@conference {leng2015safe,
	title = {Safe Limits on Voltage Reduction Efficiency in GPUs: A Direct Measurement Approach},
	booktitle = {Microarchitecture (MICRO), 2015 48th Annual IEEE/ACM International Symposium on},
	year = {2015},
	pages = {294{\textendash}307},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Energy eciency of GPU architectures has emerged as an important aspect of computer system design. In this paper, we explore the energy benefits of reducing the GPU chip{\textquoteright}s voltage to the safe limit, i.e. Vmin point. We perform such a study on several commercial o↵- the-shelf GPU cards. We find that there exists about 20\% voltage guardband on those GPUs spanning two architectural generations, which, if {\textquotedblleft}eliminated{\textquotedblright} completely, can result in up to 25\% energy savings on one of the studied GPU cards. The exact improvement magnitude depends on the program{\textquoteright}s available guardband, because our measurement results unveil a program dependent Vmin behavior across the studied programs. We make fundamental observations about the programdependent Vmin behavior. We experimentally determine that the voltage noise has a larger impact on Vmin compared to the process and temperature variation, and the activities during the kernel execution cause large voltage droops. From these findings, we show how to use a kernel{\textquoteright}s microarchitectural performance counters to predict its Vmin value accurately. The average and maximum prediction errors are 0.5\% and 3\%, respectively. The accurate Vmin prediction opens up new possibilities of a cross-layer dynamic guardbanding scheme for GPUs, in which software predicts and manages the voltage guardband, while the functional correctness is ensured by a hardware safety net mechanism.},
	url = {https://doi.org/10.1145/2830772.2830811},
	author = {Leng, Jingwen and Buyuktosunoglu, Alper and Bertran, Ramon and Bose, Pradip and Reddi, Vijay Janapa}
}
