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Memory Power-Performance Trade-Off based on SW Task Mapping and Graph Transformation

Führ (Onnebrink), G. ,  Aramburú, J. ,  Leupers, R. ,  Eusse, J. F.
Book Title:
The Thirteenth International Workshop on Programmability and Architectures for Heterogeneous Multicores
Jan. 2020


The contribution of memory power consumption can no longer be neglected for today’s heterogeneous multi-processor systems-on-chip. In addition, the hardware and software complexity necessitates fast and accurate compiler technology for determining the trade-off between performance and power. To cope with both constraints, this paper proposes a heuristic for automatic task-to-processor mapping based on task graph transformations. Moreover, a novel memory power model enables the power-driven optimisation. The approach is integrated into a commercially available framework for a detailed evaluation and tested against representative benchmarks on two diff erent platforms. Developed to minimise memory power under performance and power budget constraints, a reduction of up to 34 % memory power is possible, while the combined power consumption of the processor and the memory is decreased by 27 %. Further, the comparison with a processor power minimising approach rounds of the evaluation.