Neat. What about power density? An H100 has a TDP of 700 watts (for the SXM5 version). With a die size of 814 mm^2 that's 0.86 W/mm^2. If the cerebras chip has the same power density, that means a cerebras TDP of 37.8 kW. That's a lot. Let's say you cover the whole die area of the chip with water 1 cm deep. How long would it take to boil the water starting from room temperature (20 degrees C)? amount of water = (die…
100x defect tolerance: How we solved the yield problem
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Re: 100x defect tolerance: How we solved the yield problem
#72Earlier quoted context omitted.
I had been under the impression that Nvidia had done something similar here, but they did not talk about deploying the space saving design and instead only talked about the server rack where all of the chips on the mega wafer normally are. https://www.sportskeeda.com/gaming-tech/what-nvlink72-nvidia...
That shield is just a prop that looks nothing like the real product. The NVL72 rack doesn't use any wafer-scale-like packaging.
Re: 100x defect tolerance: How we solved the yield problem
#73Neat. What about power density? An H100 has a TDP of 700 watts (for the SXM5 version). With a die size of 814 mm^2 that's 0.86 W/mm^2. If the cerebras chip has the same power density, that means a cerebras TDP of 37.8 kW. That's a lot. Let's say you cover the whole die area of the chip with water 1 cm deep. How long would it take to boil the water starting from room temperature (20 degrees C)? amount of water = (die…
Re: 100x defect tolerance: How we solved the yield problem
#74Neat. What about power density? An H100 has a TDP of 700 watts (for the SXM5 version). With a die size of 814 mm^2 that's 0.86 W/mm^2. If the cerebras chip has the same power density, that means a cerebras TDP of 37.8 kW. That's a lot. Let's say you cover the whole die area of the chip with water 1 cm deep. How long would it take to boil the water starting from room temperature (20 degrees C)? amount of water = (die…
[1] https://en.wikipedia.org/wiki/Enthalpy_of_vaporization#Other... [2] https://cerebras.ai/product-system/
Re: 100x defect tolerance: How we solved the yield problem
#75I think this is an important step, but it skips over that 'fault tolerant routing architecture' means you're spending die space on routes vs transistors. This is exactly analogous to using bits in your storage for error correcting vs storing data. That said, I think they do a great job of exploiting this technique to create a "larger"[1] chip. And like storage it benefits from every core is the same and you don't nee…
Can you please explain more why you think so ?
Thank you.
Re: 100x defect tolerance: How we solved the yield problem
#76My biggest question is who are the buyers?
Re: 100x defect tolerance: How we solved the yield problem
#77Cerebras yields 46225 * .93 = 43000 square millimeters per wafer
NVIDIA yields 58608 * .92 = 54000 square millimeters per wafer
I don't know if their numbers are correct but it is a strange thing for a startup to brag that it is worse than a big company at something important.
Re: 100x defect tolerance: How we solved the yield problem
#78I think this is an important step, but it skips over that 'fault tolerant routing architecture' means you're spending die space on routes vs transistors. This is exactly analogous to using bits in your storage for error correcting vs storing data. That said, I think they do a great job of exploiting this technique to create a "larger"[1] chip. And like storage it benefits from every core is the same and you don't nee…
Re: 100x defect tolerance: How we solved the yield problem
#79Understanding that there's inherent bias by them being competitors of the other companies, but still this article seems to make some stretches. If you told me you had an 8% core defect rate reduced 100x, I'd assume you got to close to 99% enablement. The table at the end shows... Otherwise. They also keep flipping between cores, SMs, dies, and maybe other block sizes. At the end of the day I'm not very impressed. The…
> Despite having built the world’s largest chip, we enable 93% of our silicon area, which is higher than the leading GPU today.
The important part is building the largest chip. The icing on the top is that the enablement is not lower. Which it would be without the routing-to-spare-cores magic sauce.
And the differing terminology is because they're talking about differing things? You could call an SM a core, but it kind of contains (heterogeneous) cores itself. (I've no idea whether intra-SM cores can be redundant to boost yield.) A die is the part you break off and build a computer out of, it may contain a bunch of cores, a wafer can be broken up into multiple dies but for Cerebras it isn't.
If NVIDIA were to go and build a whole-wafer die, they'd do something similar. But Cerebras did it and got it to work. NVIDIA hasn't gotten into that space yet, so there's no point in building a product that you can't sell to a consumer or even a data center that isn't built around that exact product (or to contain a Balrog).
Re: 100x defect tolerance: How we solved the yield problem
#80I think this is an important step, but it skips over that 'fault tolerant routing architecture' means you're spending die space on routes vs transistors. This is exactly analogous to using bits in your storage for error correcting vs storing data. That said, I think they do a great job of exploiting this technique to create a "larger"[1] chip. And like storage it benefits from every core is the same and you don't nee…
Any thoughts on why they are disabling so many cores in their current product? I did some quick noodling based on the 46/970000 number and the only way I ended up close to 900,000 was by assuming that an entire row or column would be disabled if any core within it was faulty. But doing that gave me a ~6% yield as most trials had active core counts in the high 800,000s