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Now that major frameworks finally started supporting ROCm, AMD has half-abandoned it (IIRC the last consumer cards supported were the Vega ones, cards from 2 ge

Now that major frameworks finally started supporting ROCm, AMD has half-abandoned it (IIRC the last consumer cards supported were the Vega ones, cards from 2 generations ago). I hope this will change.

NavinF 6y ago
Oh oof. Thanks for saving me time not having to look up ROCm benchmarks. I find it really surprising they they don't wanna compete on performance/$ at all by not supporting consumer cards
- mastazi 6y ago
  No worries, for future reference you can check here (hopefully that page will report improved support in the future) https://github.com/RadeonOpenCompute/ROCm#supported-gpus https://github.com/RadeonOpenCompute/ROCm#supported-gpus
- AlphaSite 6y ago
  I think this is more of an issue that they have Compute optimised and Graphics optimised cards and Vega is their last compute optimised card. It would be very nice for them to refresh their compute cards as well.
  - my123 6y ago
    They made new compute cards, but they aren’t available to customers. (Only businesses, under the Radeon Instinct brand) With the price to match for those...
    - dogma1138 6y ago
      They aren’t available for business either, you can buy a Tesla card in a microcenter or on Newegg, and through a million partners ranging from small system builders to Dell and HP. Good luck getting an instinct card.
  - detaro 6y ago
    Going for market segmentation like that sounds like a pretty bad idea if you are already the underdog in the game.
    - my123 6y ago
      “Making science accessible to everyone is important to us. That's one of the reasons why GeForce cards can run CUDA.” — Bryce Lelbach at Nvidia AMD meanwhile considers GPU compute as a premium feature... which is a different approach. Not having a shippable IR like PTX but explicitly targeting a given GPU ISA, making this unshippable outside of HPC and supporting Linux only also points in that direction. Intel will end up being a much better option than AMD for GPU compute once they ship dGPUs... in their first gen.
    - sorenjan 6y ago
      Especially since more and more consumer workloads use compute as well. DLSS makes real time ray tracing at acceptable resolutions possible, your phone camera uses neural nets for every photo you take, Nvidias OptiX noise reduction is very impressive, and so on. AMD doesn't seem to want to be part of future computer usages, it's a shame. "Armies prepare to fight their last war, rather than their next war".
slavik81 6y ago
I work for AMD, but this comment contains exclusively my personal opinions and information that is publicly available. ROCm has not been abandoned. PyTorch is built on top of rocBLAS, rocFFT, and Tensile (among other libraries) which are all under active development. You can watch the commits roll in day-by-day on their public GitHub repositories. I can't speak about hardware support beyond what's written in the docs, but there are more senior folks at AMD who do comment on future plans (like John Bridgman).
- beagle3 6y ago
  Can you comment perhaps on what you guys have compared to nVidia’s DGX? I’d rather buy a workhorse with open drivers.
  - slavik81 6y ago
    The MI100 is our server compute product. The marketing page is probably a better source of information than I am: https://www.amd.com/en/products/server-accelerators/instinct-mi100 https://www.amd.com/en/products/server-accelerators/instinct...
- mcdevilkiller 6y ago
  Yes, you can ask bridgmanAMD on Reddit.
- ckastner 6y ago
  Hardware support is key, though. CUDA works with basically any card made in the last 5 years, consumer or compute. ROCm seems to work with a limited set of compute cards only. There's a ROCm team in Debian [1] trying to push ROCm forward (ROCm being open), but just getting supported hardware alone is already a major roadblock, which stalls the effort, and hence any contributions Debian could give back. [1] https://salsa.debian.org/rocm-team https://salsa.debian.org/rocm-team
  - slavik81 6y ago
    I didn't know about the Debian team. Thank you very much for informing me! I'm not sure how much I can do, but I would be happy to discuss with them the obstacles they are facing and see what I can help with. I'm better positioned to help with software issues than hardware matters, but I would love to hear about ROCm from their perspective. What's the best way to contact the team?
dogma1138 6y ago
It’s worse.... It’s Linux only so no Mac, Windows or WSL. No support what so ever for APUs which means if you have a laptop without a dedicated GPU you’re out of luck (tho discrete mobile GPUs aren’t officially supported either and often do not work). They’ve not only haven’t been supporting any of their consumer based R“we promise it’s not GCN this time”DNA GPUs, but since December last year (2020) they’ve dropped support for all pre-Vega GCN cards which means that Polaris (400/500 series) which is not only the most prolific of AMD GPUs that have been released in the past 5 years or so but also the most affordable ones are no longer supported. That’s on top of all the technical and architectural software issues that plague the framework.
- the8472 6y ago
  > or WSL Does WSL not support PCIe passthrough?
  - my123 6y ago
    It does not. And even then, almost all AMD customer GPUs are not supported. (Everything but Vega) APUs? Nope too.
- vetinari 6y ago
  > It’s worse.... > It’s Linux only so no Mac, Windows or WSL. I don't see really a problem here. You want Office or Photoshop? It runs on Mac and Windows only, so you better get one. You want ROCm? Get Linux for exactly the same reason.
  - sorenjan 6y ago
    It's a big problem if you want to use GPGPU in a product shipped to customers, or if you want to do some GPU programming on your own computer in your free time. Keep in mind that not only is it Linux only, it doesn't work on consumer hardware either.
    - vetinari 6y ago
t-vi 6y ago
Part of the problem is that Vega GPUs are too good for crypto currency mining. Example: I bought a 16GB Radeon VII for €550 (including 19% VAT). That would be a decent value proposition for Deep Learning even today. However, the card appears to trade second hand(!) for €1300+ on e-bay, because you apparently can run 90-100 MH/sec or so (this is an estimate I found on the web, I don't engage in this type of thing). As a result, you would not be able to get consumer Vega with these performance characteristics for a good price even if AMD produced them.

NavinF 6y ago

Oh oof. Thanks for saving me time not having to look up ROCm benchmarks. I find it really surprising they they don't wanna compete on performance/$ at all by not supporting consumer cards

mastazi 6y ago
No worries, for future reference you can check here (hopefully that page will report improved support in the future) https://github.com/RadeonOpenCompute/ROCm#supported-gpus https://github.com/RadeonOpenCompute/ROCm#supported-gpus
AlphaSite 6y ago
I think this is more of an issue that they have Compute optimised and Graphics optimised cards and Vega is their last compute optimised card. It would be very nice for them to refresh their compute cards as well.
- my123 6y ago
  They made new compute cards, but they aren’t available to customers. (Only businesses, under the Radeon Instinct brand) With the price to match for those...
  - dogma1138 6y ago
    They aren’t available for business either, you can buy a Tesla card in a microcenter or on Newegg, and through a million partners ranging from small system builders to Dell and HP. Good luck getting an instinct card.
- detaro 6y ago
  Going for market segmentation like that sounds like a pretty bad idea if you are already the underdog in the game.
  - my123 6y ago
    “Making science accessible to everyone is important to us. That's one of the reasons why GeForce cards can run CUDA.” — Bryce Lelbach at Nvidia AMD meanwhile considers GPU compute as a premium feature... which is a different approach. Not having a shippable IR like PTX but explicitly targeting a given GPU ISA, making this unshippable outside of HPC and supporting Linux only also points in that direction. Intel will end up being a much better option than AMD for GPU compute once they ship dGPUs... in their first gen.
  - sorenjan 6y ago
    Especially since more and more consumer workloads use compute as well. DLSS makes real time ray tracing at acceptable resolutions possible, your phone camera uses neural nets for every photo you take, Nvidias OptiX noise reduction is very impressive, and so on. AMD doesn't seem to want to be part of future computer usages, it's a shame. "Armies prepare to fight their last war, rather than their next war".

slavik81 6y ago

I work for AMD, but this comment contains exclusively my personal opinions and information that is publicly available. ROCm has not been abandoned. PyTorch is built on top of rocBLAS, rocFFT, and Tensile (among other libraries) which are all under active development. You can watch the commits roll in day-by-day on their public GitHub repositories. I can't speak about hardware support beyond what's written in the docs, but there are more senior folks at AMD who do comment on future plans (like John Bridgman).

beagle3 6y ago
Can you comment perhaps on what you guys have compared to nVidia’s DGX? I’d rather buy a workhorse with open drivers.
- slavik81 6y ago
  The MI100 is our server compute product. The marketing page is probably a better source of information than I am: https://www.amd.com/en/products/server-accelerators/instinct-mi100 https://www.amd.com/en/products/server-accelerators/instinct...
mcdevilkiller 6y ago
Yes, you can ask bridgmanAMD on Reddit.
ckastner 6y ago
Hardware support is key, though. CUDA works with basically any card made in the last 5 years, consumer or compute. ROCm seems to work with a limited set of compute cards only. There's a ROCm team in Debian [1] trying to push ROCm forward (ROCm being open), but just getting supported hardware alone is already a major roadblock, which stalls the effort, and hence any contributions Debian could give back. [1] https://salsa.debian.org/rocm-team https://salsa.debian.org/rocm-team
- slavik81 6y ago
  I didn't know about the Debian team. Thank you very much for informing me! I'm not sure how much I can do, but I would be happy to discuss with them the obstacles they are facing and see what I can help with. I'm better positioned to help with software issues than hardware matters, but I would love to hear about ROCm from their perspective. What's the best way to contact the team?

dogma1138 6y ago

It’s worse.... It’s Linux only so no Mac, Windows or WSL. No support what so ever for APUs which means if you have a laptop without a dedicated GPU you’re out of luck (tho discrete mobile GPUs aren’t officially supported either and often do not work). They’ve not only haven’t been supporting any of their consumer based R“we promise it’s not GCN this time”DNA GPUs, but since December last year (2020) they’ve dropped support for all pre-Vega GCN cards which means that Polaris (400/500 series) which is not only the most prolific of AMD GPUs that have been released in the past 5 years or so but also the most affordable ones are no longer supported. That’s on top of all the technical and architectural software issues that plague the framework.

the8472 6y ago
> or WSL Does WSL not support PCIe passthrough?
- my123 6y ago
  It does not. And even then, almost all AMD customer GPUs are not supported. (Everything but Vega) APUs? Nope too.
vetinari 6y ago
> It’s worse.... > It’s Linux only so no Mac, Windows or WSL. I don't see really a problem here. You want Office or Photoshop? It runs on Mac and Windows only, so you better get one. You want ROCm? Get Linux for exactly the same reason.
- sorenjan 6y ago
  It's a big problem if you want to use GPGPU in a product shipped to customers, or if you want to do some GPU programming on your own computer in your free time. Keep in mind that not only is it Linux only, it doesn't work on consumer hardware either.
  - vetinari 6y ago

t-vi 6y ago

Part of the problem is that Vega GPUs are too good for crypto currency mining. Example: I bought a 16GB Radeon VII for €550 (including 19% VAT). That would be a decent value proposition for Deep Learning even today. However, the card appears to trade second hand(!) for €1300+ on e-bay, because you apparently can run 90-100 MH/sec or so (this is an estimate I found on the web, I don't engage in this type of thing). As a result, you would not be able to get consumer Vega with these performance characteristics for a good price even if AMD produced them.