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From the article: > Liquid cooling is a familiar concept to PC enthusiasts, and has a long history in enterprise compute as well. And the trend in data center

From the article: > Liquid cooling is a familiar concept to PC enthusiasts, and has a long history in enterprise compute as well. And the trend in data centers was to move towards more passive cooling at the individual servers and hotter operating temperatures for a while. This is interesting because it reverses that trend a lot, and possibly because of the per-row cooling.

echelon 1y ago
This abundance of marketing (not necessarily this blog post) is happening because of all the environmental chatter about AI and data centers recently. Google wants you to know it recycles its water. It's free points. Edit: to clarify, normal social media is being flooded with stories about AI energy and water usage. Google isn't greenwashing, they're simply showing how things work and getting good press for something they already do.
- mlyle 1y ago
  Google uses plenty of water in cooling towers and chillers. Sure, water cooling loops to the server may reduce the amount a little bit compared to fans, but this isn't "recycling" in any normal sense. It's mostly a play for density.
- Legend2440 1y ago
  The environmental impact of water usage seems way overblown to me. Last year, U.S. data centers consumed 17 billion gallons of water. Which sounds like a lot, but the US as a whole uses 300 billion gallons of water every day. Water is not a scarce resource in much of the country.
  - foota 1y ago
    Personally, I agree. That said, I think it might be worth considering the impact of water usage in local areas that are relatively water constrained.
  - Guvante 1y ago
    To be clear all talk of water usage has been focusing on local usage which isn't well represented by national numbers.
    - abdullahkhalids 1y ago
      Yeah. There are metrics for how water stressed a community is. We know where data centers have been built, and we know how these water metrics have changed over time. The correct metric is something like, what's the probability that the launch of data center in a location results in nearby communities to drop significantly in these water metrics.
  - deleted 1y ago
    [deleted]
  - bee_rider 1y ago
    It seems like a very minor problem next to the huge super obvious one, electricity use.
- quickthrowman 1y ago
  Google almost certainly uses evaporative cooling towers, it’s almost twice as efficient as air cooled chillers by themselves.
dekhn 1y ago
We've basically been watching Google gradually re-discover all the tricks of supercomputing (and other high performance areas) over the past 10+ years. For a long time, websearch and ads were the two main drivers of Google's datacenter architecture, along with services like storage and jobs like mapreduce. I would describe the approach as "horizontal scaling with statistical multiplexing for load balancing". Those style of jobs worked well but as Google has realized it has more high performance computing with unique workload characteristics that are mission-critical (https://cloud.google.com/blog/topics/systems/the-fifth-epoch-of-distributed-computing https://cloud.google.com/blog/topics/systems/the-fifth-epoch...) their infrastructure has had to undergo a lot of evolution to adapt to that. Google PR has always been full of "look we discovered something important and new and everybody should do it", often for things that were effectively solved using that approach a long time ago. MapReduce is a great example of that- Google certainly didn't invent the concepts of Map or Reduce, or even the idea of using those for doing high throughput computing (and the shuffle phase of MapReduce is more "interesting" from a high performance computing perspective than mapping or reducing anyway).
- liquidgecka 1y ago
  As somebody that worked on Google data centers after coming from a high performance computing world I can categorically say that Google is not “re-learning” old technology. In the early days (when I was there) they focused heavily on moving from thinking of computers to thinking of compute units. This is where containers and self contained data centers came from. This was actually a joke inside of Google because it failed but was copied by all the other vendors for years after Google had given up on it. They then moved to stop thinking about cooling as something that happens within a server case to something that happens to a whole facility. This was the first major leap forward where they moved from cooling the facility and pushing conditioned air in to cooling the air immediately behind the server. Liquid cooling at Google scale is different than mainframes as well. Mainframes needed to move heat from the core out to the edges of the server where traditional data center cooling would transfer it away to be conditioned. Google liquid cooling is moving the heat completely outside of the building while it’s still liquid. That’s never been done before as far as I am aware. Not at this scale at least.

echelon 1y ago

This abundance of marketing (not necessarily this blog post) is happening because of all the environmental chatter about AI and data centers recently. Google wants you to know it recycles its water. It's free points. Edit: to clarify, normal social media is being flooded with stories about AI energy and water usage. Google isn't greenwashing, they're simply showing how things work and getting good press for something they already do.

mlyle 1y ago
Google uses plenty of water in cooling towers and chillers. Sure, water cooling loops to the server may reduce the amount a little bit compared to fans, but this isn't "recycling" in any normal sense. It's mostly a play for density.
Legend2440 1y ago
The environmental impact of water usage seems way overblown to me. Last year, U.S. data centers consumed 17 billion gallons of water. Which sounds like a lot, but the US as a whole uses 300 billion gallons of water every day. Water is not a scarce resource in much of the country.
- foota 1y ago
  Personally, I agree. That said, I think it might be worth considering the impact of water usage in local areas that are relatively water constrained.
- Guvante 1y ago
  To be clear all talk of water usage has been focusing on local usage which isn't well represented by national numbers.
  - abdullahkhalids 1y ago
    Yeah. There are metrics for how water stressed a community is. We know where data centers have been built, and we know how these water metrics have changed over time. The correct metric is something like, what's the probability that the launch of data center in a location results in nearby communities to drop significantly in these water metrics.
- deleted 1y ago
  [deleted]
- bee_rider 1y ago
  It seems like a very minor problem next to the huge super obvious one, electricity use.
quickthrowman 1y ago
Google almost certainly uses evaporative cooling towers, it’s almost twice as efficient as air cooled chillers by themselves.

dekhn 1y ago

We've basically been watching Google gradually re-discover all the tricks of supercomputing (and other high performance areas) over the past 10+ years. For a long time, websearch and ads were the two main drivers of Google's datacenter architecture, along with services like storage and jobs like mapreduce. I would describe the approach as "horizontal scaling with statistical multiplexing for load balancing". Those style of jobs worked well but as Google has realized it has more high performance computing with unique workload characteristics that are mission-critical (https://cloud.google.com/blog/topics/systems/the-fifth-epoch-of-distributed-computing https://cloud.google.com/blog/topics/systems/the-fifth-epoch...) their infrastructure has had to undergo a lot of evolution to adapt to that. Google PR has always been full of "look we discovered something important and new and everybody should do it", often for things that were effectively solved using that approach a long time ago. MapReduce is a great example of that- Google certainly didn't invent the concepts of Map or Reduce, or even the idea of using those for doing high throughput computing (and the shuffle phase of MapReduce is more "interesting" from a high performance computing perspective than mapping or reducing anyway).

liquidgecka 1y ago
As somebody that worked on Google data centers after coming from a high performance computing world I can categorically say that Google is not “re-learning” old technology. In the early days (when I was there) they focused heavily on moving from thinking of computers to thinking of compute units. This is where containers and self contained data centers came from. This was actually a joke inside of Google because it failed but was copied by all the other vendors for years after Google had given up on it. They then moved to stop thinking about cooling as something that happens within a server case to something that happens to a whole facility. This was the first major leap forward where they moved from cooling the facility and pushing conditioned air in to cooling the air immediately behind the server. Liquid cooling at Google scale is different than mainframes as well. Mainframes needed to move heat from the core out to the edges of the server where traditional data center cooling would transfer it away to be conditioned. Google liquid cooling is moving the heat completely outside of the building while it’s still liquid. That’s never been done before as far as I am aware. Not at this scale at least.