I wonder how the driver situation is. From Jeff Geerling's work on running "big" GPUs on Raspberry Pis, my impression is that often less-common platforms should work but are littered with papercuts in practice.
…and when it comes to the most common use of big-iron GPUs right now, neural network engines, they're all so poorly put together that a papercut is often fatal. If every dependency isn't the exact needed version, the whole thing will collapse, and using all but the most common hardware is sure to be unsupported in some deprecated library version that is absolutely required to get everything running.
I had thought Xilinx ISE and Altera Quartus had the market cornered on the most difficult environments to get running, but then LLMs and stable diffusion came along.
AMD GPUs have worked on RISC-V for a couple years at this point. I have a Milk-V Titan that's paired with an AMD GPU running well: https://milkv.io/titan
I wonder how the driver situation is. From Jeff Geerling's work on running "big" GPUs on Raspberry Pis, my impression is that often less-common platforms should work but are littered with papercuts in practice.
oh a double wide surprise for the AI industry? just what we needed.
I had thought Xilinx ISE and Altera Quartus had the market cornered on the most difficult environments to get running, but then LLMs and stable diffusion came along.
is it opensource or megs of blob?