3 ms·

I'm pretty sure that's actually wrong. Some math: A16 is 200 sq mm of silicon while an H100 is about 800. That means you get about 100-120 A16's on a wafer, wh

I'm pretty sure that's actually wrong. Some math: A16 is 200 sq mm of silicon while an H100 is about 800. That means you get about 100-120 A16's on a wafer, while you only get ~30 H100's (see https://www.silicon-edge.co.uk/j/index.php/resources/die-per-wafer https://www.silicon-edge.co.uk/j/index.php/resources/die-per...). Let's assume yield is 100% to make things easier. The rated max power of the A16 is about 250W, while the H100 is quoted at 700W. Thus, a wafer of A16's is about 25-30 kW of power, while a wafer of H100's is about 21 kW. Edit: Just clarifying, this is not about the Apple A16, but the Nvidia A16. The mobile process used by the Apple chips is built for much lower performance and power, so I can't imagine the two chips being anywhere near comparable - they fill two completely different roles.

wmf 3y ago
That's my point; if silicon demand shits from mobile to AI data centers you can't expect energy consumption to be the same.
- pclmulqdq 3y ago
  Demand right now is not shifting from mobile to datacenter, demand is shifting from "normal" datacenter compute to AI datacenter compute. I think if you had said "AMD Epyc" rather than a mobile chip, that would be a much more apt comparison. The AI chips are somewhat more power intensive per box, but fairly similar on power/area. It turns out that these silicon processes are fairly uniform in terms of the power/area that they can sustain for any kind of workload. Mobile chips are designed for <10% utilization and "rush-to-idle" workloads, and they are not remotely comparable to datacenter silicon (of any kind).