And also:
Reddy, V. D., Setz, B., Rao, G. S. V. R. K., Gangadharan, G. R., & Aiello, M. (2017). Metrics for Sustainable Data Centers. IEEE Transactions on Sustainable Computing, 2(3), 290β303. https://doi.org/10.1109/TSUSC.2017.2701883
PUE describes how efficiently a data center uses energy: How much energy is used for the IT equipment in contrast to cooling and other overhead that supports the equipment.
Ideal PUE value is 1.
Limitations
shehabi.etal.2016.unitedstatesdata (pg. 57)
The limitations of PUE, the most commonly discussed metric of efficiency, are generally understood, but a key issue it that PUE only measures the efficiency of the building infrastructure supporting a given data center and indicates nothing about the efficiency of the IT equipment itself.
β PUE indicates nothing about the efficiency of the IT equipment. A great PUE value can be almost useless if the IT equipment is highly inefficient. This also includes the wasted energy of idle servers.
Example:
In a data center with a PUE (power usage effectiveness) of 1.65, the IT equipment represents 61% of the power demand, whereas in a data center with a PUE of 1.1, it represents 91%.
β Lawrence, A., & Dietrich, J. M. (2022)
shehabi.etal.2016.unitedstatesdata (pg. 34)
The slower rate of efficiency improvement in PUE relative to IT equipment is partially due to the slower turnover rate of a data centerβs infrastructure relative to the IT equipment. The opportunities to improve data center PUE increase with larger data centers that have the ability to develop better airflow management and employ more efficient cooling equipment or advanced cooling technologies such as liquid cooling. Consequently, smaller data centers are still being measured with PUE values greater than 2.037 while large hyperscale cloud data centers are beginning to record PUE value of 1.1 or less.
β To increase the PUE you have to change the data center's infrastructure. The turnover rate of such a change is slower than changing the IT equipment. Only big data centers are able to make such an investment, e.g. to develop a better airflow management or employ more efficient cooling equipment.
davis.etal.2022.uptimeinstituteglobal (pg. 7)
Relying too heavily on PUE as the industryβs key efficiency metric may reduce operatorsβ motivation to pursue IT efficiency improvements.
