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That makes a lot more sense, thanks. They could do with making that a lot clearer on the project. Still handicaps them compared to Nvidia where you can just bu

That makes a lot more sense, thanks. They could do with making that a lot clearer on the project. Still handicaps them compared to Nvidia where you can just buy anything recent and expect it to work. Suspect it also means they get virtually no open source contributions from the community because nobody can run or test it on personal hardware.

dragontamer 5y ago
NVidia can support anything because they have a PTX-translation layer between cards, and invest heavily on PTX. Each assembly language from each generation of cards changes. PTX recompiles the "pseudo-assembly" instructions into the new assembly code each generation. --------- AMD has no such technology. When AMD's assembly language changes (ex: from Vega into RDNA), its a big compiler change. AMD managed to keep the ISA mostly compatible from 7xxx GCN 1.0 series in the late 00s all the way to Vega 7nm in the late 10s... but RDNA's ISA change was pretty massive. I think its only natural that RDNA was going to have compiler issues. --------- AMD focused on Vulkan / DirectX support for its RDNA cards, while its compute team focused on continuing "CDNA" (which won large supercomputer contracts). So that's just how the business ended up.
blagie 5y ago
I bought an ATI card for deep learning. I'm a big fan of open source. Less than 12 months later, ROCm dropped support. I bought an NVidia, and I'm not looking back. This makes absolutely no sense to me, and I have a Ph.D: "* RDNA -- consumer cards. A new ISA with new compilers / everything. I don't think its reasonable to expect AMD's compilers to work on RDNA, when such large changes have been made to the architecture. (32-wide instead of 64-wide. 1024 registers. Etc. etc.) * CDNA -- based off of Vega's ISA. Despite being "legacy ISA", its pretty modern in terms of capabilities. MI100 is competitive against the A100. CDNA is likely going to run Frontier and El Capitan supercomputers. ROCm focused on CDNA. They've had compilers emit RDNA code, but its not "official" and still buggy. But if you went for CDNA, that HIP / ROCm stuff works enough for the Oak Ridge National Labs. Yeah, CDNA is expensive ($5k for MI50 / Radeon VII, and $9k for MI100). But that's the price of full-speed scientific-oriented double-precision floating point GPUs these days. I neither know nor care what RDNA, CDNA, A100, MI50, Radeon VII, MI100, or all the other AMD acronyms are. Yes, I could figure it out, but I want plug-and-play, stability, and backwards-compatibility. I ran into a whole different minefield with AMD. I'd need to run old ROCm, downgrade my kernel, and use a different card to drive monitors than for ROCm. It was a mess. NVidia gave me plug-and-play. I bought a random NVidia card with the highest "compute level," and was confident everything would work. It does. I'm happy. Intel has historically had great open source drivers, and if it give better plug-and-play and open source, I'll buy Intel next time. I'm skeptical, though. The past few year, Intel has a hard time tying their own shoelaces. I can't imagine this will be different.
- dragontamer 5y ago
  > Yes, I could figure it out, but I want plug-and-play, stability, and backwards-compatibility Its right there in the ROCm introduction. https://github.com/RadeonOpenCompute/ROCm#Hardware-and-Software-Support https://github.com/RadeonOpenCompute/ROCm#Hardware-and-Softw... > ROCm officially supports AMD GPUs that use following chips: > GFX9 GPUs > "Vega 10" chips, such as on the AMD Radeon RX Vega 64 and Radeon Instinct MI25 > "Vega 7nm" chips, such as on the Radeon Instinct MI50, Radeon Instinct MI60 or AMD Radeon VII, Radeon Pro VII > CDNA GPUs > MI100 chips such as on the AMD Instinct™ MI100 -------- The documentation of ROCm is pretty clear that it works on a limited range of hardware, with "unofficial" support at best on other sets of hardware.
  - blagie 5y ago
    Only... (1) There are a million different ROCm pages and introductions (2) Even that page is out-of-date, and e.g. claims unofficial support for "GFX8 GPUs: Polaris 11 chips, such as on the AMD Radeon RX 570 and Radeon Pro WX 4100," although those were randomly disabled after ROCm 3.5.1. ... if you have a Ph.D in AMD productology, you might be able to figure it out. If it's merely in computer science, math, or engineering, you're SOL. There are now unofficial guides to downgrading to 3.5.1, only 3.5.1 doesn't work with many modern frameworks, and you land in a version incompatibility mess. These aren't old cards either. Half-decent engineer time is worth $350/hour, all in (benefits, overhead, etc.). Once you've spent a week futzing with AMD's mess, you're behind by the cost of ten NVidia A4000 cards which Just Work. As a footnote, I suspect in the long term, small purchases will be worth more than the supercomputing megacontracts. GPGPU is wildly underutilized right now. That's mostly a gap of software, standards, and support. If we can get that right, every computer have many teraflops of computing power, even for stupid video chat filters and whatnot.
    - dragontamer 5y ago
      > Half-decent engineer time is worth $350/hour, all in (benefits, overhead, etc.). Once you've spent a week futzing with AMD's mess, you're behind by the cost of ten NVidia A4000 cards which Just Work. It seems pretty simple to me if we're talking about compute. The MI-cards are AMD's line of compute GPUs. Buy an MI-card if you want to use ROCm with full support. That's MI25, MI50, or MI100. > As a footnote, I suspect in the long term, small purchases will be worth more than the supercomputing megacontracts. GPGPU is wildly underutilized right now. That's mostly a gap of software, standards, and support. If we can get that right, every computer have many teraflops of computing power, even for stupid video chat filters and whatnot. I think you're right, but the #1 use of these devices is running video games (aka: DirectX and Vulkan). Compute capabilities are quite secondary at the moment.

dragontamer 5y ago

NVidia can support anything because they have a PTX-translation layer between cards, and invest heavily on PTX. Each assembly language from each generation of cards changes. PTX recompiles the "pseudo-assembly" instructions into the new assembly code each generation. --------- AMD has no such technology. When AMD's assembly language changes (ex: from Vega into RDNA), its a big compiler change. AMD managed to keep the ISA mostly compatible from 7xxx GCN 1.0 series in the late 00s all the way to Vega 7nm in the late 10s... but RDNA's ISA change was pretty massive. I think its only natural that RDNA was going to have compiler issues. --------- AMD focused on Vulkan / DirectX support for its RDNA cards, while its compute team focused on continuing "CDNA" (which won large supercomputer contracts). So that's just how the business ended up.

blagie 5y ago

I bought an ATI card for deep learning. I'm a big fan of open source. Less than 12 months later, ROCm dropped support. I bought an NVidia, and I'm not looking back. This makes absolutely no sense to me, and I have a Ph.D: "* RDNA -- consumer cards. A new ISA with new compilers / everything. I don't think its reasonable to expect AMD's compilers to work on RDNA, when such large changes have been made to the architecture. (32-wide instead of 64-wide. 1024 registers. Etc. etc.) * CDNA -- based off of Vega's ISA. Despite being "legacy ISA", its pretty modern in terms of capabilities. MI100 is competitive against the A100. CDNA is likely going to run Frontier and El Capitan supercomputers. ROCm focused on CDNA. They've had compilers emit RDNA code, but its not "official" and still buggy. But if you went for CDNA, that HIP / ROCm stuff works enough for the Oak Ridge National Labs. Yeah, CDNA is expensive ($5k for MI50 / Radeon VII, and $9k for MI100). But that's the price of full-speed scientific-oriented double-precision floating point GPUs these days. I neither know nor care what RDNA, CDNA, A100, MI50, Radeon VII, MI100, or all the other AMD acronyms are. Yes, I could figure it out, but I want plug-and-play, stability, and backwards-compatibility. I ran into a whole different minefield with AMD. I'd need to run old ROCm, downgrade my kernel, and use a different card to drive monitors than for ROCm. It was a mess. NVidia gave me plug-and-play. I bought a random NVidia card with the highest "compute level," and was confident everything would work. It does. I'm happy. Intel has historically had great open source drivers, and if it give better plug-and-play and open source, I'll buy Intel next time. I'm skeptical, though. The past few year, Intel has a hard time tying their own shoelaces. I can't imagine this will be different.

dragontamer 5y ago
> Yes, I could figure it out, but I want plug-and-play, stability, and backwards-compatibility Its right there in the ROCm introduction. https://github.com/RadeonOpenCompute/ROCm#Hardware-and-Software-Support https://github.com/RadeonOpenCompute/ROCm#Hardware-and-Softw... > ROCm officially supports AMD GPUs that use following chips: > GFX9 GPUs > "Vega 10" chips, such as on the AMD Radeon RX Vega 64 and Radeon Instinct MI25 > "Vega 7nm" chips, such as on the Radeon Instinct MI50, Radeon Instinct MI60 or AMD Radeon VII, Radeon Pro VII > CDNA GPUs > MI100 chips such as on the AMD Instinct™ MI100 -------- The documentation of ROCm is pretty clear that it works on a limited range of hardware, with "unofficial" support at best on other sets of hardware.
- blagie 5y ago
  Only... (1) There are a million different ROCm pages and introductions (2) Even that page is out-of-date, and e.g. claims unofficial support for "GFX8 GPUs: Polaris 11 chips, such as on the AMD Radeon RX 570 and Radeon Pro WX 4100," although those were randomly disabled after ROCm 3.5.1. ... if you have a Ph.D in AMD productology, you might be able to figure it out. If it's merely in computer science, math, or engineering, you're SOL. There are now unofficial guides to downgrading to 3.5.1, only 3.5.1 doesn't work with many modern frameworks, and you land in a version incompatibility mess. These aren't old cards either. Half-decent engineer time is worth $350/hour, all in (benefits, overhead, etc.). Once you've spent a week futzing with AMD's mess, you're behind by the cost of ten NVidia A4000 cards which Just Work. As a footnote, I suspect in the long term, small purchases will be worth more than the supercomputing megacontracts. GPGPU is wildly underutilized right now. That's mostly a gap of software, standards, and support. If we can get that right, every computer have many teraflops of computing power, even for stupid video chat filters and whatnot.
  - dragontamer 5y ago
    > Half-decent engineer time is worth $350/hour, all in (benefits, overhead, etc.). Once you've spent a week futzing with AMD's mess, you're behind by the cost of ten NVidia A4000 cards which Just Work. It seems pretty simple to me if we're talking about compute. The MI-cards are AMD's line of compute GPUs. Buy an MI-card if you want to use ROCm with full support. That's MI25, MI50, or MI100. > As a footnote, I suspect in the long term, small purchases will be worth more than the supercomputing megacontracts. GPGPU is wildly underutilized right now. That's mostly a gap of software, standards, and support. If we can get that right, every computer have many teraflops of computing power, even for stupid video chat filters and whatnot. I think you're right, but the #1 use of these devices is running video games (aka: DirectX and Vulkan). Compute capabilities are quite secondary at the moment.