Renewable Energy, Google & AI
Yesterday I wrote an article about the lack of data on data centres within the new feature Google released to search for datasets. However in this article I had little focus on the great things that Google are doing. I will through this article only skim the surface focusing on the importance of responsible use of hardware.
According to a blog post from February Google is the world’s largest corporate purchaser of renewable energy. They are minimising the amount of energy they use. They refer to a new paper in Science that says the growth in energy use has slowed owing to efficiency gains. Thus keeping energy usage ‘almost flat’ across the globe’s data centres.
“The new study shows that while the amount of computing done in data centers increased by about 550 percent between 2010 and 2018, the amount of energy consumed by data centers only grew by six percent during the same time period.”
So if we consider these energy efficiency gains the technology industry is doing rather well to address the issues in regards to renewable energy.
“…outpaced anything seen in other major sectors of the economy.”
Data centres power a lot of applications around the world.
According to Google they still account for about 1 percent of global electricity consumption — the same proportion as in 2010 (although this sounds unlikely).
According to this argument Google considers that a person or company can “…immediately reduce the energy consumption associated with their computing simply by switching to cloud-based software.”
Google does eliminate waste in operations and designed highly efficient Tensor Processing Units. I have written about these previously.
The Google Edge TPU
The combination of custom hardware, open software, and state-of-the-art AI algorithms
These AI chips are part of the advances in machine learning.
They have outfitted all of our data centers with high-performance servers.
“Starting in 2014, we even began using machine learning to automatically optimize cooling in our data centers.”
They also took several measures deploying:
- Smart temperature
- Cooling controls
“…on average, a Google data center is twice as energy efficient as a typical enterprise data center. And compared with five years ago, we now deliver around seven times as much computing power with the same amount of electrical power.”
What does this result in?
- AI-powered recommendation system is already delivering consistent energy savings of around 30 percent on average.
- The average annual power usage effectiveness for our global fleet of data centers in 2019 hit a new record low of 1.10, compared with the industry average of 1.67 — meaning that Google data centers use about six times less overhead energy for every unit of IT equipment energy.
As such they seem to be delivering on their promises.
It seems a common measure Power Usage Effectiveness (PUE).
“…our best site could boast a PUE of less than 1.06 if we used an interpretation commonly used in the industry. However, we’re sticking to a higher standard because we believe it’s better to measure and optimize everything on our site, not just part of it. Therefore, we report a comprehensive trailing twelve-month (TTM) PUE of 1.11 across all our large-scale data centers (once they reach stable operations), in all seasons, including all sources of overhead.”
Google has data centres mainly in Europe and North America.
It seems Google has done some comprehensive work that has to be commended in attempting to fulfil their duties and expanding renewable energy around the world.
Although one can take a resource perspective and be critical of many practices one must admit that Google seems to be doing a lot to make sure they act responsibly with their operations.
When running artificial intelligence applications considering where your cloud is located is important, and to be honest on the surface Google seems like one of the best options if you consider responsible use of data centres.
This is #500daysofAI and you are reading article 323. I am writing one new article about or related to artificial intelligence every day for 500 days. My focus for day 300–400 is about AI, hardware and the climate crisis.