Whereas the
Top500 record ranks the five hundred greatest high-performance computer systems (HPCs) on the earth, its cousin the Green500 re-ranks the identical 500 supercomputers in accordance with their vitality effectivity. For the final three iterations of the record, Henri—a small supercomputer operated by the Flatiron Institute in New York—has been named the world’s most vitality environment friendly high-performance laptop. Constructed within the fall of 2022, Henri was the primary system to make use of Nvidia’s H100 GPU’s, aka Hopper.
To study the secrets and techniques of constructing and sustaining essentially the most energy-efficient supercomputer, we caught up with Henri’s architect,
Ian Fisk, who’s co-director of the Scientific Computing Core on the Flatiron Institute. Flatiron is an inner analysis division of the Simons Basis that brings collectively researchers utilizing fashionable computational instruments to advance our understanding of science.
The Flatiron Insitute’s Ian Fisk on…
IEEE Spectrum: The place did the identify Henri come from?
Ian Fisk: The identify took place for a foolish cause. Our earlier machine was known as Rusty. So, when requested by the seller what the machine identify was going to be, we stated, ‘nicely, by our naming conference, it’ll be Rusty, and it’s utilizing [Nvidia’s] H100 chip, so it’d be Rusty Hopper.’ However Rusty Hopper seems like a rustic singer from the Nineteen Eighties, in order that they didn’t need to name it that. And one of many Nvidia engineers who determined that you just may have the ability to really construct a machine that might make the top500 and be the highest of the Green500 had simply had a son named Henri. So, we had been requested by the seller if we would think about naming it after that particular person, which we thought was candy.
Because the Green500 measures efficiency per watt, it doesn’t matter how briskly you’re, it issues how briskly you’re for what number of watts you used. —Ian Fisk, Flatiron Institute
Did you got down to construct the world’s greenest supercomputer?
Fisk: Nvidia offered us that gear at an academic low cost worth partly as a result of we had been aiming for this benchmark. It was good for us as a result of it gave us some publicity, however we actually needed the {hardware} for the scientists, and it was a approach for us to get entry to H100s very early. However to try this, we needed to do the check in November 2022. So the gear got here to the loading dock in October, and it was assembled into a pc after which examined in document time. If there was an award for the quick 500, we might even be the winner.
The numbers within the first check run [November 2022] had been inferior to the second time [June 2023]. The second time when there was a little bit bit extra time to breathe, we upgraded the machine. It was larger: it was 80 GPUs the primary time and 144 the second time. It’s 2.7 petaflops, which for 2 racks of apparatus is an affordable dimension. It’s round 250 on the highest 500 largest supercomputers record. After which primary on the inexperienced 500 record.
Are you able to clarify your design selections when constructing Henri? Why Nvidia’s H100s?
Fisk: Our expertise with Nvidia, which works all the way in which again to
K40s, was that each era was about two to a few instances quicker than its predecessor. And that was actually true of all of the issues that led as much as it, just like the V100 and the A100. It’s about two and a half instances higher. We already had two racks of A100s, and when it got here time to improve the ability, H100s had been the factor to purchase.
The H100 on the time had been solely obtainable within the PCI related model, they didn’t have the NV-link possibility but. They usually didn’t have any water-cooled ones, so we had been utilizing air cooled programs once more. The GPUs earlier than that machine and after have all been water cooled programs, as a result of they’re just a bit bit extra environment friendly, and simpler to function as a result of you may eliminate much more warmth. However we selected it as a result of we had been anticipating very good efficiency numbers. And we received them, finally. With Nvidia, the software program and the {hardware} kind of come out on the similar time. And the efficiency tends to get higher over time as issues get optimized correctly.
The factor that separates a pc from a supercomputer is the low-latency cloth. And on nearly all programs proper now, that low-latency cloth is InfiniBand. The one individuals who present it’s Mellanox [Technologies], which was lately acquired by the NVIDIA Company, in order that they personal the entire stack.
[What] has allowed us to face on prime has been that expertise has developed to make use of extra energy slightly than be extra environment friendly. We didn’t count on to win greater than as soon as. —Ian Fisk, Flatiron Institute
There was one design alternative that was kind of thrust upon us that we’re revisiting proper now. Once we purchased the system, the one chassis that you might purchase had been PCI Gen 4, and the H100s use PCI Gen 5. As a result of it was Gen 4, we had been restricted by the communication velocity to the GPUs and to the InfiniBand playing cards. Once we began, we had HDR playing cards at 100 gigabits every. And we quickly found that that wasn’t going to be adequate to do a superb check for the Green500. So, we upgraded to 400 gigabits of InfiniBand on every node, and that helped some. Have we had PCIe Gen 5, we may have had two instances 400 gigabits, and that might have been even higher.
What optimizations did it’s important to do for the Green500 check?
Fisk: I believe doing the Green500 run is a little bit bit like being a hypermiler. You’ve a Honda Civic and also you drive throughout the nation getting sixty miles per gallon with the home windows closed AC off, and accelerating very slowly, however that’s not precisely the way in which you’d drive it in a rush to get someplace. As an illustration, while you do the Green500 run, the whole lot that doesn’t generate efficiency is turned down. There are huge solid-state drives on all the programs of this sort while you’re working in manufacturing, as a result of you’ll want to serve coaching samples to machine studying purposes. However they use energy, they usually don’t provide you with any efficiency, so these get turned off. It’s a little bit bit like a hypermiler taking the spare tire out of their automobile as a result of they needed to get higher mileage, nevertheless it’s not how they’d really drive it on a regular basis.
How have you ever been capable of preserve the number one spot for nearly two years?
Fisk: Definitely, the factor that may knock Henri off its perch would be the subsequent era of {hardware}. However I believe the factor that has allowed us to face on prime has been that expertise has developed to make use of extra energy slightly than be extra environment friendly. We didn’t count on to win greater than as soon as, we had been anticipating that individuals would come together with the water-cooled model of H100’s and be extra environment friendly than us, however that hasn’t occurred thus far.
The H100 is available in two fashions, the PCI model that plugs into the board as a card and the motherboard mount, it’s known as an SXM5. And the SXM5 is the NV-linked model. The large distinction is that there the SXM5 has a communication protocol between the GPUs that enables them to speak to one another at 900 gigabytes per second. It’s dramatically higher than something on InfiniBand. It’s actually what permits them to resolve issues like massive language fashions, as a result of while you’re doing these sorts of calculations, at every epoch, there is usually a large quantity of knowledge that has to stream backwards and forwards. So these communication hyperlinks are crucial, however additionally they use extra electrical energy. The LINPACK benchmark that they do for the green500 check advantages from a superb communication layer, however not at that stage.
The explanation why nobody has crushed the machine but is that the SXM5s really use much more electrical energy, they use 700 watts per GPU whereas ours solely use 350, and the efficiency [on things like the LINPACK test] just isn’t an element of two completely different. Because the green500 measures efficiency per watt, it doesn’t matter how briskly you’re, it issues how briskly you’re for what number of watts you used. And that’s the factor that we see with these PCI related H100s, they’re very exhausting to beat as a result of they don’t use a number of electrical energy they usually have comparable efficiency to the a lot greater wattage stuff on these sorts of calculations.
Do you count on to be the greenest supercomputer once more in Could?
Fisk: Effectively, we’re constructing a brand new machine with 96 GPUs, these would be the SXM5s, water-cooled NV-linked units. We are going to know quickly if they’ll have higher efficiency. As I discussed, they might be quicker, however they will not be extra environment friendly. However, one factor we discovered with our A100s was that a lot of the efficiency is obtainable within the first half the wattage, so that you get 90 % of the efficiency within the first 225 Watts. So, one of many issues that we’re going to attempt with the water-cooled system is to run it in energy capped mode, and see what sort of efficiency we get.
The long run goes to be costly. And the longer term goes to be very excessive powered. —Ian Fisk, Flatiron Institute
One good factor in regards to the water-cooled model is that it doesn’t want followers, as a result of the followers rely in opposition to your wattage. When these models are working, it’s about 4 kilowatts of energy per three models of house (3U). So it’s like forty 100 watt mild bulbs in a small field. Cooling that down requires blowing an incredible quantity of air throughout it, so you may have a couple of 100 watts of followers. And with water cooling, you simply have a central pump, which implies important financial savings. The warmth capability of water is about 4000 instances the warmth capability of air by quantity, so it’s important to use so much much less of it.
It’s going to be attention-grabbing to see the subsequent Green500 record in Could of this 12 months. We’ll see who comes alongside and whether or not no one beats us, or any individual beats us, or we beat ourselves. It’s all potential.
Fisk: The long run goes to be costly. And the longer term goes to be very excessive powered.
Once we began, the GPU was a specialised useful resource that was superb for machine studying and sure sorts of linear algebra calculations. At first, everybody used a single GPU. Then they began utilizing them collectively in teams the place they’d match their computation throughout a number of nodes, as much as eight nodes. Now, we’re seeing increasingly individuals who need to do tightly related massive language fashions, the place it requires 100 GPUs or a number of 100s of GPUs related in ways in which we by no means would have imagined.
For the subsequent set of assets we’re shopping for, the community connectivity is 16 instances higher than those that got here earlier than that. It’s an analogous set of apparatus, however these ones have 1.6 terabit of communication per node, as in comparison with 100 gigabits. And it makes the machines very costly, as a result of immediately the community cloth is a big issue within the buy worth, since you want heaps and plenty of InfiniBand switches and plenty of cables. And these are 800 gigabit—unique, very excessive efficiency cables.
With tightly related GPUs you may get fashions which have 10 to the ability of 10 parameters. And that is what’s actually driving that individual expertise. —Ian Fisk, Flatiron Institute
We count on there’ll be a number of people who find themselves working standard high-performance computing codes. However now there’s this new neighborhood that desires to make use of huge chunks of very precious assets, and we’re making an attempt to help these folks. It’s difficult, partly as a result of we’re competing with industries that do that, too. These sorts of assets are very exhausting to purchase, they’ve lengthy lead instances, they’re very costly, partly as a result of it’s pushed by the AI gold rush that is happening proper now. We’re making an attempt to determine our place in that, and so we’re shopping for a medium scale machine. And we don’t know what occurs after that.
Fisk: It’s a combination. I’d say, nonetheless 75 or 80 % is what I’d think about canned machine studying purposes. That is PyTorch primarily, the place persons are constructing fashions to make both simulation or prediction of varied issues, discovering correlations. This runs throughout the entire spectrum. We’ve received people who find themselves taking a look at perceive the AI and construct higher fashions. We even have people who find themselves engaged on issues like structural programs biology, in search of correlations of microbiome within the intestine. We have now folks engaged on protein construction, gene perform, taking a look at gene sequences, and utilizing machine studying methods to establish what’s happening.
The newest mission is named
Polymathic AI. A simplistic abstract can be one thing like ChatGPT for science. The thought is to make a big sufficient basis mannequin for science, the place you educate the AI algorithms so much about bodily processes, after which ask them to do issues like fluid dynamics simulations. It’s a really formidable mission. They usually’re making an attempt to determine get larger, scale up their work. And the thought behind that is that with tightly related GPUs you may get fashions which have 10 to the ability of 10 parameters. And that is what’s actually driving that individual expertise.
Henri is a workhorse machine. For those who go into the queue proper now, it’s fully full. If I needed to run one other inexperienced 500 check and say: ‘I’m going to take this factor offline for 2 weeks,’ I’d have riot on my fingers. There can be pitchforks outdoors my workplace. So sure, it’s a really inexperienced environment friendly laptop. However on the finish of the day, its legacy is all the wonderful science it permits.
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