Recalibrating global data center energy-use estimates

Status:: 🟩
Links:: Low-Carbon Data Centers

Metadata

Type:: #zotero/journalArticle
Authors:: Masanet, Eric; Shehabi, Arman; Lei, Nuoa; Smith, Sarah; Koomey, Jonathan
Title:: Recalibrating global data center energy-use estimates
Publication Title:: "Science"
Date:: 2020
URL:: https://www.science.org/doi/10.1126/science.aba3758

Bibliography

Masanet, E., Shehabi, A., Lei, N., Smith, S., & Koomey, J. (2020). Recalibrating global data center energy-use estimates. Science, 367(6481), 984–986. https://doi.org/10.1126/science.aba3758

Zotero

Zotero Tags:: #zotero/⏳ #zotero/climate_footprint

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Notes & Annotations

🟨 Note (last modified: 2023-04-04#16:51:58) (

89% des Bedarfs an Rechenleistung decken Amazon, Microsoft und Google ab

Die Cloud hat die Entwicklung hin zu immer größeren Rechenzentren begünstigt. Waren in den Nuller Jahren rund 79 Prozent der weltweiten Rechenzentren in der Hand kleiner und mittlerer Player, decken heutzutage die großen Tech-Firmen wie Amazon, Microsoft oder Google 89 Prozent des Bedarfs an Rechenzentrumsleistung ab.


🟨 Note (last modified: 2023-04-04#16:52:52) (

Rechenzentren in 2018: 1 % des globalen Energieverbrauchs


🟨 Note (last modified: 2023-04-04#16:53:20) (

Von 2010 - 2018 hat sich der Energieverbrauch von Rechenzentren nur um 6 % erhöht. Deutlich weniger als von vielen vorhergesagt.


📑 Annotations (imported on 2023-04-04#18:09:05)

masanet.etal.2020.recalibratingglobaldata (pg. 1)

Several oft-cited yet simplistic analyses claim that the energy used by the world’s data centers has doubled over the past decade and that their energy use will triple or even quadruple within the next decade (3–5). Such estimates contribute to a conventional wisdom (5, 6) that as demand for data center services rises rapidly, so too must their global energy use. But such extrapolations based on recent service demand growth indicators overlook strong countervailing energy efficiency trends that have occurred in parallel

masanet.etal.2020.recalibratingglobaldata (pg. 1)

By 2018, global data center workloads and compute instances had increased more than sixfold, whereas data center internet protocol (IP) traffic had increased by more than 10-fold (1). Data center storage capacity has also grown rapidly, increasing by an estimated factor of 25 over the same time period (1, 8).

masanet.etal.2020.recalibratingglobaldata (pg. 1)

But since 2010, electricity use per computation of a typical volume server—the workhorse of the data center—has dropped by a factor of four, largely owing to processorefficiency improvements and reductions in idle power (10).

masanet.etal.2020.recalibratingglobaldata (pg. 2)

In 2018, we estimated that global data center energy use rose to 205 TWh, or around 1% of global electricity consumption. This represents a 6% increase compared with 2010, whereas global data center compute instances increased by 550% over the same time period.

masanet.etal.2020.recalibratingglobaldata (pg. 2)

Notably, the new data also suggest a large decrease in the energy use of data center infrastructure systems (i.e., cooling and power provisioning), enough to mostly offset the growth in total IT device energy use. This decrease is explainable by ongoing shifts in servers away from smaller traditional data centers (79% of compute instances in 2010) and toward larger and more energyefficient cloud (including hyperscale) data centers (89% of compute instances in 2018) (see the second figure, third graph), which have much lower reported PUE values owing to cutting-edge cooling-system and power-supply efficiencies (1, 11).

masanet.etal.2020.recalibratingglobaldata (pg. 2)

Yet over the near term, market analysts predict that even greater levels of server virtualization are feasible (1), and technology studies indicate remaining potential for IT device efficiency gains, including more shifts to low-power storage devices (8).

masanet.etal.2020.recalibratingglobaldata (pg. 2)

On the infrastructure side, world-class hyperscale data centers are already operating with PUEs of 1.1 or lower, which is close to the practical minimum value.