Superconducting Computer: Imec's plan to shrink datacenters
spectrum.ieee.org
spectrum.ieee.org
One critical limitation is that information transfer from superconducting to regular wiring is relatively energy intensive, so a superconducting CPU won't actually result in advantages for input/output intensive processing. For processing heavy jobs though, if you don't have to shuffle data around the speed and energy savings will be very attractive.
the issue is that moving that data even to anything outside the core is cost about 100x that so the main every consumption for CPU is not in doing actual computation but in moving data around
That lets you speed up single-threaded execution more by adding more functional units (since you can't really jam the clock speed any more).
> To complement the logic architecture, we also redesigned a compatible Josephson-junction-based SRAM.
[...]
> But there are also some striking differences. First, most of the chip is to be submerged in liquid helium for cooling to a mere 4 K. This includes the SPUs and SRAM, which depend on superconducting logic rather than CMOS, and are housed on an interposer board. Next, there is a glass bridge to a warmer area, a balmy 77 K that hosts the DRAM. The DRAM technology is not superconducting, but conventional silicon cooled down from room temperature, making it more efficient. From there, bespoke connectors lead data to and from the room-temperature world.
... with the idea of stacking this technology to put a 'supercomputer in a shoebox':
> It is also straightforward to stack multiple boards of 3D superconducting chips on top of each other, leaving only a small space between them. We modeled a stack of 100 such boards, all operating within the same cooling environment and contained in a 20- by 20- by 12-centimeter volume, roughly the size of a shoebox. We calculated that this stack can perform 20 exaflops (in BF16 number format), 20 times the capacity of the largest supercomputer today. What’s more, the system promises to consume only 500 kilowatts of total power. This translates to energy efficiency one hundred times as high as the most efficient supercomputer today.
... or make datacenters a fraction of the size:
> In addition, with this technology we can engineer data centers with much smaller footprints. Drastically smaller data centers can be placed close to their target applications, rather than being in some far-off football-stadium-size facility.
- Superconductors are lossy with AC signals, is this loss not a big problem?
- Cooling things is very expensive, is this approach not simply transferring the costs to the cooling plant?
- I imagine that having a superconducting interconnect represents an impedance discontinuity, effects like the large kinetic inductances in superconducting materials have large ramifications on signal integrity. Any comments on how to deal with these problems? I worry when I see the words "top-down approach" towards this problem because from my experience it should be driven bottom-up. Superconducting circuits are not just: 'Oh it's lossless in DC, everything is great!' You have new limitations on trace dimensions because if you go too small or you drive too large a current you kill the superconducting state.
- NbTiN with amorphous Si as the barrier. How sensitive is the system to stray magnetic fields and stray radiation? If one of these structures switches into the normal state can it reset itself like sc photon detectors do or are the phonons trapped and the structure is latched in the normal state?
It's nice to see people working on this.
In this logic style, data are represented with fluxons. One fluxon is the quantum unit of flux. You can't have "half a fluxon" in a superconducting loop. In that sense it's actually "more digital than" anything in commercial CMOS chips. The circuit can still malfunction of course -- the failure mode looks like a fluxon failing to move from one logic stage to the next.
The real worry is that cryocooler though. Cryocoolers that can do liquid helium temperatures have efficiency ratings around 1%, so that 500kW shoebox is going to need an entire cooling tower attached to its refrigerator.
I don't understand, if these 500kW is the power consumed by a computation itself, or does the cooling equipment consumption included? To suck out 500kW of heat out of a shoebox box while keeping box's temperature at 4 kelvin... it seems to me impossible.
It is, IMO, a bit dubious whether or not anything is truly flowing in a superconductor at constant current. Electrons don't have identity, so the 'constant flow of electrons' can be rephrased as 'the physical system isn't changing'... and the degree to which you can tell that there are electrons moving about is also the degree to which the superconductor isn't truly zero-resistance.
Of course it isn't actually constant -- there are multiple electrons, and you can tell that the electron field is quantized. But the degree to which that is visible, is the exact degree to which the superconductor nevertheless doesn't superconduct!
You can't quote a number for the cryocooler without knowing how much heat is being injected into the thing it needs to keep below 4.2K.
The word "cooling" alone appears seven times, none of them in the context of specific power numbers.
Pretty clear to me.
> What’s more, the system promises to consume only 500 kilowatts of total power.
Also quite clear.
Exactly like I said.
Additionally, nowhere is it said that "the system" includes the cryocooler. Since IMEC doesn't make cryocoolers, it would be unreasonable to assume that their "system" includes one.
This quantum stuff is starting to get even more scammy than cryptocurrency.
> there is a glass bridge to a warmer area, a balmy 77 K that hosts the DRAM. The DRAM technology is not superconducting,
There is a lot of not-superconducting circuitry in that shoebox; without it you wouldn't have enough memory to do anything that qualifies as "AI".
The reasonable conclusion is that the power figure covers only the components they have described. Note that the article fails to mention the word "cryocooler" even once.
I know of other research groups (not IMEC) who are pretty shameless about excluding cryocooler power and cost from all of their press-release/popsci materials. It's considered acceptable in this field.
> We call it a superconductor processing unit (SPU), with embedded superconducting SRAM, DRAM memory stacks, and switches, all interconnected on silicon interposer ... Next, there is a glass bridge to a warmer area, a balmy 77 K that hosts the DRAM.
Having 20 exaflops in a 20x20x12 cm volume is cool, but aren't you going to need a memory bandwidth close (factor 10 - 1000 lets say depending on arithmetic intensity) to that to be useful? And total memory capacity as well. I feel like the bytes/second/area (bandwidth flux) would be the limiting factor to make use of that compute density
From the linked paper https://pubs.aip.org/aip/apl/article-abstract/122/18/182604/... the projected JSRAM density is 4MB/cm2 so barely anything on the SRAM front
OTOH I think there are theoretical lower bounds on the amount of energy that needs to be ejected as heat from a non-reversible computation, such that a non-reversible SC would still need to produce some heat.
Yes, it's called Landauer's principle, but it's so low it can be ignored for most intent and purposes.
Have AI models really been around for a decade?
seq2seq? attention model? BERT model?
At least 5 years old, if not 10.
Amazing to read through this though, as someone who's studied mostly traditional computer architecture this stuff is absolutely boggling.
https://stackoverflow.com/questions/32226993/understanding-s...
https://primo.ai/index.php?title=Processing_Units_-_CPU,_GPU...
I take issue with this though because the DSP/SIMD approach that GPUs and TPUs take is a subset of SMP/MIMD (symmetric multiprocessing and multiple instruction multiple data).
Where this matters is that today's neural networks are built on matrix operations, which is a narrow niche within computer science. A more general approach which would allow for faster evolution of the 20 or so other algorithms in AI would be to use compute clusters to explore genetic algorithms, simulated annealing and all the rest in playgrounds limited only by the developer's imagination. Loosely that would look like a desktop computer with perhaps 1000 or more cores appearing as a single CPU, that could be programmed in a language of choice like Erlang, Go, Julia, MATLAB, C/C++, etc (optionally using containerization tools like Docker). Or like having something akin to AWS EC2 locally.
I believe that this divergence in computing approaches is why Moore's Law ended around 2007 with emphasis switching to low cost and low power mobile and embedded systems. It's also why my heart fell out of programming and I stopped pursuing endlessly more photorealistic game engines that result in everyone making the same game over and over again.
If someone out there won the internet lottery and wants to invest in something truly disruptive, some low hanging fruit might be a highly scaled multicore RISC-V processor (as you mentioned) with 100-1000 cores running over 1 GHz using under 100 watts for under $1000. Targeting 10,000 to 100,000 cores by 2030 and 1 million cores shortly thereafter. That's the level of performance we should be expecting from companies like Intel, had Moore's Law continued. And it shows just how far expectations have fallen, with today's personal computers running little faster than those of 2010 for typical (non-GPU) workflows, tragically at the same price of $1000-3000.
I also wish that Imec would start with a consumer-level superconducting processor for under $1000, but unfortunately today's socioeconomic reality of widening wealth inequality doesn't support that. But it's easy enough to make liquid nitrogen from the air with a liquid nitrogen generator (looks like they start around $4000, that could/should be disrupted to $400 or less). Unfortunately their Josephson junctions still need liquid helium at 4k it looks like. Probably some company overseas will figure out a 77k liquid nitrogen version and bypass IP law, as these things tend to go lately.
So is Bitcoin still "evil"?