Supercomputing’s Future Is Green and Interconnected


While 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 power 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 power environment friendly high-performance laptop. Built within the fall of 2022, Henri was the primary system to make use of Nvidia’s H100 GPU’s, aka Hopper.

To be taught 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 inside analysis division of the Simons Foundation that brings collectively researchers utilizing trendy computational instruments to advance our understanding of science.

The Flatiron Insitute’s Ian Fisk on…

IEEE Spectrum: Where did the title Henri come from?

Ian Fisk: The title took place for a foolish cause. Our earlier machine was known as Rusty. So, when requested by the seller what the machine title was going to be, we mentioned, ‘well, by our naming convention, it’ll be Rusty, and it’s utilizing [Nvidia’s] H100 chip, so it’d be Rusty Hopper.’ But Rusty Hopper feels like a rustic singer from the Eighties, in order that they didn’t need to name it that. And one of many Nvidia engineers who determined that you just would possibly be capable 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 have been requested by the seller if we would contemplate naming it after that particular person, which we thought was candy.

Since the Green500 measures efficiency per watt, it doesn’t matter how briskly you might be, it issues how briskly you might be 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 have 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 method for us to get entry to H100s very early. But 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 report time. If there was an award for the quick 500, we’d even be the winner.

The numbers within the first check run [November 2022] have been inferior to the second time [June 2023]. The second time when there was a bit of bit extra time to breathe, we upgraded the machine. It was greater: 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 inexpensive measurement. It’s round 250 on the highest 500 largest supercomputers record. And then primary on the inexperienced 500 record.

Can you clarify your design choices when constructing Henri? Why Nvidia’s H100s?

Fisk: Our expertise with Nvidia, which fits all the best way again to
K40s, was that each era was about two to 3 instances sooner 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 have been the factor to purchase.

The H100 on the time have been solely obtainable within the PCI related model, they didn’t have the NV-link choice but. And they didn’t have any water-cooled ones, so we have been utilizing air cooled techniques once more. The GPUs earlier than that machine and after have all been water cooled techniques, as a result of they’re just a bit bit extra environment friendly, and simpler to function as a result of you possibly can eliminate much more warmth. But we selected it as a result of we have been anticipating very good efficiency numbers. And we bought them, finally. With Nvidia, the software program and the {hardware} form 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 material. And on virtually all techniques proper now, that low-latency material is InfiniBand. The solely individuals who present it’s Mellanox [Technologies], which was just lately acquired by the NVIDIA Corporation, in order that they personal the entire stack.

[What] has allowed us to face on prime has been that expertise has advanced to make use of extra energy quite 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 form of thrust upon us that we’re revisiting proper now. When we purchased the system, the one chassis that you can purchase have been PCI Gen 4, and the H100s use PCI Gen 5. Because it was Gen 4, we have been restricted by the communication pace to the GPUs and to the InfiniBand playing cards. When 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 very good 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 might have had two instances 400 gigabits, and that might have been even higher.

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What optimizations did it’s important to do for the Green500 check?

Fisk: I feel doing the Green500 run is a bit of bit like being a hypermiler. You have 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 best way you’d drive it in a rush to get someplace. For occasion, once you do the Green500 run, all the things that doesn’t generate efficiency is turned down. There are massive solid-state drives on all the techniques of this sort once you’re operating in manufacturing, as a result of it is advisable to serve coaching samples to machine studying functions. But they use energy, and so they don’t provide you with any efficiency, so these get turned off. It’s a bit of 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 might really drive it on a regular basis.

How have you ever been capable of hold the number one spot for nearly two years?

Fisk: Certainly, the factor that may knock Henri off its perch would be the subsequent era of {hardware}. But I feel the factor that has allowed us to face on prime has been that expertise has advanced to make use of extra energy quite than be extra environment friendly. We didn’t count on to win greater than as soon as, we have been anticipating that folks would come together with the water-cooled model of H100’s and be extra environment friendly than us, however that hasn’t occurred up to now.

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 massive 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 unravel issues like giant language fashions, as a result of once you’re doing these sorts of calculations, at every epoch, there generally is a great quantity of knowledge that has to circulate 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 very good communication layer, however not at that stage.

The cause 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] shouldn’t be an element of two totally different. Since the green500 measures efficiency per watt, it doesn’t matter how briskly you might be, it issues how briskly you might be for what number of watts you used. And that’s the factor that we see with these PCI related H100s, they’re very laborious to beat as a result of they don’t use a variety of electrical energy and so they have related efficiency to the a lot larger wattage stuff on these sorts of calculations.

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Do you count on to be the greenest supercomputer once more in May?

Fisk: Well, we’re constructing a brand new machine with 96 GPUs, these would be the SXM5s, water-cooled NV-linked gadgets. We will know quickly if they may have higher efficiency. As I discussed, they might be sooner, however they will not be extra environment friendly. But, one factor we discovered with our A100s was that many of the efficiency is offered within the first half the wattage, so that you get 90 p.c of the efficiency within the first 225 Watts. So, one of many issues that we’re going to strive with the water-cooled system is to run it in energy capped mode, and see what sort of efficiency we get.

The future goes to be costly. And the long run goes to be very excessive powered. —Ian Fisk, Flatiron Institute

One good factor concerning the water-cooled model is that it doesn’t want followers, as a result of the followers depend towards your wattage. When these models are operating, 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 amazing quantity of air throughout it, so you possibly can 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 loads much less of it.

It’s going to be fascinating to see the subsequent Green500 record in May 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 attainable.

Fisk: The future goes to be costly. And the long run goes to be very excessive powered.

When we began, the GPU was a specialised useful resource that was excellent for machine studying and sure sorts of linear algebra calculations. At the start, everybody used a single GPU. Then they began utilizing them collectively in teams the place they might 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 giant 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 sources we’re shopping for, the community connectivity is 16 instances higher than those that got here earlier than that. It’s an identical 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 out of the blue the community material 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 facility of 10 parameters. And that is what’s actually driving that individual expertise. —Ian Fisk, Flatiron Institute

We count on there’ll be numerous people who find themselves operating typical high-performance computing codes. But now there’s this new group that wishes to make use of massive chunks of very beneficial sources, and we’re making an attempt to assist these folks. It’s difficult, partly as a result of we’re competing with industries that do that, too. These sorts of sources are very laborious 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 occurring 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.

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Fisk: It’s a combination. I’d say, nonetheless 75 or 80 p.c is what I’d contemplate canned machine studying functions. This 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 bought people who find themselves taking a look at the way to perceive the AI and construct higher fashions. We even have people who find themselves engaged on issues like structural techniques biology, on the lookout for correlations of microbiome within the intestine. We have folks engaged on protein construction, gene perform, taking a look at gene sequences, and utilizing machine studying strategies to determine what’s happening.

The most up-to-date venture 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 loads about bodily processes, after which ask them to do issues like fluid dynamics simulations. It’s a really bold venture. And they’re making an attempt to determine the way to get greater, the way to scale up their work. And the thought behind that is that with tightly related GPUs you may get fashions which have 10 to the facility of 10 parameters. And that is what’s actually driving that individual expertise.

Henri is a workhorse machine. If you go into the queue proper now, it’s totally 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 arms. There can be pitchforks outdoors my workplace. So sure, it’s a really inexperienced environment friendly laptop. But on the finish of the day, its legacy is all the wonderful science it allows.

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