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Actually, I wouldn't bother if Nvidia would go out of business, as I find it disgusting how they ignore consumer wishes since ages. I mean, in the past I have b

Actually, I wouldn't bother if Nvidia would go out of business, as I find it disgusting how they ignore consumer wishes since ages. I mean, in the past I have bought GPU hardware from Nvidia, AMD, and Intel but for a Linux desktop, the experience has been so much better when not using Nvidia, that I try to avoid their products nowadays. This won't help current owners of Nvidia hardware (as myself), but you shouldn't blame RedHat for issues that obviously have been caused by Nvidia.

atemerev 7y ago
Unfortunately, there is only one CUDA, and OpenCL is not an alternative.
- arendtio 7y ago
  Yes, I know :-/ I am not sure what the status of AMD ROCm is, but I guess it will take a while until it becomes a viable alternative.
  - atemerev 7y ago
    I'd be happy to say "hurrah!" and close the page, but it is also not an alternative :( Here is the FFT example in ROCm: https://github.com/ROCm-Developer-Tools/HCC-Example-Application/blob/master/HCFFT/FFT.cpp https://github.com/ROCm-Developer-Tools/HCC-Example-Applicat... Compared to FFT in CUDA: https://github.com/drufat/cuda-examples/blob/master/cuda/fft.cu https://github.com/drufat/cuda-examples/blob/master/cuda/fft... 1163 vs 216 lines of code! CUDA is really straightforward; ROCm is still low-level and incomprehensible (unless you are a C++ expert who happens to love low-level details).
fortran77 7y ago
They don’t ignore consumer wishes. They have the best GPGPU toolchain around. That’s why I only use NVIDIA. Nobody supports developers for High-Performance GPU computing like they do. They also support PC gamers very well.
- imtringued 7y ago
  Does that tool chain require a desktop environment?
- arendtio 7y ago
  > They have the best GPGPU toolchain around. Probably depends on the use-case: I mean, weren't the cryptocurrency people using AMD before they switched to custom FPGAs? But for sure, for the TensorFlow users, there doesn't seem to be a viable alternative to NVIDIA and there must be a reason why CUDA is more popular than OpenCL. What I mean with ignoring consumer wishes is that they neither offer an open-source driver like AMD and Intel do and they do not even support others in doing so, like the Nouveau people. Subsequently, as a Linux user with NVIDIA hardware, you are either stuck with the buggy binary driver or the feature-incomplete Nouveau driver while AMD and Intel users have relatively stable and feature complete open-source drivers. Why do you think Linus Torvalds likes Nvidia so much? https://duckduckgo.com/?q=Linus+Torvalds+Nvidia https://duckduckgo.com/?q=Linus+Torvalds+Nvidia

atemerev 7y ago

Unfortunately, there is only one CUDA, and OpenCL is not an alternative.

arendtio 7y ago
Yes, I know :-/ I am not sure what the status of AMD ROCm is, but I guess it will take a while until it becomes a viable alternative.
- atemerev 7y ago
  I'd be happy to say "hurrah!" and close the page, but it is also not an alternative :( Here is the FFT example in ROCm: https://github.com/ROCm-Developer-Tools/HCC-Example-Application/blob/master/HCFFT/FFT.cpp https://github.com/ROCm-Developer-Tools/HCC-Example-Applicat... Compared to FFT in CUDA: https://github.com/drufat/cuda-examples/blob/master/cuda/fft.cu https://github.com/drufat/cuda-examples/blob/master/cuda/fft... 1163 vs 216 lines of code! CUDA is really straightforward; ROCm is still low-level and incomprehensible (unless you are a C++ expert who happens to love low-level details).

fortran77 7y ago

They don’t ignore consumer wishes. They have the best GPGPU toolchain around. That’s why I only use NVIDIA. Nobody supports developers for High-Performance GPU computing like they do. They also support PC gamers very well.

imtringued 7y ago
Does that tool chain require a desktop environment?
arendtio 7y ago
> They have the best GPGPU toolchain around. Probably depends on the use-case: I mean, weren't the cryptocurrency people using AMD before they switched to custom FPGAs? But for sure, for the TensorFlow users, there doesn't seem to be a viable alternative to NVIDIA and there must be a reason why CUDA is more popular than OpenCL. What I mean with ignoring consumer wishes is that they neither offer an open-source driver like AMD and Intel do and they do not even support others in doing so, like the Nouveau people. Subsequently, as a Linux user with NVIDIA hardware, you are either stuck with the buggy binary driver or the feature-incomplete Nouveau driver while AMD and Intel users have relatively stable and feature complete open-source drivers. Why do you think Linus Torvalds likes Nvidia so much? https://duckduckgo.com/?q=Linus+Torvalds+Nvidia https://duckduckgo.com/?q=Linus+Torvalds+Nvidia