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unfortunately having a competitive card is only half the battle, they also need all the deep learning libraries to support using this card otherwise nobody is g

unfortunately having a competitive card is only half the battle, they also need all the deep learning libraries to support using this card otherwise nobody is going to bother. I hope AMD understands that I enlists their own engineers to help the community make this card support solid.

FredFS456 6y ago
ROCm (https://rocmdocs.amd.com/en/latest/ https://rocmdocs.amd.com/en/latest/) is their compute framework/stack. Not as good as CUDA but has support for Tensorflow etc
- dogma1138 6y ago
  The problem is that ROCm is only for linux which is still a huge downside, and it doesn't have good support (or support at all) for the consumer grade GPUs, pretty much Polaris onwards is good luck, heck even Radeon VII isn't well supported. CUDA works because any NVIDIA GPU will run CUDA this means it's easier to learn, easier to prototype and easier to ship and the code you ship isn't limited to the datacenter. What AMD needs to do to "win" an HPC GPU launch is to have an event which is 95% "How we fixed ROCm, and here is our full software roadmap and support guarantee for the next 5 years" and the remaining 5% "oh btw here is our new silicon, it's really fast and shiny".
  - PEJOE 6y ago
    I would be interested in knowing how much compute happens away from Linux. My impression is that almost nobody uses windows for theses tasks, but anecdotes are not data. There are of course workstation type acceleration tasks like simulation that are very windows heavy(e.g. ANSYS), but I am not privy to the breakdown of compute demand per segment. > What AMD needs to do to "win" an HPC GPU launch is to have an event which is 95% "How we fixed ROCm, and here is our full software roadmap and support guarantee for the next 5 years" and the remaining 5% "oh btw here is our new silicon, it's really fast and shiny". This is a great point. NVDA has worked on CUDA for years and has a great ecosystem of material and questions on places like stackexchange. AMD will have to work very purposefully to close the gap, but it seems like they are aware and headed in the right direction.
    - dogma1138 6y ago
      Your impression is wrong, there is a metric ton of enterprise and consumer software that uses CUDA and runs only on windows. There are also whole "data sciences" divisions in bluechip companies that are running windows. Case in point i work for a huge financial company we have CUDA powered excel add-ins/macros... And no I'm not joking https://on-demand.gputechconf.com/gtc/2010/presentations/S12297-Developing-CUDA-Accelerated-Net-Plugins-for-Microsoft-Excel.pdf https://on-demand.gputechconf.com/gtc/2010/presentations/S12... And engineering, sciences and medical consumer applications are also quite often than not Windows only or Windows first. Then you have all the less-enterprisy stuff video and photo editing, filters, chess programs w/e... And lastly the biggest point is that Windows and consumer grade hardware is where most developers and students live, good luck running ROCm on your laptop, and no I really mean it it's officially not supported and in reality even if you manage to get a moderately compatible chip you'll encounter more bugs than on Klendathu. Don't underestimate the importance of software that runs everywhere and just works. Node.JS didn't became popular because JavaScript on the backend was something that was desperately needed, it became popular because you had a plethora of front-end developers that had little to no knowledge of server-side languages and frameworks. Unlike what HN and recruiters would like you to believe most developers can't learn 10 languages and frameworks, and definitely not well sure some can but the vast majority of developers don't spend 9 hours working and 9 hours hacking, for every dev with a github account that needs it's own storage rack there are 10,000 that just do 9 to 5 and check out. If on one hand you have a solution that forces you to pick from a narrow list of linux kernels and supported distros and an extremely narrow list of GPUs and still encounter bugs on every corner so you can maybe produce something that if it runs would only run on the same system as yours vs on the other hand a solution that would run on any OS that supports an NVIDIA GPU you'll pick the latter unless you are really really bored. And that is before you entertain the marketability and job prospects of learning CUDA vs ROCm, one allows you to get a job at any place that ships something that runs on a GPU it doesn't matter if it's something that occupies 1000 racks and might become sentient or something that filters excel spreadsheets faster the other one doesn't.
      - PEJOE 6y ago
        > And no I'm not joking https://on-demand.gputechconf.com/gtc/2010/presentations/S12 https://on-demand.gputechconf.com/gtc/2010/presentations/S12... Thank you for sharing the link and correcting my information bias. It sounds like the "workstation," compute world is a forest of deep niches. You make a lot of good points about the staying power of Windows. I am excited about all the moves towards a complete Linux desktop, but am not imagining that it will be mainstream.
  - boulos 6y ago
    That’s kind of the make-or-break plan for Frontier and El Capitan [1]. They’re having all the science folks try using ROCm and the HIP recompiler thing. We’ll see how that shakes out in practice. [1] https://www.anandtech.com/show/15581/el-capitan-supercomputer-detailed-amd-cpus-gpus-2-exaflops https://www.anandtech.com/show/15581/el-capitan-supercompute...
    - dogma1138 6y ago
      LLNL writes their own stack usually, I don't see the main API for El Capitan being anything but OpenMP and LLNL can and has written their own compilers and libraries for other GPU powered supercomputers.
      - boulos 6y ago
        Sure, but other folks have to make use of it, too. Not everyone's code will be abstracted from CUDA. They're trying to get folks on Summit to test out HIP more strongly. Repeating my comment from last summer [1] that linked to the "try to use HIP" [2]: > The OLCF plans to make HIP available on Summit so that users can begin using it prior to its availability on Frontier. HIP is a C++ runtime API that allows developers to write portable code to run on AMD and NVIDIA GPUs. It is essentially a wrapper that uses the underlying CUDA or ROCm platform that is installed on a system. The API is very similar to CUDA so transitioning existing codes from CUDA to HIP should be fairly straightforward in most cases. In addition, HIP provides porting tools which can be used to help port CUDA codes to the HIP layer, with no loss of performance as compared to the original CUDA application. HIP is not intended to be a drop-in replacement for CUDA, and developers should expect to do some manual coding and performance tuning work to complete the port. [1] https://news.ycombinator.com/item?id=20495637 https://news.ycombinator.com/item?id=20495637 [2] https://www.olcf.ornl.gov/wp-content/uploads/2019/05/frontier_specsheet.pdf https://www.olcf.ornl.gov/wp-content/uploads/2019/05/frontie...

FredFS456 6y ago

ROCm (https://rocmdocs.amd.com/en/latest/ https://rocmdocs.amd.com/en/latest/) is their compute framework/stack. Not as good as CUDA but has support for Tensorflow etc

dogma1138 6y ago
The problem is that ROCm is only for linux which is still a huge downside, and it doesn't have good support (or support at all) for the consumer grade GPUs, pretty much Polaris onwards is good luck, heck even Radeon VII isn't well supported. CUDA works because any NVIDIA GPU will run CUDA this means it's easier to learn, easier to prototype and easier to ship and the code you ship isn't limited to the datacenter. What AMD needs to do to "win" an HPC GPU launch is to have an event which is 95% "How we fixed ROCm, and here is our full software roadmap and support guarantee for the next 5 years" and the remaining 5% "oh btw here is our new silicon, it's really fast and shiny".
- PEJOE 6y ago
  I would be interested in knowing how much compute happens away from Linux. My impression is that almost nobody uses windows for theses tasks, but anecdotes are not data. There are of course workstation type acceleration tasks like simulation that are very windows heavy(e.g. ANSYS), but I am not privy to the breakdown of compute demand per segment. > What AMD needs to do to "win" an HPC GPU launch is to have an event which is 95% "How we fixed ROCm, and here is our full software roadmap and support guarantee for the next 5 years" and the remaining 5% "oh btw here is our new silicon, it's really fast and shiny". This is a great point. NVDA has worked on CUDA for years and has a great ecosystem of material and questions on places like stackexchange. AMD will have to work very purposefully to close the gap, but it seems like they are aware and headed in the right direction.
  - dogma1138 6y ago
    Your impression is wrong, there is a metric ton of enterprise and consumer software that uses CUDA and runs only on windows. There are also whole "data sciences" divisions in bluechip companies that are running windows. Case in point i work for a huge financial company we have CUDA powered excel add-ins/macros... And no I'm not joking https://on-demand.gputechconf.com/gtc/2010/presentations/S12297-Developing-CUDA-Accelerated-Net-Plugins-for-Microsoft-Excel.pdf https://on-demand.gputechconf.com/gtc/2010/presentations/S12... And engineering, sciences and medical consumer applications are also quite often than not Windows only or Windows first. Then you have all the less-enterprisy stuff video and photo editing, filters, chess programs w/e... And lastly the biggest point is that Windows and consumer grade hardware is where most developers and students live, good luck running ROCm on your laptop, and no I really mean it it's officially not supported and in reality even if you manage to get a moderately compatible chip you'll encounter more bugs than on Klendathu. Don't underestimate the importance of software that runs everywhere and just works. Node.JS didn't became popular because JavaScript on the backend was something that was desperately needed, it became popular because you had a plethora of front-end developers that had little to no knowledge of server-side languages and frameworks. Unlike what HN and recruiters would like you to believe most developers can't learn 10 languages and frameworks, and definitely not well sure some can but the vast majority of developers don't spend 9 hours working and 9 hours hacking, for every dev with a github account that needs it's own storage rack there are 10,000 that just do 9 to 5 and check out. If on one hand you have a solution that forces you to pick from a narrow list of linux kernels and supported distros and an extremely narrow list of GPUs and still encounter bugs on every corner so you can maybe produce something that if it runs would only run on the same system as yours vs on the other hand a solution that would run on any OS that supports an NVIDIA GPU you'll pick the latter unless you are really really bored. And that is before you entertain the marketability and job prospects of learning CUDA vs ROCm, one allows you to get a job at any place that ships something that runs on a GPU it doesn't matter if it's something that occupies 1000 racks and might become sentient or something that filters excel spreadsheets faster the other one doesn't.
    - PEJOE 6y ago
      > And no I'm not joking https://on-demand.gputechconf.com/gtc/2010/presentations/S12 https://on-demand.gputechconf.com/gtc/2010/presentations/S12... Thank you for sharing the link and correcting my information bias. It sounds like the "workstation," compute world is a forest of deep niches. You make a lot of good points about the staying power of Windows. I am excited about all the moves towards a complete Linux desktop, but am not imagining that it will be mainstream.
- boulos 6y ago
  That’s kind of the make-or-break plan for Frontier and El Capitan [1]. They’re having all the science folks try using ROCm and the HIP recompiler thing. We’ll see how that shakes out in practice. [1] https://www.anandtech.com/show/15581/el-capitan-supercomputer-detailed-amd-cpus-gpus-2-exaflops https://www.anandtech.com/show/15581/el-capitan-supercompute...
  - dogma1138 6y ago
    LLNL writes their own stack usually, I don't see the main API for El Capitan being anything but OpenMP and LLNL can and has written their own compilers and libraries for other GPU powered supercomputers.
    - boulos 6y ago
      Sure, but other folks have to make use of it, too. Not everyone's code will be abstracted from CUDA. They're trying to get folks on Summit to test out HIP more strongly. Repeating my comment from last summer [1] that linked to the "try to use HIP" [2]: > The OLCF plans to make HIP available on Summit so that users can begin using it prior to its availability on Frontier. HIP is a C++ runtime API that allows developers to write portable code to run on AMD and NVIDIA GPUs. It is essentially a wrapper that uses the underlying CUDA or ROCm platform that is installed on a system. The API is very similar to CUDA so transitioning existing codes from CUDA to HIP should be fairly straightforward in most cases. In addition, HIP provides porting tools which can be used to help port CUDA codes to the HIP layer, with no loss of performance as compared to the original CUDA application. HIP is not intended to be a drop-in replacement for CUDA, and developers should expect to do some manual coding and performance tuning work to complete the port. [1] https://news.ycombinator.com/item?id=20495637 https://news.ycombinator.com/item?id=20495637 [2] https://www.olcf.ornl.gov/wp-content/uploads/2019/05/frontier_specsheet.pdf https://www.olcf.ornl.gov/wp-content/uploads/2019/05/frontie...