You should be looking at transistor amount if anything at all, “cuda cores” is only somewhat useful when looking at different products within the same generation.
It isn’t a major architecture update. Nvidia’s slides from Ampere’s release stated that the next two architectures after Ampere would be part of the same family.
Performance gains will be had by improving the RT & tensor cores, using an improved node, probably N4X, to facilitate clock speed increases at the same voltages, and by increasing the number of SMs across the product stack. The maturity of the 5nm process will allow Nvidia to use larger die than they could in Ada.
Am I reading those Cuda core projections right?
GA102 to AD102 increased by about 80%, but the jump from Ad102 to GB202 is only slightly above 30%, aside from no large gains going to 3nm?
Might not turn out that impressive after all.
You should be looking at transistor amount if anything at all, “cuda cores” is only somewhat useful when looking at different products within the same generation.
Still very accurate if you know what to look for.
For example, the reason why Ampere vs Turing CUDA cores scale different will let you predict how an Ampere GPU scales vs Turing GPU.
It’s also why we knew how Ada would scale linearly except with 4090 that was nerfed to be more efficient
I guess people don’t dig into white papers to learn about how and why the architectures perform as they do
It’s highly likely to be a major architecture update, so core count alone won’t be a good indicator of performance.
It isn’t a major architecture update. Nvidia’s slides from Ampere’s release stated that the next two architectures after Ampere would be part of the same family.
Performance gains will be had by improving the RT & tensor cores, using an improved node, probably N4X, to facilitate clock speed increases at the same voltages, and by increasing the number of SMs across the product stack. The maturity of the 5nm process will allow Nvidia to use larger die than they could in Ada.
lmao