4 ms·

I see these complains from time to time and I never understand them. I've literally been running nvidia on linux since the TNT2 days and have _never_ had this

I see these complains from time to time and I never understand them. I've literally been running nvidia on linux since the TNT2 days and have _never_ had this sort of issue. That's across many drivers and many cards over the many many years.

ant6n 3y ago
Well tnt2 should be pretty well supported by now ;-)
- PH95VuimJjqBqy 3y ago
  lmao, touche :)
temp0826 3y ago
I understand it, but I also haven't had any trouble since I figured out the right procedure for me on fedora (which probably took some time, but it's been so long that I can't remember). Whenever I read people having issues it sounds like they are using a package installed via dnf for the driver/etc. I've always had issues with dkms and the like and just install the latest .run from nvidia's website whenever I have a kernel update (I made a one-line script to call it with the silent option and flags for signing for secure boot so I don't really think about it). No issues in a very long time even with the whackiness of prime/optimus offloading on my old laptop.
- PH95VuimJjqBqy 3y ago
  actually, it's a good point because that's how I always install nvidia drivers as well. Never from the local package manager.
- bootsmann 3y ago
  So you don‘t recommend going the rpm-fusion route?
jjoonathan 3y ago
Same but linux experience is a steep and bumpy function of hardware. My guess: something like laptop GPU switching failed badly in the nvidia binary, earning it a reputation.
- HideousKojima 3y ago
  That was my experience, Nvidia Optimus (which is what allows dynamic switching between the integrated and dedicated GPU in laptops) was completely broken (as in a black screen, not just crashes or other issues) for several years, and Nvidia didn't care to do anything about it.
  - PH95VuimJjqBqy 3y ago
    I don't run laptops except when work requires it and that tends to be windows so that may explain the difference in experience.
  - lhl 3y ago
    Yeah, Optimus was a huge PITA. I remember fighting with workarounds like bumblebee and prime for years. Also Nvidia dragged their feet on Wayland support for a few years too (and simultaneously was seemingly intent on sabotaging Nouveau).
    - distract8901 3y ago
      I tried bumblebee again recently, and it works shockingly well now. I have a thinkpad T530 from 2013 with an NVS5400m. There is some strange issue with some games where they don't get full performance from the dGPU, but more than the iGPU. I have to use optirun to get full performance. It also has problems when the computer wakes from sleep. For whatever reason, hardware video decoding doesn't work after entering standby. Makes steam in home streaming crash on the client, but flipping to software decoding usually works fine. The important part is that battery life is almost as good with bumblebee as it is with the dGPU turned off. No more fucking with Prime or rebooting into BIOS to turn the GPU back on.
einpoklum 3y ago
I have been NVIDIA cards for compute capabilities only, both personally and at work, for nearly a decade. I've had dozens and dozens of different issues involving the hardware, the drivers, integration with the rest of the OS, version compatibilities, ensuring my desktop environment doesn't try to use the NVIDIA cards, etc. etc. Having said that - I (or rarely, other people) have almost always managed to work out those issues and get my systems to work. Not in all cases though.
LtWorf 3y ago
I've had kernel panics that disappeared when I started using the on board intel graphics instead of the nvidia. Your statement makes no sense. It's like a smoker claiming that since he didn't die of lung cancer, smoke is 100% safe.
- kkielhofner 3y ago
  Describing kernel panics and general nightmare scenarios as the general course with Nvidia doesn’t make sense either. Nvidia has 80% market share of the discrete GPU desktop market and at least 90% market share of cloud/datacenter. Nvidia GPUs are used almost exclusively for every cloud powered AI service and to train virtually every ML model in existence. Almost always on Linux. Do you really think any of this would be possible if what you are describing was anything approaching the typical experience starting at the /driver/ level? Nvidia would have never achieved their market dominance nor held on to it this long if the issues you’ve experienced impacted anything approaching a statistically significant number of users or applications. Nvidia gets a lot of hate on HN and elsewhere (much of it fair) but I will never understand the people who claim it doesn’t work and get the job done (often very well).
  - mr_toad 3y ago
    People use flakey software all their time. As long as it mostly works most of the time most people put up with it. Examples: Windows in the 90’s and 00’s, or any AAA game on first release in the last 10 years.
    - kkielhofner 3y ago
      I have a friend at the Facebook AI Research lab and I assure you they would not tolerate any level of fundamental flakiness from their 8,000 GPU cluster. Talent, opportunity cost, and time to market in general is so crucial in AI no one has any time or patience for the "oddball Linux desktop" experiences people are describing here. Gaming users may tolerate some flakiness for their hobby but these AI companies dealing in the nine-figure range (minimum) absolutely do not.

ant6n 3y ago

Well tnt2 should be pretty well supported by now ;-)

PH95VuimJjqBqy 3y ago
lmao, touche :)

temp0826 3y ago

I understand it, but I also haven't had any trouble since I figured out the right procedure for me on fedora (which probably took some time, but it's been so long that I can't remember). Whenever I read people having issues it sounds like they are using a package installed via dnf for the driver/etc. I've always had issues with dkms and the like and just install the latest .run from nvidia's website whenever I have a kernel update (I made a one-line script to call it with the silent option and flags for signing for secure boot so I don't really think about it). No issues in a very long time even with the whackiness of prime/optimus offloading on my old laptop.

PH95VuimJjqBqy 3y ago
actually, it's a good point because that's how I always install nvidia drivers as well. Never from the local package manager.
bootsmann 3y ago
So you don‘t recommend going the rpm-fusion route?

jjoonathan 3y ago

Same but linux experience is a steep and bumpy function of hardware. My guess: something like laptop GPU switching failed badly in the nvidia binary, earning it a reputation.

HideousKojima 3y ago
That was my experience, Nvidia Optimus (which is what allows dynamic switching between the integrated and dedicated GPU in laptops) was completely broken (as in a black screen, not just crashes or other issues) for several years, and Nvidia didn't care to do anything about it.
- PH95VuimJjqBqy 3y ago
  I don't run laptops except when work requires it and that tends to be windows so that may explain the difference in experience.
- lhl 3y ago
  Yeah, Optimus was a huge PITA. I remember fighting with workarounds like bumblebee and prime for years. Also Nvidia dragged their feet on Wayland support for a few years too (and simultaneously was seemingly intent on sabotaging Nouveau).
  - distract8901 3y ago
    I tried bumblebee again recently, and it works shockingly well now. I have a thinkpad T530 from 2013 with an NVS5400m. There is some strange issue with some games where they don't get full performance from the dGPU, but more than the iGPU. I have to use optirun to get full performance. It also has problems when the computer wakes from sleep. For whatever reason, hardware video decoding doesn't work after entering standby. Makes steam in home streaming crash on the client, but flipping to software decoding usually works fine. The important part is that battery life is almost as good with bumblebee as it is with the dGPU turned off. No more fucking with Prime or rebooting into BIOS to turn the GPU back on.

einpoklum 3y ago

I have been NVIDIA cards for compute capabilities only, both personally and at work, for nearly a decade. I've had dozens and dozens of different issues involving the hardware, the drivers, integration with the rest of the OS, version compatibilities, ensuring my desktop environment doesn't try to use the NVIDIA cards, etc. etc. Having said that - I (or rarely, other people) have almost always managed to work out those issues and get my systems to work. Not in all cases though.

LtWorf 3y ago

I've had kernel panics that disappeared when I started using the on board intel graphics instead of the nvidia. Your statement makes no sense. It's like a smoker claiming that since he didn't die of lung cancer, smoke is 100% safe.

kkielhofner 3y ago
Describing kernel panics and general nightmare scenarios as the general course with Nvidia doesn’t make sense either. Nvidia has 80% market share of the discrete GPU desktop market and at least 90% market share of cloud/datacenter. Nvidia GPUs are used almost exclusively for every cloud powered AI service and to train virtually every ML model in existence. Almost always on Linux. Do you really think any of this would be possible if what you are describing was anything approaching the typical experience starting at the /driver/ level? Nvidia would have never achieved their market dominance nor held on to it this long if the issues you’ve experienced impacted anything approaching a statistically significant number of users or applications. Nvidia gets a lot of hate on HN and elsewhere (much of it fair) but I will never understand the people who claim it doesn’t work and get the job done (often very well).
- mr_toad 3y ago
  People use flakey software all their time. As long as it mostly works most of the time most people put up with it. Examples: Windows in the 90’s and 00’s, or any AAA game on first release in the last 10 years.
  - kkielhofner 3y ago
    I have a friend at the Facebook AI Research lab and I assure you they would not tolerate any level of fundamental flakiness from their 8,000 GPU cluster. Talent, opportunity cost, and time to market in general is so crucial in AI no one has any time or patience for the "oddball Linux desktop" experiences people are describing here. Gaming users may tolerate some flakiness for their hobby but these AI companies dealing in the nine-figure range (minimum) absolutely do not.