Tuesday, May 21, 2024

As The Amount Of Electricity Required By Data Centers Heads Toward Half Of Current Generating Capacity....

Heads toward. We are nowhere near that point right now but that is the way things seem to be going. As promised in the intro to the post immediately below: "It may be super-smart to shovel some money Imec's way. More on that in the next post."

From a couple physics brainiacs writing at brainiac central, IEEE Spectrum, May 15:

Anna Herr has been a scientific director at Imec since May 2021. See full bio →
Quentin Herr has been a scientific director at Imec since May 2021. See full bio →

How to Put a Data Center in a Shoebox
Imec’s plan to use superconductors to shrink computers

Scientists have predicted that by 2040, almost 50 percent of the world’s electric power will be used in computing. What’s more, this projection was made before the sudden explosion of generative AI. The amount of computing resources used to train the largest AI models has been doubling roughly every 6 months for more than the past decade. At this rate, by 2030 training a single artificial-intelligence model would take one hundred times as much computing resources as the combined annual resources of the current top ten supercomputers. Simply put, computing will require colossal amounts of power, soon exceeding what our planet can provide.

One way to manage the unsustainable energy requirements of the computing sector is to fundamentally change the way we compute. Superconductors could let us do just that.

Superconductors offer the possibility of drastically lowering energy consumption because they do not dissipate energy when passing current. True, superconductors work only at cryogenic temperatures, requiring some cooling overhead. But in exchange, they offer virtually zero-resistance interconnects, digital logic built on ultrashort pulses that require minimal energy, and the capacity for incredible computing density due to easy 3D chip stacking.

Are the advantages enough to overcome the cost of cryogenic cooling? Our work suggests they most certainly are. As the scale of computing resources gets larger, the marginal cost of the cooling overhead gets smaller. Our research shows that starting at around 1016 floating-point operations per second (tens of petaflops) the superconducting computer handily becomes more power efficient than its classical cousin. This is exactly the scale of typical high-performance computers today, so the time for a superconducting supercomputer is now.

At Imec, we have spent the past two years developing superconducting processing units that can be manufactured using standard CMOS tools. A processor based on this work would be one hundred times as energy efficient as the most efficient chips today, and it would lead to a computer that fits a data-center’s worth of computing resources into a system the size of a shoebox.

The Physics of Energy-Efficient Computation...


Jensen Huang at Nvidia is very, very aware of the electrical consumption of chips in general and his in particular and I'm curious about his thinking regarding this complete revamp of mental and physical architecture.