Originally posted by bug77
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AMD Announces Radeon Open Compute ROCm 3.0
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There should be ROCm with NAVI support soon.
https://www.amd.com/en/press-releases/2019-11-13-amd-radeon-pro-5000m-series-mobile-gpus-bring-high-performance-amd-rdna AMD now confirms that Navi 14 has indeed 24 Compute Units or 12 Workgroup Processors. At least 16" MacBook Pro will include the full blown model as an option
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Originally posted by bridgman View Post
In fairness, if the range of supported Windows versions big as the range of Linux distro versions "the Windows way" would probably be worse than the Linux way. It's not an intrinsic advantage of Windows, just the combination of stable driver ABI and much smaller range of OS versions to support.
On Linux, not even Nvidia's drivers are automatically installed. But once you install them, you get support for the whole enchilada: 3D gfx, HDMI sound (never used/needed it, but it's supposedly there) and the ability to tap into your card's compute resources. With AMD you get a mainlined gfx driver (huge step forward), but then you're left wondering why you can't get compute outside of Ubuntu 18.04, because you're unaware there's a script for Arch Linux that can point you in the right direction. It's just sad.
*I may have said Windows but MacOS works the same way, leaving Linux as the redhead kid on the block.
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It will take a while for application fully use Vulkan so OpenCL is currently a better option on the open source part. amdpgu-pro version runs well on APU although unofficially as it does not recognize Ryzen APU yet. ROCm version is slower but it is currently the only OpenCL running on Davinci Resolve.
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This is one of those tools that I've wanted to try for a long time now, but I haven't been able to simply because it literally supports no distros outside specific versions of Ubuntu and RHEL. I'm not going to waste hundreds of hours researching if I can get a frankestein installation to work or if my only options are either the docker (which segfaulted on its included tests when I gave it a quick try) or installing those distros on bare hardware.Last edited by Aeder; 19 November 2019, 12:32 AM.
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Originally posted by bug77 View Post
I prefer the Windows way: plug stuff in, detect it, install drivers and make stuff work.
What you have just described is horrible by comparison.
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Originally posted by zxy_thf View PostTo be fair, CUDA is just slightly better; its installer won't stop you from continuing, but it's very likely you will have to stop due to incompatibility with newer gcc or newer kernel.
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ROCm upstream integration into leading TensorFlow and PyTorch machine learning frameworks for applications like reinforcement learning, autonomous driving, and image and video detection.
https://developer.nvidia.com/nvidia-...#NVDECFeatures
Besides releasing ROCm 3.0 for SC19, the rest of AMD's press release is mostly EPYC newsLast edited by coder; 19 November 2019, 02:51 AM.
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