Power-efficient time-sensitive mapping in heterogeneous systems

  • Authors:

  • Cong Liu;Jian Li;Wei Huang;Juan Rubio;Evan Speight;Xiaozhu Lin

  • Affiliations:

  • University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;IBM Austin research laboratory, Austin, TX, USA;IBM Austin research laboratory, Austin, TX, USA;IBM Austin research laboratory, Austin, TX, USA;IBM Austin research laboratory, Austin, TX, USA;Rice University, Houston, TX, USA

  • Venue:
  • Proceedings of the 21st international conference on Parallel architectures and compilation techniques
  • Year:
  • 2012

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Abstract

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 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.