https://resources.nvidia.com/en-us-blackwell-architecture
Blackwell uses the TSMC 4NP process. It has two layers. A very back of the envelope estimate:
750mm^2 / (208/2) * 10^9 = 7211 nm^2
85 nm x 85 nm
It seems there is a huge market for inference.
Less programmable, but more throughput/power efficiency?
Traditional GPUs like Blackwell that can do anything and have backwards compatibility.
Less programmable and more ASIC-like inference chips like Google's TPUs. Inference market is going to be multiple times bigger than training soon.
ksec•2h ago
On another note I am waiting for Nvidia's entry to CPU. At some point down the line I expect the CPU will be less important, ( relatively speaking ) and Nvidia could afford to throw a CPU in the system as bonus. Especially when we are expecting ARM X930 to rival Apple's M4 in terms of IPC. CPU design has become somewhat of a commodity.
Incipient•2h ago
I don't have really solid evidence, just semi-anecdotal/semi-reliable internet posts:
Eg. https://www.tomshardware.com/tech-industry/more-than-251-mil...
Nvidia as a whole has been fairly anti-consumer recently with pricing, so I wouldn't be banking on them for a great cpu option. Weirdly Intel is in the position where they have to prove themselves, so hopefully they'll give us some great products in the next 2-5 years - if they survive (think the old lead-up-to-ryzen era for amd)
jonas21•1h ago
Haven't they already started doing this with Grace and GB10?
- https://www.nvidia.com/en-us/data-center/grace-cpu/
- https://nvidianews.nvidia.com/news/nvidia-puts-grace-blackwe...
wtallis•1h ago
GB10 when it ships might be more interesting, since it'll go into systems that need to support use cases other than merely feeding a big GPU ML workloads. But it sounds like the CPU chiplet at least was more or less outsourced to Mediatek.
xl-brain•59m ago