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Nvidia still sells GPUs to China, they made special SKUs specifically to slip under the spec limits imposed by the sanctions: https://www.tomshardware.com/news

Nvidia still sells GPUs to China, they made special SKUs specifically to slip under the spec limits imposed by the sanctions: https://www.tomshardware.com/news/nvidia-reportedly-creating-new-rtx-4090-d-dragon-gpu-to-comply-with-us-export-regulations-for-china https://www.tomshardware.com/news/nvidia-reportedly-creating... Those cards ship with 24GB of VRAM but supposedly there's companies doing PCB rework to upgrade them to 48GB: https://videocardz.com/newz/nvidia-geforce-rtx-4090d-with-48gb-and-rtx-4080-super-32gb-now-offered-in-china-for-cloud-computing https://videocardz.com/newz/nvidia-geforce-rtx-4090d-with-48... Assuming the regular SKUs aren't making it into China anyway through back channels...

hyperknot 2y ago
There was also a video where they are resoldering memory chips on gaming grade cards to make them usable for AI workloads.
- ipsum2 2y ago
  That only works for inference, not training.
  - willy_k 2y ago
    Why so?
    - miki123211 2y ago
      Because training usually requires bigger batches, doing a backward pass instead of just the forward pass, storing optimizer states in memory etc. This means it takes a lot more RAM than inference, so much more that you can't run it on a single GPU. If you're training on more than one GPU, the speed at which you can exchange data between them suddenly becomes your bottleneck. To alleviate that problem, you need extremely fast, direct GPU-to-GPU "interconnect", something like NV Link for example, and consumer GPUs don't provide that. Even if you could train on a single GPU, you probably wouldn't want to, because of the sheer amount of time that would take.
      - elashri 2y ago
        But does this prevent usage of cluster or consumer GPUs to be used in training? Or does it just make it slower and less efficient? Those are real questions and not argumentative questions.
        blackoil 2y ago
        Consumer GPUs don't have Nvlink so they don't work very well in cluster.
paxys 2y ago
A company of Alibaba's scale probably isn't going to risk evading US sanctions. Even more so considering they are listed in the NYSE.
- deleted 2y ago
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- griomnib 2y ago
  NVIDIA sure as hell is trying to evade the spirit of the sanctions. Seriously questioning the wisdom of that.
  - nl 2y ago
    > the spirit of the sanctions What does this mean? The sanctions are very specific on what can't be sold, so the spirit is to sell anything up to that limit.
    - chronic74930791 2y ago
      > What does this mean? The sanctions are very specific on what can't be sold, so the spirit is to sell anything up to that limit. 25% of Nvidia revenue comes from the tiny country of Singapore. You think Nvidia is asking why? (Answer: they aren’t)
      - bovinejoni 2y ago
        Not according to their reported financials. You have a source for that number?
        umeshunni 2y ago
        https://www.cnbc.com/amp/2023/12/01/this-tiny-country-drove-15percent-of-nvidias-revenue-heres-why-it-needs-so-many-chips.html https://www.cnbc.com/amp/2023/12/01/this-tiny-country-drove-... About 15% or $2.7 billion of Nvidia's revenue for the quarter ended October came from Singapore, a U.S. Securities and Exchange Commission filing showed. Revenue coming from Singapore in the third quarter jumped 404.1% from the $562 million in revenue recorded in the same period a year ago.

hyperknot 2y ago

There was also a video where they are resoldering memory chips on gaming grade cards to make them usable for AI workloads.

ipsum2 2y ago
That only works for inference, not training.
- willy_k 2y ago
  Why so?
  - miki123211 2y ago
    Because training usually requires bigger batches, doing a backward pass instead of just the forward pass, storing optimizer states in memory etc. This means it takes a lot more RAM than inference, so much more that you can't run it on a single GPU. If you're training on more than one GPU, the speed at which you can exchange data between them suddenly becomes your bottleneck. To alleviate that problem, you need extremely fast, direct GPU-to-GPU "interconnect", something like NV Link for example, and consumer GPUs don't provide that. Even if you could train on a single GPU, you probably wouldn't want to, because of the sheer amount of time that would take.
    - elashri 2y ago
      But does this prevent usage of cluster or consumer GPUs to be used in training? Or does it just make it slower and less efficient? Those are real questions and not argumentative questions.
      - blackoil 2y ago
        Consumer GPUs don't have Nvlink so they don't work very well in cluster.

paxys 2y ago

A company of Alibaba's scale probably isn't going to risk evading US sanctions. Even more so considering they are listed in the NYSE.

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griomnib 2y ago
NVIDIA sure as hell is trying to evade the spirit of the sanctions. Seriously questioning the wisdom of that.
- nl 2y ago
  > the spirit of the sanctions What does this mean? The sanctions are very specific on what can't be sold, so the spirit is to sell anything up to that limit.
  - chronic74930791 2y ago
    > What does this mean? The sanctions are very specific on what can't be sold, so the spirit is to sell anything up to that limit. 25% of Nvidia revenue comes from the tiny country of Singapore. You think Nvidia is asking why? (Answer: they aren’t)
    - bovinejoni 2y ago
      Not according to their reported financials. You have a source for that number?
      - umeshunni 2y ago
        https://www.cnbc.com/amp/2023/12/01/this-tiny-country-drove-15percent-of-nvidias-revenue-heres-why-it-needs-so-many-chips.html https://www.cnbc.com/amp/2023/12/01/this-tiny-country-drove-... About 15% or $2.7 billion of Nvidia's revenue for the quarter ended October came from Singapore, a U.S. Securities and Exchange Commission filing showed. Revenue coming from Singapore in the third quarter jumped 404.1% from the $562 million in revenue recorded in the same period a year ago.