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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, the authors propose power-aware 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.
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