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Contents 28 S uper smarts How NREL uses AI Ops to save energy 30 E nergy efficient servers Intelligence cuts energy use 32 E +I Advertorial Busways to prevent arc flash 34 D emand response Data centers can save the utility grid but why should they? 37 K eeping up with 5G's power demands 5G is set to usher in higher data transfer speeds, enabling a new wave of computing technologies
Smart Energy: thinking how to cut energy use
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ork smarter, not harder. It's a good motto for life, but also for data center hardware and infrastructure. This special supplement is about how AI and human intelligence can be applied right now to digital infrastructure, to save Watts of power demand. We've mostly looked inside the facility, with a foray into the wider world.
Human intelligence has plenty to contribute, in redesigning racks, servers, and cooling systems, to reduce energy waste. We may be approaching the limits of efficiency achievable through the approach of PUE, which reduces the energy used in cooling the facility. The next step after that is to concentrate on the energy used in the IT equipment. Alex Alley tracks the trends in today's data centers, which may be pointing to a need for new ideas in future (p30).
Common sense can save lives
Supply and demand are well understood in economics, but in data centers, they are still getting to know each other (p34). Data centers want energy, they want reliability, and they also want to use renewable power sources. It's increasingly likely that they won't be able to get all three, unless they start work with the utilities. Renewables are intermittent. At a certain point, utilities can't switch on any more solar or wind power, until sites with stored power start to share it. That's the hurdle demandresponse is going to address - and it's a challenge for data centers to deliver on their promises to enable green energy.
and equipment lost to arc flash, according to E+I (p32). One way to reduce that risk is to use an intelligent design of busway, that includes protective housing and safety features.
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A high-performance computing site at an energy efficiency laboratory was a natural place to develop the use of AI to make computing itself more efficient. The US NREL institution found out that it takes a huge amount of data points and a lot of effort training up algorithms, to start to making its supercomputers run more efficiently, and to intervene when they work less well (p28). Another finding is that, even with this level of applied intellect, it's too early to completely hand over optimization to AI. We still need to check the working, or else the AI's recommendations run the risk of being impractical or just wrong.
5G could change everything - but only if we can actually provide the electric power it needs (p37). The history of cellular comms is a story of continuing change and improvement. Vlad-Gabriel Anghel shows how we can power the next revolution.
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