Modern system-on-chips (SoC) integrate CPU and GPU for immersive 3D gaming experience. These games require both the CPU and GPU to work in tandem, resulting in high power consumption. In the past, Dynamic Voltage Frequency Scaling (DVFS) has been exploited for embedded CPU to save power during game play; but it is only recently that embedded GPUs have attained DVFS capabilities that provide additional opportunities. In this paper, we propose a power management approach that takes a unified view of the CPU-GPU DVFS, resulting in reduced power consumption for latest 3D mobile games compared to an independent CPU-GPU power management approach.
Current generation GPUs can accelerate high-performance, computeintensive applications by exploiting massive thread-level parallelism. The high performance, however, comes at the cost of increased power consumption. Recently, commercial GPGPU architectures have introduced support for concurrent kernel execution to better utilize the computational/memory resources and thereby improve overall throughput. In this paper, we argue and experimentally validate the benefits of concurrent kernels towards energyefficient execution. We design power-performance models to carefully select the appropriate kernel combinations to be executed concurrently, the relative contributions of the kernels to the thread mix, along with the frequency choices for the cores and the memory to achieve high performance per watt metric. Our experimental evaluation shows that the concurrent kernel execution in combination with DVFS can improve energy-efficiency by up to 34.5% compared to the most energy-efficient sequential execution.
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