5 ms·

If this turns around it will be amazing but ROCm isnt the only issue. The entire driver stack is important. If they came out with virtualization support for the

If this turns around it will be amazing but ROCm isnt the only issue. The entire driver stack is important. If they came out with virtualization support for their gpus (even if everyone paid a 10% perf hit) they'd take over the cheap hosted gpu space which is a huge market.

mindcrime 3y ago
Getting proper (and official) ROCm support across their consumer GPU line will be big as well. Hobbyists aren't buying MI300's and their ilk. And surely AMD is better off if a would be hobbyist (or low budget academic/industrial researcher) chooses a Radeon card over something from NVIDIA! I'm about to buy a high-end Radeon card myself, gambling that AMD is serious about this and will get it right, and that it won't be a wasted purchase. So yeah, if I seem like an AMD fan-boy (I am, somewhat) at least I'm putting my money where my mouth is. :-) AMD’s software stacks for each class of product are separate: ROCm (short for Radeon Open Compute platform) targets its Instinct data center GPU lines (and, soon, its Radeon consumer GPUs), They've been saying this for a while, and I'm encouraged by reports that people "out there" in the wild have actually gotten this to work with some cards, even in advance of the official support shipping. So here's hoping they are really serious about this point and make this real.
- auggierose 3y ago
  Yeah, don't. Buy an Nvidia and get shit done.
  - iforgotpassword 3y ago
    A bit harsh but I agree in that I only believe it when I see it. Have been burned by empty promises by AMD before.
  - capableweb 3y ago
    For some people, it's not just about getting results or "get shit done" but about the journey and learning on the way there. Also, AMDs approach to openness tends to be a bit better than NVIDIA, so there's that too. And since we're on HackerNews after all, an AMD GPU for the hacker betting on the future seems pretty fitting.
    - bravetraveler 3y ago
      For someone using Linux, an AMD card may be even better suited for 'getting things done' Wayland and many things outside of GPGPU are much better; ie: power control/gating/monitoring are all available over sysfs. You can over/underclock a fleet of systems with traditional config management. GPGPU surely deserves some weight given the context of the thread, but let's not ignore the warts Nvidia shows elsewhere.
      - TimeBearingDown 3y ago
        Agreed, AMD and Intel are much easier to rely on. I’ve never had it nicer on Linux than I do now with a primary AMD GPU and a secondary NVIDIA that I can use for games or CUDA, or pass to a VM. It feels great finally having bleeding edge kernels and Wayland compositors, with the guarantee of a Linux or Windows VM’s stable driver if something breaks for the NVIDIA blob, and my desktop stays operational regardless.
        bravetraveler 3y ago
        That setup is really nice, I miss doing VFIO. The demarcation point is truly a delight, and with hugepages/CPU pinning, the performance cost is negligible.
      - lmm 3y ago
        In principle I'm all for openness, but it doesn't mean anything if the thing doesn't work. I just haven't found AMD drivers to be reliable enough to use, on any platform, whereas with NVidia I install the proprietary drivers and then it just works, on both Linux and FreeBSD.
        bravetraveler 3y ago
        That's a shame. Do you tend towards the mobile side, by chance? The vast majority of my experience has been with discrete (desktop) cards and very new kernels/mesa. It's been great, here - on a number of hardware configs.
  - mindcrime 3y ago
    I get where you're coming from, and in fact I am planning to also build an NVIDIA based ML box as well. But I pointedly want to support AMD here for a variety of reasons, including an ideological bias towards Open Source Software, and a historical affinity for AMD that dates back to the mid 90's.
    - auggierose 3y ago
      Oh, if you can afford it, of course, go for it. I was just afraid you spend money on a high-end card, and are then disappointed.
  - bryanlarsen 3y ago
    Easier said than done, at least for H100.
    - dotnet00 3y ago
      They're talking about consumer cards, which is the point. You can learn CUDA off any consumer nvidia card and have it translate to the fancier gear, that's part of why nvidia has so much mindshare. Eg I can write my cuda code with my 3090s, my boss can test it on his laptop's discrete graphics, and then after that we can take the time to bring it to our V100s and A100s and nothing really has to change.
  - Conscat 3y ago
    AMD's debuggers and profilers let you disassemble kernel/shader machine code and introspect registers and instruction latency. That's something at least that Nvidia doesn't do with Nsight tools.
  - earthling8118 3y ago
    Having come from Nvidia before recently switching to AMD, this is a naive take on it. Their compute software might be better but their Linux driver is abysmal to manage and takes the fun out of owning a PC. Never again. I'd take AMD over them even if the card burned my house down each time I used it.
- jauntywundrkind 3y ago
  Apologies for the snark, but maybe it's better that so far AMD has had terrible consumer card support. What little hardware they have targeted seems to be barely stable & barely work for the very limited workloads that are supported. If regular consumers were told their GPUs would work for GPGPU, they might be rotten pissed when they found out what the real state of affairs is. But if AMD really wants a market impact - which is what this submission is about - getting good support across a decent range of consumer GPUs is absolutely required. They cannot win this ecosystem battle with only datacenter mindshare.
- dingi 3y ago
  Good luck man! Its your money to waste.
jauntywundrkind 3y ago
Virtualization is such a key ability. I really really lament that it's been tucked away, in a couple specific products (The last MxGPU is, what, half a decade old? More? Oh I guess they finally spun off a new one, an RDNA2 V620!). I keep close & cherish a small hope that for some use-cases we might get a soft virtualization-alike that just works. I don't know enough to say how likely this is to adequately work, but in automotive & some other places there are nested Waylands, designed to share hardware. You still need a shared OS layer, a shared kernel, and a compositor that manages all the subdesktops - this isn't full virtualization - but hypothetically you get something very similar to virtualized/VDI gpus, if you can handle the constraints. This is really a huge huge huge shift that Wayland has potentially enabled, by actually using kernel resources like DMA-BUFs and what not, where apps can just allocate whatever & pass the compositor filehandles to the bufs. Wayland is ground up, unlike X's top down. So it's just a matter of writing compositors smart enough to push what data from whom needs to get rendered and sent out where. I would love to know more about what hardware virtualization really buys, know more about the limitations of what VDI is possible in software. But my hope is, in not too long, there's good enough VDI infrastructure that it's basically moot whether a gpu has hardware support. There will be some use cases where yes every users needs to run their own kernel & OS, and that won't be supported (albeit virtio might workaround even that quite effectively), but for 95% of use cases the more modern software stack might make this a non-issue. And at that point, these companies might stop having such expensive-ass product segmentation, charging 3x as much to have a couple hardware virtual devices, since in fact it costs them essentially nothing & the software virtualization is so competitive.

mindcrime 3y ago

Getting proper (and official) ROCm support across their consumer GPU line will be big as well. Hobbyists aren't buying MI300's and their ilk. And surely AMD is better off if a would be hobbyist (or low budget academic/industrial researcher) chooses a Radeon card over something from NVIDIA! I'm about to buy a high-end Radeon card myself, gambling that AMD is serious about this and will get it right, and that it won't be a wasted purchase. So yeah, if I seem like an AMD fan-boy (I am, somewhat) at least I'm putting my money where my mouth is. :-) AMD’s software stacks for each class of product are separate: ROCm (short for Radeon Open Compute platform) targets its Instinct data center GPU lines (and, soon, its Radeon consumer GPUs), They've been saying this for a while, and I'm encouraged by reports that people "out there" in the wild have actually gotten this to work with some cards, even in advance of the official support shipping. So here's hoping they are really serious about this point and make this real.

auggierose 3y ago
Yeah, don't. Buy an Nvidia and get shit done.
- iforgotpassword 3y ago
  A bit harsh but I agree in that I only believe it when I see it. Have been burned by empty promises by AMD before.
- capableweb 3y ago
  For some people, it's not just about getting results or "get shit done" but about the journey and learning on the way there. Also, AMDs approach to openness tends to be a bit better than NVIDIA, so there's that too. And since we're on HackerNews after all, an AMD GPU for the hacker betting on the future seems pretty fitting.
  - bravetraveler 3y ago
    For someone using Linux, an AMD card may be even better suited for 'getting things done' Wayland and many things outside of GPGPU are much better; ie: power control/gating/monitoring are all available over sysfs. You can over/underclock a fleet of systems with traditional config management. GPGPU surely deserves some weight given the context of the thread, but let's not ignore the warts Nvidia shows elsewhere.
    - TimeBearingDown 3y ago
      Agreed, AMD and Intel are much easier to rely on. I’ve never had it nicer on Linux than I do now with a primary AMD GPU and a secondary NVIDIA that I can use for games or CUDA, or pass to a VM. It feels great finally having bleeding edge kernels and Wayland compositors, with the guarantee of a Linux or Windows VM’s stable driver if something breaks for the NVIDIA blob, and my desktop stays operational regardless.
      - bravetraveler 3y ago
        That setup is really nice, I miss doing VFIO. The demarcation point is truly a delight, and with hugepages/CPU pinning, the performance cost is negligible.
    - lmm 3y ago
      In principle I'm all for openness, but it doesn't mean anything if the thing doesn't work. I just haven't found AMD drivers to be reliable enough to use, on any platform, whereas with NVidia I install the proprietary drivers and then it just works, on both Linux and FreeBSD.
      - bravetraveler 3y ago
        That's a shame. Do you tend towards the mobile side, by chance? The vast majority of my experience has been with discrete (desktop) cards and very new kernels/mesa. It's been great, here - on a number of hardware configs.
- mindcrime 3y ago
  I get where you're coming from, and in fact I am planning to also build an NVIDIA based ML box as well. But I pointedly want to support AMD here for a variety of reasons, including an ideological bias towards Open Source Software, and a historical affinity for AMD that dates back to the mid 90's.
  - auggierose 3y ago
    Oh, if you can afford it, of course, go for it. I was just afraid you spend money on a high-end card, and are then disappointed.
- bryanlarsen 3y ago
  Easier said than done, at least for H100.
  - dotnet00 3y ago
    They're talking about consumer cards, which is the point. You can learn CUDA off any consumer nvidia card and have it translate to the fancier gear, that's part of why nvidia has so much mindshare. Eg I can write my cuda code with my 3090s, my boss can test it on his laptop's discrete graphics, and then after that we can take the time to bring it to our V100s and A100s and nothing really has to change.
- Conscat 3y ago
  AMD's debuggers and profilers let you disassemble kernel/shader machine code and introspect registers and instruction latency. That's something at least that Nvidia doesn't do with Nsight tools.
- earthling8118 3y ago
  Having come from Nvidia before recently switching to AMD, this is a naive take on it. Their compute software might be better but their Linux driver is abysmal to manage and takes the fun out of owning a PC. Never again. I'd take AMD over them even if the card burned my house down each time I used it.
jauntywundrkind 3y ago
Apologies for the snark, but maybe it's better that so far AMD has had terrible consumer card support. What little hardware they have targeted seems to be barely stable & barely work for the very limited workloads that are supported. If regular consumers were told their GPUs would work for GPGPU, they might be rotten pissed when they found out what the real state of affairs is. But if AMD really wants a market impact - which is what this submission is about - getting good support across a decent range of consumer GPUs is absolutely required. They cannot win this ecosystem battle with only datacenter mindshare.
dingi 3y ago
Good luck man! Its your money to waste.

jauntywundrkind 3y ago

Virtualization is such a key ability. I really really lament that it's been tucked away, in a couple specific products (The last MxGPU is, what, half a decade old? More? Oh I guess they finally spun off a new one, an RDNA2 V620!). I keep close & cherish a small hope that for some use-cases we might get a soft virtualization-alike that just works. I don't know enough to say how likely this is to adequately work, but in automotive & some other places there are nested Waylands, designed to share hardware. You still need a shared OS layer, a shared kernel, and a compositor that manages all the subdesktops - this isn't full virtualization - but hypothetically you get something very similar to virtualized/VDI gpus, if you can handle the constraints. This is really a huge huge huge shift that Wayland has potentially enabled, by actually using kernel resources like DMA-BUFs and what not, where apps can just allocate whatever & pass the compositor filehandles to the bufs. Wayland is ground up, unlike X's top down. So it's just a matter of writing compositors smart enough to push what data from whom needs to get rendered and sent out where. I would love to know more about what hardware virtualization really buys, know more about the limitations of what VDI is possible in software. But my hope is, in not too long, there's good enough VDI infrastructure that it's basically moot whether a gpu has hardware support. There will be some use cases where yes every users needs to run their own kernel & OS, and that won't be supported (albeit virtio might workaround even that quite effectively), but for 95% of use cases the more modern software stack might make this a non-issue. And at that point, these companies might stop having such expensive-ass product segmentation, charging 3x as much to have a couple hardware virtual devices, since in fact it costs them essentially nothing & the software virtualization is so competitive.