16 ms·

Probably even more closed than ever. They tend to become more and more restrictive with every new hardware generation. I wonder where their promised open source

by xvilka 6y ago

Probably even more closed than ever. They tend to become more and more restrictive with every new hardware generation. I wonder where their promised open source announcement they preannounced before.

tyingq 6y ago
I suspect some of it is driven by trying to keep the gaming/ai and desktop/server markets from overlapping. Market segmentation. If it were more open, that would be harder.
- the_pwner224 6y ago
  I wanted to do GPU PCI passthrough in a VM (run Linux host, then for gaming run a Windows VM with the GPU passed through to get good performance). Nvidia disabled this for their consumer GPUs; the Nvidia drivers in the Windows VM will block this from working. It was a purely software thing; there was no reason for this aside from nvidia wanting companies to pay more for the Quadro/etc. GPUs. In addition to that, there's always the proprietary blob running in my kernel. So a few months ago I bought an AMD card for my new computer.
  - Sebb767 6y ago
    GPU passthrough is also doable pretty easily on NVidia nowadays. See here: https://wiki.archlinux.org/index.php/PCI_passthrough_via_OVMF#%22Error_43:_Driver_failed_to_load%22_on_Nvidia_GPUs_passed_to_Windows_VMs https://wiki.archlinux.org/index.php/PCI_passthrough_via_OVM... /r/VFIO on Reddit is also pretty helpful. That being said, I fully support you buying and using AMD. But no need to throw out perfectly fine hardware in case you still have NVidia lying arround.
    - diffeomorphism 6y ago
      > GPU passthrough is also doable pretty easily on NVidia nowadays. By actively working against Nvidia who could break it again at any time if they wanted to: > Starting with QEMU 2.5.0 and libvirt 1.3.3, the vendor_id for the hypervisor can be spoofed, which is enough to fool the Nvidia drivers into loading anyway. If you already have Nvidia, fine, but to me this reads as a strong reason to not buy Nvidia if you can help it.
      - Sebb767 6y ago
        Oh, don't get me wrong, I surely don't want to encourage you to buy Nvidia. To be fair here, AMD also has some gripes with VFIO: Namely, the reset bug on Navi (which I personally didn't experience, but read about quite a few times) and disabled vGPU support on their smaller cards, which is, as far as I know, only a software solution and not really something that would steal their business customers either. Still, I'm rooting for AMD, if only for the fact that they're the reason it doesn't take six CPU generations any more to have a 50% performance bump.
wegs 6y ago
Yeah. That's been my general problem with adopting NVidia for anything. They make good hardware, but there's a lot of lock-in, and not a lot of transparency. That introduces business risk. I'm not in a position where I need GPGPU, but if there wasn't that risk, and generally there were mature, open standards, I'd definitely use it. The major breakpoint would be when libraries like Numpy do it natively, and better yet, when Python can fork out list comprehensions to a GPU. I think at that point, the flood gates will open up, and NVidia's marketshare will explode from specialized applications to everywhere. Intel stumbled into it by accident, but got it right with x86. Define an open(ish) standard, and produce superior chips to that standard. Without AMD, Cyrix, Via, and the other knock-offs, there would be no Intel at this point. Intel keeps getting it right with numerical libraries. They're open. They work well. They work on AMD. But because Intel is building them, Intel has that slight bit of advantage. If Intel's open libraries are even 5% better on Intel, that's a huge market edge.
- pjmlp 6y ago
  Given that I hardly saw any clone vendors other than AMD, I really doubt that they had any influence on Intel's market share. What worked out was IBM not being able to prevent PC clones, but given the wide adoption of laptops, tablets and phones that hardly matters nowadays.
  - muxator 6y ago
    Maybe not recently, but in the years that cemented Intel dominance, there were many clones on the market.
    - pjmlp 6y ago
      Yeah, but never in an amount that was actually meaningful, only by a couple of non branded PC OEMs.
  - wegs 6y ago
    Intel was forced to license to AMD for government contracts. There's a super-complex story there I won't get into. There were a few clone vendors aside from AMD. None were ever a serious threat, and AMD itself didn't become more than a bottom-feeder until after maybe 15 years. But their existence did drive a lot of adoption. And yes, I did oversimplify. MS-DOS, IBM not being able to prevent clones, and so on, all really played together here as part of the same story.
pjmlp 6y ago
The large majority of researchers and business getting into NVidia products doesn't seem to find it that relevant, rather what tools, GPU programming languages and hardware they are able to put their hands on.
- wegs 6y ago
  It's irrelevant to researchers. Research operates on rapid cycles: prototype, publish, move on. It does impact businesses. It doesn't prevent adoption for e.g. deep learning, but I haven't seen e.g. GPU-based databases reach broad adoption, or many other places where MIMD/SIMD would reduce costs or improve performance. Using classical hardware is clearly cheaper than the business risk and engineering time of relying on a proprietary, closed hardware solution. I'm at the edge, where my workloads don't require GPU, but could benefit from it. This sort of thing factors into decision-making. I dabble in GPU, but never beyond prototypes, for those reasons. I think this is one of the reasons why these devices haven't reached wide-spread marketshare. Most computers sold have an integrated chipset. People buying NVidia GPUs are researchers (who don't care), deep learning applications (who don't have a choice), and gamers. There have been predictions for two decades that GPU-style SIMD and MIMD architectures would displace the centrality of the GPU. Technically, it makes sense. If I type a list comprehension in Python, it would run at higher speed and lower power on a SIMD or MIMD platform. I think the reason that hasn't happened is because x86 and x64 are open and widely-supported. NVidia is a walled garden, and is only practical for markets NVidia explicitly targets. This story plays out over and over. Business people push for closed. Eventually, open comes along, and wipes it out. Sometimes, as with x86 or the iPhone, that leads to increased profits. Sometimes, as with Wikipedia, that kills businesses.
  - ethbro 6y ago
    Hypothetically, from an ISA perspective, why couldn't Intel and AMD extend x86-64 more fully with SIMD / MIMD instructions? (as in, way more fully than MMX / SSE / AVX) Naive question, because I literally don't know the link between CPU instruction stream and GPGPU instruction stream. But it seems like there would be an opportunity to seize the higher (open) ground at the ISA level, and then force Nvidia to implement its own support for that standard. With the point of being able to run identical code across CPU / CPU-with-embedded-GPU / CPU + GPU. Understand we're talking about mind-boggling levels of complexity here, but it feels like the CPU shops ceded the role of graphical ISA to Nvidia & Microsoft (DirectX).
partingshots 6y ago
Do you have a link for their open source announcement?

by xvilka 6y ago

Probably even more closed than ever. They tend to become more and more restrictive with every new hardware generation. I wonder where their promised open source announcement they preannounced before.

tyingq 6y ago

I suspect some of it is driven by trying to keep the gaming/ai and desktop/server markets from overlapping. Market segmentation. If it were more open, that would be harder.

the_pwner224 6y ago
I wanted to do GPU PCI passthrough in a VM (run Linux host, then for gaming run a Windows VM with the GPU passed through to get good performance). Nvidia disabled this for their consumer GPUs; the Nvidia drivers in the Windows VM will block this from working. It was a purely software thing; there was no reason for this aside from nvidia wanting companies to pay more for the Quadro/etc. GPUs. In addition to that, there's always the proprietary blob running in my kernel. So a few months ago I bought an AMD card for my new computer.
- Sebb767 6y ago
  GPU passthrough is also doable pretty easily on NVidia nowadays. See here: https://wiki.archlinux.org/index.php/PCI_passthrough_via_OVMF#%22Error_43:_Driver_failed_to_load%22_on_Nvidia_GPUs_passed_to_Windows_VMs https://wiki.archlinux.org/index.php/PCI_passthrough_via_OVM... /r/VFIO on Reddit is also pretty helpful. That being said, I fully support you buying and using AMD. But no need to throw out perfectly fine hardware in case you still have NVidia lying arround.
  - diffeomorphism 6y ago
    > GPU passthrough is also doable pretty easily on NVidia nowadays. By actively working against Nvidia who could break it again at any time if they wanted to: > Starting with QEMU 2.5.0 and libvirt 1.3.3, the vendor_id for the hypervisor can be spoofed, which is enough to fool the Nvidia drivers into loading anyway. If you already have Nvidia, fine, but to me this reads as a strong reason to not buy Nvidia if you can help it.
    - Sebb767 6y ago
      Oh, don't get me wrong, I surely don't want to encourage you to buy Nvidia. To be fair here, AMD also has some gripes with VFIO: Namely, the reset bug on Navi (which I personally didn't experience, but read about quite a few times) and disabled vGPU support on their smaller cards, which is, as far as I know, only a software solution and not really something that would steal their business customers either. Still, I'm rooting for AMD, if only for the fact that they're the reason it doesn't take six CPU generations any more to have a 50% performance bump.

wegs 6y ago

Yeah. That's been my general problem with adopting NVidia for anything. They make good hardware, but there's a lot of lock-in, and not a lot of transparency. That introduces business risk. I'm not in a position where I need GPGPU, but if there wasn't that risk, and generally there were mature, open standards, I'd definitely use it. The major breakpoint would be when libraries like Numpy do it natively, and better yet, when Python can fork out list comprehensions to a GPU. I think at that point, the flood gates will open up, and NVidia's marketshare will explode from specialized applications to everywhere. Intel stumbled into it by accident, but got it right with x86. Define an open(ish) standard, and produce superior chips to that standard. Without AMD, Cyrix, Via, and the other knock-offs, there would be no Intel at this point. Intel keeps getting it right with numerical libraries. They're open. They work well. They work on AMD. But because Intel is building them, Intel has that slight bit of advantage. If Intel's open libraries are even 5% better on Intel, that's a huge market edge.

pjmlp 6y ago
Given that I hardly saw any clone vendors other than AMD, I really doubt that they had any influence on Intel's market share. What worked out was IBM not being able to prevent PC clones, but given the wide adoption of laptops, tablets and phones that hardly matters nowadays.
- muxator 6y ago
  Maybe not recently, but in the years that cemented Intel dominance, there were many clones on the market.
  - pjmlp 6y ago
    Yeah, but never in an amount that was actually meaningful, only by a couple of non branded PC OEMs.
- wegs 6y ago
  Intel was forced to license to AMD for government contracts. There's a super-complex story there I won't get into. There were a few clone vendors aside from AMD. None were ever a serious threat, and AMD itself didn't become more than a bottom-feeder until after maybe 15 years. But their existence did drive a lot of adoption. And yes, I did oversimplify. MS-DOS, IBM not being able to prevent clones, and so on, all really played together here as part of the same story.

pjmlp 6y ago

The large majority of researchers and business getting into NVidia products doesn't seem to find it that relevant, rather what tools, GPU programming languages and hardware they are able to put their hands on.

wegs 6y ago
It's irrelevant to researchers. Research operates on rapid cycles: prototype, publish, move on. It does impact businesses. It doesn't prevent adoption for e.g. deep learning, but I haven't seen e.g. GPU-based databases reach broad adoption, or many other places where MIMD/SIMD would reduce costs or improve performance. Using classical hardware is clearly cheaper than the business risk and engineering time of relying on a proprietary, closed hardware solution. I'm at the edge, where my workloads don't require GPU, but could benefit from it. This sort of thing factors into decision-making. I dabble in GPU, but never beyond prototypes, for those reasons. I think this is one of the reasons why these devices haven't reached wide-spread marketshare. Most computers sold have an integrated chipset. People buying NVidia GPUs are researchers (who don't care), deep learning applications (who don't have a choice), and gamers. There have been predictions for two decades that GPU-style SIMD and MIMD architectures would displace the centrality of the GPU. Technically, it makes sense. If I type a list comprehension in Python, it would run at higher speed and lower power on a SIMD or MIMD platform. I think the reason that hasn't happened is because x86 and x64 are open and widely-supported. NVidia is a walled garden, and is only practical for markets NVidia explicitly targets. This story plays out over and over. Business people push for closed. Eventually, open comes along, and wipes it out. Sometimes, as with x86 or the iPhone, that leads to increased profits. Sometimes, as with Wikipedia, that kills businesses.
- ethbro 6y ago
  Hypothetically, from an ISA perspective, why couldn't Intel and AMD extend x86-64 more fully with SIMD / MIMD instructions? (as in, way more fully than MMX / SSE / AVX) Naive question, because I literally don't know the link between CPU instruction stream and GPGPU instruction stream. But it seems like there would be an opportunity to seize the higher (open) ground at the ISA level, and then force Nvidia to implement its own support for that standard. With the point of being able to run identical code across CPU / CPU-with-embedded-GPU / CPU + GPU. Understand we're talking about mind-boggling levels of complexity here, but it feels like the CPU shops ceded the role of graphical ISA to Nvidia & Microsoft (DirectX).

partingshots 6y ago

Do you have a link for their open source announcement?