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Power management
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===DVFS techniques=== Experiments show that conventional processor DVFS policy can achieve power reduction of [[Embedded system|embedded]] GPUs with reasonable performance degradation.<ref>"[https://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6329290&tag=1 Dynamic voltage and frequency scaling framework for low-power embedded GPUs]", Daecheol You et al., Electronics Letters (Volume:48, Issue: 21 ), 2012.</ref> New directions for designing effective DVFS schedulers for heterogeneous systems are also being explored.<ref>"[http://dl.acm.org/citation.cfm?id=2571035 Effects of Dynamic Voltage and Frequency Scaling on a K20 GPU]", Rong Ge et al., 42nd International Conference on Parallel Processing Pages 826-833, 2013.</ref> A heterogeneous CPU-GPU architecture, GreenGPU<ref>"[http://dl.acm.org/citation.cfm?id=2410566 GreenGPU: A Holistic Approach to Energy Efficiency in GPU-CPU Heterogeneous Architectures]", Kai Ma et al., 41st International Conference on Parallel Processing Pages 48-57, 2012.</ref> is presented which employs DVFS in a synchronized way, both for GPU and CPU. GreenGPU is implemented using the CUDA framework on a real physical testbed with Nvidia GeForce GPUs and AMD Phenom II CPUs. Experimentally it is shown that the GreenGPU achieves 21.04% average [[energy savings]] and outperforms several well-designed baselines. For the mainstream GPUs which are extensively used in all kinds of commercial and personal applications several DVFS techniques exist and are built into the GPUs alone, [[AMD PowerTune]] and [[AMD ZeroCore Power]] are the two [[dynamic frequency scaling]] technologies for [[AMD]] graphic cards. Practical tests showed that reclocking a [[GeForce]] [[GTX 480]] can achieve a 28% lower power consumption while only decreasing performance by 1% for a given task.<ref>"[http://dl.acm.org/citation.cfm?id=2387879 Power and performance analysis of GPU-accelerated systems]", Yuki Abe et al., USENIX conference on Power-Aware Computing and Systems Pages 10-10, 2012.</ref>
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