Bridging the Cooling Gap to Support AI Computing Innovation
episode
The Fast Mode Podcasts: Breaking News, Analysis and Updates From Telecoms Industry
17 min
1 speaker
2 chapters
transcribed 1 month ago
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Welcome to the Fast Mode Podcast series. I'm Tara Neal, and with me today is Kevin Roof, the Global Director of Offer and Capture Management at Liquid Stack. Liquid Stack is a full service provider and pioneer of high-performance, energy-efficient liquid cooling solutions that solve the most challenging thermal management needs of generative AI and HPC workloads in centralized and Data centers worldwide. Kevin brings deep experience in data center liquid cooling with over a decade of experience in engineering and product management. Welcome Kevin. Great to have you on today's episode.
Yeah, appreciate you having me.
Awesome. Okay, so let's dive right in. We know there's a lot of talk about, you know, um data centers and the load that they are carrying because of these um you know, AI and Gen AI um processes and applications. So and and people are talking about, you know, how to keep data centers cool, to cater for these workloads. So um let's go back and and examine why can't current air cooling systems keep up with the heat produced by um new GPUs and processors?
Yeah, great, great question. So traditionally data centers are are are air cooled as a as a mode of of cooling the technology, the CPUs and GPUs that are that are in the IT racks in the data hall. Um but the the rate at which the GPU manufacturers are advancing this technology, it's it's scaling at such an incredible pace. They're they're packing more and more transistors into such a smaller physical die size and they're creating new architectures that are really um pushing the limits about what's what's capable and as a result they're gr generating um A lot more heat on their CPUs and GPUs. Uh we're seeing the what's called the TDP, and that's the the chip's thermal design power. It's it's rising at an unprecedented pace.
Um previously, prior to twenty twenty or so, we weren't seeing chip densities that were um going past seven hundred watts. And now that was a really dense, uh high density chip. But now today we're seeing nearly double that with one point two kilowatt chips. Point four kilowatt chips, and we're seeing indications from uh the GPU, CPU, and chip manufacturers that they're gonna be pushing that even further over the next three to five years. So it's really um pushing what air can do because to to cool these traditional technologies, what we're doing is uh directly attached to the chip, there is there's a heat sink and we're blowing air over that heat sink um with fins on it to to try to cool that chip.
But the challenge is there's a limitation to how much airflow we can move over over that chip because um we're driving such a large amount of air over a limited surface area. You can tr only blow so much air through such a small confined space.
Mm-hmm.
So if we kind of back that up and look at that that that's at the chip level, if we back up and look at it from a a rack, a pod level and a data center infrastructure, um we're seeing it scale there as well. Um traditionally, uh a few years ago, we wouldn't see a IT rack or a compute rack that was pushing over ten kilowatts power a rack. That was considered high density. Now we're we're really pushing the limits of that with what's going on with generative AI um and machine learning. We're seeing rack densities go well above eighty kilowatts of rack. Um we've been seeing in l re the recent years that that's scaling from 120, 130, 150 kilowatts of rack. Uh we've seen indications from from some of the GPU manufacturers um during their um conferences that they're announcing racks in 2027 that's gonna be 600 kilowatts a rack and then even by 2030 a megawatt of rack.
So it's just it's scaling so fast and the air cooling is just not not able to keep up with with that um because of limitations of of what it can do with air cool. Airflow.
Mm. Wow. Okay. So then comes uh liquid cooling, right? So what's liquid cooling and uh how does it solve these uh heat challenges you just mentioned? Um, you know, especially say in smaller or modular data centers.
Yeah, so there's a there's a couple ways to look at why liquid cooling is is a a more efficient and effective way to cool heat source.
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Chapters
2 chaptersSpeakers
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