At Linux Plumbers Conference 2022, we held a BoF session around accelerators. This is a summary made from memory and notes taken by John Hubbard. We started with defining categories of accelerator devices. 1. single shot data processors, submit one off jobs to a device. (simpler image processors) 2. single-user, single task offload devices (ML training devices) 3. multi-app devices (GPU, ML/inference execution engines) One of the main points made is that common device frameworks are normally about targeting a common userspace (e.g. mesa for GPUs). Since a common userspace doesn't exist for accelerators, this presents a problem of what sort of common things can be targetted. Discussion about tensorflow, pytorch as being the userspace, but also camera image processing and OpenCL. OpenXLA was also named as a userspace API that might be of interest to use as a target for implementations. There was a discussion on what to call the subsystem and where to place it in the tree. It was ag
You can get working Vulkan drivers on Ubuntu with this PPA:
ReplyDeletehttps://launchpad.net/~oibaf/+archive/ubuntu/graphics-drivers/
Do they know? https://bugs.launchpad.net/ubuntu/+source/mesa has only one bug mentioning radv, and it's not about radv.
ReplyDeleteThis is the Ubuntu bug:
Deletehttps://bugs.launchpad.net/ubuntu/+source/mesa/+bug/1720890
yes, they do: https://bugs.launchpad.net/ubuntu/+source/mesa/+bug/1720890
ReplyDelete