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Our experimental results show that a GPU adopting our runtime dynamic voltage/frequency and core scaling technique can provide up to 38% (and nearly 20% on average) higher throughput than the baseline GPU under the same power constraint.
We quantify the impact of voltage and frequency scaling on each architecture with a particularly intriguing result that a cutting-edge Kepler-based GPU achieves energy saving of 75% by lowering GPU clocks in the best scenario, while Fermi- and Tesla-based GPUs achieve no greater than 40% and 13%, respectively.
On the basis of these findings, we propose a combined register-file and execution-unit throttling mechanism that smooths GPU voltage noise and reduces the guardband requirement by as much as 29%.
We find that there exists about 20% voltage guardband on those GPUs spanning two architectural generations, which, if "eliminated" completely, can result in up to 25% energy savings on one of the studied GPU cards.
Open accessProceedings ArticleDOI
03 Nov 2013
80 Citations
For all tested GPU applications, core voltage scaling is significantly effective to reduce system energy consumption.
However, by leveraging process variation, overclocking techniques can improve performance.
The effect of scaling core voltage/frequency and memory voltage/frequency depends on not only the GPU architectures, but also the characteristic of GPU applications.
This evidence encourages future work on the management of power and performance for GPU-accelerated systems to benefit from dynamic voltage and frequency scaling.
As microprocessors have substantial clock cycle time margin for yield, there is enough room for performance improvement by overclocking techniques.
Our experimental results show that the F-overclocking technique significantly improves performance as well as energy consumption.

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