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How far behind is AMD? https://www.reuters.com/technology/amd-launches-new-ai-chips-take-leader-nvidia-2024-06-03/ https://www.reuters.com/technology/amd-launc

How far behind is AMD? https://www.reuters.com/technology/amd-launches-new-ai-chips-take-leader-nvidia-2024-06-03/ https://www.reuters.com/technology/amd-launches-new-ai-chips...

talldayo 2y ago
Hardware wise, they have a shot. But software wise, they are relying on everyone else to start using something they can leverage. I respect AMD for trying to get people to care about Open Source alternatives to CUDA, but the rest of the industry would rather fight Nvidia for scraps than work together to dethrone them. CUDA represents almost a decade of concentrated software design, and it's going to take a lot of work, proprietary or Open Source, to put it in it's grave.
- breadwinner 2y ago
  I have not seen any explanation of why CUDA is so hard to replicate. Is it that hard... even with billions of dollars at stake no one can come up with an alternative?
  - talldayo 2y ago
    > Is it that hard... even with billions of dollars at stake no one can come up with an alternative? It's so hard that with trillions of dollars at stake, nobody can be bothered to compete. There are really two alternative routes that the industry can take to kill CUDA. I've mentioned it a few times in this thread but their choices are: 1) Revive OpenCL as a cross-platform GPGPU solution. Fund Khronos and get them to brush up the spec and make OpenCL into what Vulkan was for DirectX. There's a lot of work OpenCL needs before it catches up with CUDA, but a Free and Open Source, cross-platform GPGPU API would make a lot of Nvidia's software monopoly irrelevant. 2) Compete with proprietary, hardware-specific CUDA alternatives that implement only parts of CUDA's spec piecemeal. Basically entails trying to beat Nvidia at their own game, something the rest of the industry hasn't been very good at historically. Option 1 makes the most sense; everyone wins if everyone's device speaks the same language. But the industry is too greedy to desire a true solution to CUDA's problem. OpenCL is derelict today because Apple, Microsoft and Google all feel as though they have better odds fighting CUDA alone. None of them are even close to Nvidia's performance profile or software capability, which is why I really feel that Option 1 is the only way forward.
rs999gti 2y ago
I would love AMD in the race, but isn't it CUDA and the software written specifically for NVDA hardware that makes them dominant?

How far behind is AMD? https://www.reuters.com/technology/amd-launches-new-ai-chips-take-leader-nvidia-2024-06-03/ https://www.reuters.com/technology/amd-launches-new-ai-chips...

talldayo 2y ago

Hardware wise, they have a shot. But software wise, they are relying on everyone else to start using something they can leverage. I respect AMD for trying to get people to care about Open Source alternatives to CUDA, but the rest of the industry would rather fight Nvidia for scraps than work together to dethrone them. CUDA represents almost a decade of concentrated software design, and it's going to take a lot of work, proprietary or Open Source, to put it in it's grave.

breadwinner 2y ago
I have not seen any explanation of why CUDA is so hard to replicate. Is it that hard... even with billions of dollars at stake no one can come up with an alternative?
- talldayo 2y ago
  > Is it that hard... even with billions of dollars at stake no one can come up with an alternative? It's so hard that with trillions of dollars at stake, nobody can be bothered to compete. There are really two alternative routes that the industry can take to kill CUDA. I've mentioned it a few times in this thread but their choices are: 1) Revive OpenCL as a cross-platform GPGPU solution. Fund Khronos and get them to brush up the spec and make OpenCL into what Vulkan was for DirectX. There's a lot of work OpenCL needs before it catches up with CUDA, but a Free and Open Source, cross-platform GPGPU API would make a lot of Nvidia's software monopoly irrelevant. 2) Compete with proprietary, hardware-specific CUDA alternatives that implement only parts of CUDA's spec piecemeal. Basically entails trying to beat Nvidia at their own game, something the rest of the industry hasn't been very good at historically. Option 1 makes the most sense; everyone wins if everyone's device speaks the same language. But the industry is too greedy to desire a true solution to CUDA's problem. OpenCL is derelict today because Apple, Microsoft and Google all feel as though they have better odds fighting CUDA alone. None of them are even close to Nvidia's performance profile or software capability, which is why I really feel that Option 1 is the only way forward.

rs999gti 2y ago

I would love AMD in the race, but isn't it CUDA and the software written specifically for NVDA hardware that makes them dominant?