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This NVidia stuff is getting ridiculous. Apple basically killed off any Deep Learning enthusiasts and nobody could do any serious computing-intense stuff on the

by bitL 7y ago

This NVidia stuff is getting ridiculous. Apple basically killed off any Deep Learning enthusiasts and nobody could do any serious computing-intense stuff on their platform. A polished toy.

thstart 7y ago
May be because Apple would release ML hardware soon?
thstart 7y ago
May be because se Apple would release ML hardware soon?
burn_cycle 7y ago
It is indeed very frustrating, especially for those of us who bought Pascal cards before they stopped "working". In the end only the customers suffer.
wjakob 7y ago
The extra-painful part about this whole situation is that it's apparently only due to Apple blocking NVIDIA from signing and publishing their drivers. (for whatever bizarre reason they may have to do that)
- soganess 7y ago
  I know it stinks for the people who are acustom to Nvidia's workflow, but it is quite hard to feel bad for Nvidia. A bigger fish is doing to them what they do to smaller players. Nvidia blocks the Nouveau drivers from working properly on Maxwell2 or newer cards: https://www.phoronix.com/scan.php?page=news_item&px=Nouveau-XDC2017 https://www.phoronix.com/scan.php?page=news_item&px=Nouveau-...
  - judge2020 7y ago
    Related: https://news.ycombinator.com/item?id=18834715 https://news.ycombinator.com/item?id=18834715
- kitsunesoba 7y ago
  I think there’s more to the story than Nvidia is letting on. It wouldn’t surprise me a single bit if Apple is blocking Nvidia due to something like QA issues — Nvidia’s web drivers are notoriously buggy under macOS and Nvidia seems completely unrepentant about it. Pair this with Nvidia’s unwillingness to share source and collaborate with other companies on development and you’ve got problems. I currently run an EVGA 980Ti Classified in my hackintosh. It’s great hardware, but with the frequency of glitches that the drivers bring I’m increasingly inclined to sell it and replace it with an AMD card.
snazz 7y ago
Hopefully at some point deep learning and other applications for GPU technology will become vendor-agnostic, as with CPUs. While I can run Linux on either an Intel or an AMD CPU (and many others), it seems awfully silly that I can't run a CUDA application on an AMD GPU.
- gameswithgo 7y ago
  there are vendor agnostic ways to do it, but performance is just not very good on AMD gpus.
  - etaioinshrdlu 7y ago
    A bigger problem than the performance is the very poor software support. None of the top frameworks officially support AMD or openCL. Only broken patchsets are available for both tensorflow or pytorch. Performance is an issue, but the bigger issue is that your model just won't work. NVIDIA is really the only game in town right now. Google's TPUs are somewhat of an exception but they only sort of count, because you can't just go buy a TPU for training. Makes TPUs a non-starter for a lot of businesses. What's interesting is the slow pace of change. 3 years ago we were in the exact same place. I don't see it changing overnight.
    - slavik81 7y ago
      Apple abandoned OpenCL years ago. It's now officially deprecated on macOS. The most recent version they implemented is OpenCL 1.2 (released 2011). For reference, the current version is OpenCL 2.2 (released 2017).
    - mdaniel 7y ago
      because you can't just go buy a TPU for training but that's what this is, right? https://coral.withgoogle.com/products/ https://coral.withgoogle.com/products/
      - hollerith 7y ago
        That's for low-power devices.
StreamBright 7y ago
You are implying that there is a significant user base that does deep learning on a single node using MacOS. In my experience supporting data scientists for 10 years this is almost never the case.
- bitL 7y ago
  Not pros, but when you are a macOS user and want to learn Deep Learning or do some smaller state-of-art models, you are simply out of luck. Or if you are a data scientist on a plane/traveling with no Internet connectivity needing to quickly change something in the model and retrain. With Linux/Windows you have no issue if you have a proper NVidia hardware (1070 and better).

by bitL 7y ago

This NVidia stuff is getting ridiculous. Apple basically killed off any Deep Learning enthusiasts and nobody could do any serious computing-intense stuff on their platform. A polished toy.

thstart 7y ago

May be because Apple would release ML hardware soon?

thstart 7y ago

May be because se Apple would release ML hardware soon?

burn_cycle 7y ago

It is indeed very frustrating, especially for those of us who bought Pascal cards before they stopped "working". In the end only the customers suffer.

wjakob 7y ago

The extra-painful part about this whole situation is that it's apparently only due to Apple blocking NVIDIA from signing and publishing their drivers. (for whatever bizarre reason they may have to do that)

soganess 7y ago
I know it stinks for the people who are acustom to Nvidia's workflow, but it is quite hard to feel bad for Nvidia. A bigger fish is doing to them what they do to smaller players. Nvidia blocks the Nouveau drivers from working properly on Maxwell2 or newer cards: https://www.phoronix.com/scan.php?page=news_item&px=Nouveau-XDC2017 https://www.phoronix.com/scan.php?page=news_item&px=Nouveau-...
- judge2020 7y ago
  Related: https://news.ycombinator.com/item?id=18834715 https://news.ycombinator.com/item?id=18834715
kitsunesoba 7y ago
I think there’s more to the story than Nvidia is letting on. It wouldn’t surprise me a single bit if Apple is blocking Nvidia due to something like QA issues — Nvidia’s web drivers are notoriously buggy under macOS and Nvidia seems completely unrepentant about it. Pair this with Nvidia’s unwillingness to share source and collaborate with other companies on development and you’ve got problems. I currently run an EVGA 980Ti Classified in my hackintosh. It’s great hardware, but with the frequency of glitches that the drivers bring I’m increasingly inclined to sell it and replace it with an AMD card.

snazz 7y ago

Hopefully at some point deep learning and other applications for GPU technology will become vendor-agnostic, as with CPUs. While I can run Linux on either an Intel or an AMD CPU (and many others), it seems awfully silly that I can't run a CUDA application on an AMD GPU.

gameswithgo 7y ago
there are vendor agnostic ways to do it, but performance is just not very good on AMD gpus.
- etaioinshrdlu 7y ago
  A bigger problem than the performance is the very poor software support. None of the top frameworks officially support AMD or openCL. Only broken patchsets are available for both tensorflow or pytorch. Performance is an issue, but the bigger issue is that your model just won't work. NVIDIA is really the only game in town right now. Google's TPUs are somewhat of an exception but they only sort of count, because you can't just go buy a TPU for training. Makes TPUs a non-starter for a lot of businesses. What's interesting is the slow pace of change. 3 years ago we were in the exact same place. I don't see it changing overnight.
  - slavik81 7y ago
    Apple abandoned OpenCL years ago. It's now officially deprecated on macOS. The most recent version they implemented is OpenCL 1.2 (released 2011). For reference, the current version is OpenCL 2.2 (released 2017).
  - mdaniel 7y ago
    because you can't just go buy a TPU for training but that's what this is, right? https://coral.withgoogle.com/products/ https://coral.withgoogle.com/products/
    - hollerith 7y ago
      That's for low-power devices.

StreamBright 7y ago

You are implying that there is a significant user base that does deep learning on a single node using MacOS. In my experience supporting data scientists for 10 years this is almost never the case.

bitL 7y ago
Not pros, but when you are a macOS user and want to learn Deep Learning or do some smaller state-of-art models, you are simply out of luck. Or if you are a data scientist on a plane/traveling with no Internet connectivity needing to quickly change something in the model and retrain. With Linux/Windows you have no issue if you have a proper NVidia hardware (1070 and better).