system. Experimental results with several data analytics workloads show that compared to performance-driven mapping, our power-efficient mapping techniques can often achieve a reduction of more than 20% in power and energy consumption.
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