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If I want to play games on Linux in the same quality/speed as on Windows, I have to use NVidia. If I want to do Deep Learning in Linux, I have to use NVidia. If

by bitL 9y ago

If I want to play games on Linux in the same quality/speed as on Windows, I have to use NVidia. If I want to do Deep Learning in Linux, I have to use NVidia. If I want to plug 3x 4k monitors on Linux, I have to use NVidia. If you can't come to agreement with them, what am I supposed to do?

Sir_Cmpwn 9y ago
You just play games at marginally inferior quality. Our new work on Sway also will let you use multiple GPUs without any proprietary interfaces, so you can do 3x 4K on AMD too. Regarding Deep Learning, that's too bad. If you can afford a 3x 4K setup though you can probably afford to have a Nvidia GPU for Deep Learning and an AMD GPU for your desktop. There are compromises you can make, most of them easy. None of this is my problem as the maintainer of Sway.
- falcolas 9y ago
  > None of this is my problem as the maintainer of Sway So, in short, you're firing your Nvidia users? Sometimes it has to be done, but you'll have to be very clear that you don't want Nvidia users. Passive-aggressive attacks in an indirectly linked blog post against the userbase and Nvidia themselves are not sufficient, you will have to just be explicit about it in your GitHub README.
  - Sir_Cmpwn 9y ago
    Well, I'm firing my Nvidia proprietary driver users. Really, I never "hired" them in the first place. The ones who use nouveau are cool in my book. I don't feel the need to call this out in the README. Also, this article contains pretty forwardly agressive attacks, I think.
    - SEJeff 9y ago
      Your users (those with 4 x 30" monitors like me) will be firing you as well. It isn't my fault that Nvidia makes superior GPUs and writes shit software :)
      - Sir_Cmpwn 9y ago
        I use 4 displays, 3x 1080p and 1x 4K. I'm happy to lose users who don't do their research and misportray the superiority of Nvidia, though.
        SEJeff 9y ago
        I do CUDA work (OpenCL is close, but not nearly as powerful) along with run big monitors. I've done my research, and there is Nvidia, and inferior options.
        deleted 9y ago
        [deleted]
        shmerl 9y ago
        How does using Vulkan for GPGPU today compare to using CUDA, I mean performance wise?
        kbutler 9y ago
        Depends on how you value Wayland support. That said, if I were Nvidia, and the post was an example of "cooperating" and "working" with the Wayland developers, I don't think I'd go out of my way to cooperate.
        wizbright 9y ago
        You can swap "Nvidia" and "Wayland developers" and still end up with an equally valid argument.
        kelnos 9y ago
        How so? The Wayland developers are pushing for open, unified standards that work across all chipsets. Nvidia is pushing for their own special snowflake implementation/interface, that no one else would or could use. You can certainly make the swap and the sentence still makes sense and is factually correct, but the context matters.
    - Qwertious 9y ago
      >Well, I'm firing my Nvidia proprietary driver users. Really, I never "hired" them in the first place. The ones who use nouveau are cool in my book. I don't feel the need to call this out in the README. Upon thinking about this, it's kind of like listing dependencies. I think you should make it clear in the README. I don't think the blog post is relevant in this context, as people likely won't read your blog post before installing Sway (and how would they know to do so, anyway?).
      - seba_dos1 9y ago
        Shouldn't it be Nvidia who needs to write it in their README? It's them who are incompatible with everything else, not Sway or Kwin.
- datawarrior 9y ago
  Sorry but with your attitude I really don't care about anything else you have to say. Grow up.
  - sctb 9y ago
    Could you please not make personal attacks? They don't belong on Hacker News. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
shmerl 9y ago
> If I want to play games on Linux in the same quality/speed as on Windows, I have to use NVidia. Not anymore. AMD/Mesa are already competitive enough, and are getting better fast. I was using Nvidia myself as well, until around the time Polaris cards came out, and Mesa was bumped to 17.x. That's when things really started to get good with AMD. And in the overall integration sense, it's like night and day. Nvidia is never going to reach it with their blob approach. Seamless upgrades, proper framebuffer, proper KMS/DRM, no constant screen tearing, Wayland support, GALLIUM_HUD, you name it. I wouldn't go back to Nvidia now (and I do all my gaming on Linux).
shmerl 9y ago
> If I want to do Deep Learning in Linux, I have to use NVidia. Why is that? What prevents you from using open APIs like Vulkan for GPGPU? Unless you rely on some CUDA only middleware of course.
- gh02t 9y ago
  CUDA has a strong grasp on a lot of the scientific market because Nvidia was ahead of the curve with CUDA initially and then has spent tons of money advertising and selling it to entrench it. To some degree it's a dev's own fault for getting sucked into a proprietary ecosystem, but ultimately "switch your code to something else" is not always a realistic option if you want to keep up with a community where CUDA is popular. CUDA is not as dominant as it was at first now that there are serious alternatives, but Nvidia works hard (both carrot and stick) to keep you locked in. And their hardware and software tools genuinely do have great performance, even if they should be better if Nvidia was a bit less... well evil honestly.
  - shmerl 9y ago
    Yeah, that's very Nvidia-like. Hopefully Vulkan based solutions will phase out CUDA lock-in in the future.
- TomVDB 9y ago
  There is a huge amount of CUDA middleware while there is very little for OpenCL. In the case of deep learning, there's cuDNN which is highly optimized and used by all major frameworks. AMD has promised something equivalent, but a first version is very unlikely to have the same scope and features. (Nvidia probably does a large amount of dog fooding given their deep learning based automobile efforts.) Using anything but Nvidia for deep learning is a great idea if you want to get noticed for not using Nvidia for deep learning, but it wouldn't be the smart thing to do if you want to actually get something done.
Luminarys 9y ago
With regards to Deep Learning, a recently released Keras backend[0] actually supports OpenCL with direct validation on a few AMD cards. I've been playing around with it for the past week or so and so far have had no issues with it, though I'm admittedly not doing anything too serious. 0. https://github.com/plaidml/plaidml https://github.com/plaidml/plaidml
abstractbeliefs 9y ago
For deep learning I can't specifically comment, but for GPGPU I can: give AMD your money and use OpenCL and the upcoming Vulkan. It worked great for me, and given Nvidia deliberately de-rate their support for OpenCL to push CUDA, I feel it's important to signal with your money that given the choice between flexible and open standards vs. proprietary, I'll support openness.

by bitL 9y ago

Sir_Cmpwn 9y ago

You just play games at marginally inferior quality. Our new work on Sway also will let you use multiple GPUs without any proprietary interfaces, so you can do 3x 4K on AMD too. Regarding Deep Learning, that's too bad. If you can afford a 3x 4K setup though you can probably afford to have a Nvidia GPU for Deep Learning and an AMD GPU for your desktop. There are compromises you can make, most of them easy. None of this is my problem as the maintainer of Sway.

falcolas 9y ago
> None of this is my problem as the maintainer of Sway So, in short, you're firing your Nvidia users? Sometimes it has to be done, but you'll have to be very clear that you don't want Nvidia users. Passive-aggressive attacks in an indirectly linked blog post against the userbase and Nvidia themselves are not sufficient, you will have to just be explicit about it in your GitHub README.
- Sir_Cmpwn 9y ago
  Well, I'm firing my Nvidia proprietary driver users. Really, I never "hired" them in the first place. The ones who use nouveau are cool in my book. I don't feel the need to call this out in the README. Also, this article contains pretty forwardly agressive attacks, I think.
  - SEJeff 9y ago
    Your users (those with 4 x 30" monitors like me) will be firing you as well. It isn't my fault that Nvidia makes superior GPUs and writes shit software :)
    - Sir_Cmpwn 9y ago
      I use 4 displays, 3x 1080p and 1x 4K. I'm happy to lose users who don't do their research and misportray the superiority of Nvidia, though.
      - SEJeff 9y ago
        I do CUDA work (OpenCL is close, but not nearly as powerful) along with run big monitors. I've done my research, and there is Nvidia, and inferior options.
        deleted 9y ago
        [deleted]
        shmerl 9y ago
        How does using Vulkan for GPGPU today compare to using CUDA, I mean performance wise?
        kbutler 9y ago
        Depends on how you value Wayland support. That said, if I were Nvidia, and the post was an example of "cooperating" and "working" with the Wayland developers, I don't think I'd go out of my way to cooperate.
        wizbright 9y ago
        You can swap "Nvidia" and "Wayland developers" and still end up with an equally valid argument.
        kelnos 9y ago
        How so? The Wayland developers are pushing for open, unified standards that work across all chipsets. Nvidia is pushing for their own special snowflake implementation/interface, that no one else would or could use. You can certainly make the swap and the sentence still makes sense and is factually correct, but the context matters.
  - Qwertious 9y ago
    >Well, I'm firing my Nvidia proprietary driver users. Really, I never "hired" them in the first place. The ones who use nouveau are cool in my book. I don't feel the need to call this out in the README. Upon thinking about this, it's kind of like listing dependencies. I think you should make it clear in the README. I don't think the blog post is relevant in this context, as people likely won't read your blog post before installing Sway (and how would they know to do so, anyway?).
    - seba_dos1 9y ago
      Shouldn't it be Nvidia who needs to write it in their README? It's them who are incompatible with everything else, not Sway or Kwin.
datawarrior 9y ago
Sorry but with your attitude I really don't care about anything else you have to say. Grow up.
- sctb 9y ago
  Could you please not make personal attacks? They don't belong on Hacker News. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html

shmerl 9y ago

> If I want to play games on Linux in the same quality/speed as on Windows, I have to use NVidia. Not anymore. AMD/Mesa are already competitive enough, and are getting better fast. I was using Nvidia myself as well, until around the time Polaris cards came out, and Mesa was bumped to 17.x. That's when things really started to get good with AMD. And in the overall integration sense, it's like night and day. Nvidia is never going to reach it with their blob approach. Seamless upgrades, proper framebuffer, proper KMS/DRM, no constant screen tearing, Wayland support, GALLIUM_HUD, you name it. I wouldn't go back to Nvidia now (and I do all my gaming on Linux).

shmerl 9y ago

> If I want to do Deep Learning in Linux, I have to use NVidia. Why is that? What prevents you from using open APIs like Vulkan for GPGPU? Unless you rely on some CUDA only middleware of course.

gh02t 9y ago
CUDA has a strong grasp on a lot of the scientific market because Nvidia was ahead of the curve with CUDA initially and then has spent tons of money advertising and selling it to entrench it. To some degree it's a dev's own fault for getting sucked into a proprietary ecosystem, but ultimately "switch your code to something else" is not always a realistic option if you want to keep up with a community where CUDA is popular. CUDA is not as dominant as it was at first now that there are serious alternatives, but Nvidia works hard (both carrot and stick) to keep you locked in. And their hardware and software tools genuinely do have great performance, even if they should be better if Nvidia was a bit less... well evil honestly.
- shmerl 9y ago
  Yeah, that's very Nvidia-like. Hopefully Vulkan based solutions will phase out CUDA lock-in in the future.
TomVDB 9y ago
There is a huge amount of CUDA middleware while there is very little for OpenCL. In the case of deep learning, there's cuDNN which is highly optimized and used by all major frameworks. AMD has promised something equivalent, but a first version is very unlikely to have the same scope and features. (Nvidia probably does a large amount of dog fooding given their deep learning based automobile efforts.) Using anything but Nvidia for deep learning is a great idea if you want to get noticed for not using Nvidia for deep learning, but it wouldn't be the smart thing to do if you want to actually get something done.

Luminarys 9y ago

With regards to Deep Learning, a recently released Keras backend[0] actually supports OpenCL with direct validation on a few AMD cards. I've been playing around with it for the past week or so and so far have had no issues with it, though I'm admittedly not doing anything too serious. 0. https://github.com/plaidml/plaidml https://github.com/plaidml/plaidml

abstractbeliefs 9y ago

For deep learning I can't specifically comment, but for GPGPU I can: give AMD your money and use OpenCL and the upcoming Vulkan. It worked great for me, and given Nvidia deliberately de-rate their support for OpenCL to push CUDA, I feel it's important to signal with your money that given the choice between flexible and open standards vs. proprietary, I'll support openness.