> GPUs are being limited for simulation (aka Nuclear weapons testing) reasons - not "AI"
that information seems dated in 2024
that information seems dated in 2024
You don't need bespoke cutting edge hardware or models for most defense applications (aka to kill people) today.
For example, C-RAMs are using Maxwell level hardware at most.
The biggest driver for GPU, FPGA, and CPU development has been nuclear research, and is a major reason why the top supercomputers and HPC programs globally are usually linked with Nuclear Weapons Labs (eg. LLNL, LBL, Argonne, Oak Ridge, NSC Guangzhou).
It just so happens that you use the same math for nuclear simulations as you would for "ML", bioinformatics, and computer graphics.
It's all Numerical Analysis and Optimization Theory at the end of the day.
> "What we cannot allow them to ship is the most sophisticated, highest-processing power AI chips, which would enable China to train their frontier models," she added.
[0] https://www.reuters.com/technology/us-talks-with-nvidia-abou...
No one wants to say the "Ne" word as it causes some pretty severe domestic political blowback.
Already China has been looking at countering American second strike capabilities with their nuclear weapons buildup over the past decade.
It also doesn't help that unlike most previous Premiers post-Mao, Xi Jinping started his administration career in the PLA.
And then, Sunway happened, it's built for military-use supercomputers. Do we even know whether it's 40nm, 28nm or 14nm or who on the earth fabricated them? And nothing changed on how export control works after that, that's certainly not the trigger.
GPU bans before ChatGPT happened were also targeted, similar to how BIS Entity List works.
Let's face it: the recent ban-entire-China movement was just about "AI", instead of HPC/simulations, the only purpose of it is to deny China NVIDIA GPU access and ensure they can't compete on SOTA language models.
Based on the network bandwidth and clock speed of the SW26010P, my hunch is most likely 40nm [0]
> ensure they can't compete on SOTA language models
I disagree.
For commercial NLP applications, a leading edge GPU like an A100 can help (due to cost constraints), but the true value is unlocked from Monte Carlo Simulations (heavily used in Nuclear Physics to simulate interactions among particles), as bechmacks have show magnitudes of performance in GPUs over CPUs for MC and MCMC simulations [1] just with commercial untuned hardware alone.
This itself was a major reason Nvidia has been working with the DoE since the beginning of the Exascale program [2], which itself was driven by NatSec priorities [3]
Raimondo's ban also came after the WSJ leaked how the CAEP and other sanctioned entities were accessing Nvidia GPUs despite an export ban since 1997 [4][5]
Of course this is dual use, as math is critical to everything, but at the end of the day - Nuclear Weapons is the driving factor and China's ability to erode American Nuclear Deterrence [6] and the fact that China now has a "launch-on-warning" posture [7] since 2022 instead of "on-launch" has severely spooked the US.
[0] - https://sc23.supercomputing.org/proceedings/tech_paper/tech_...
[1] - https://indico.cern.ch/event/1106990/contributions/4991264/a...
[2] - http://helper.ipam.ucla.edu/publications/nmetut/nmetut_19423...
[3] - https://www.exascaleproject.org/research-group/national-secu...
[4] - https://www.wsj.com/articles/chinas-top-nuclear-weapons-lab-...
[5] - https://www.federalregister.gov/documents/2022/06/30/2022-14...
[6] - https://direct.mit.edu/isec/article/47/4/147/115920/The-Dyna...
[7] - https://media.defense.gov/2023/Oct/19/2003323409/-1/-1/1/202...
Far safer, intellectually, to assume everything they omit to be a ploy, and to try to understand (with what limited information we have, comrade), the Real Juice.