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.
While thinking about it, if NVIDIA or SAMSUNG go performant RISC-V CPU micro-architecture, will "probably" change the world.
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.
These tools were the reason why I gave up on FPGAs years ago and chose to spend my time on GPUs instead. And to this day, I still don't understand why they worked so differently from what I had expected in so many ways.
Yosys is a super lightweight open-source FPGA toolchain that really easy to get up and running. The FPGA models I mentioned have ~5k to ~10k LUTs, can all support simple RISC-V processors, and have built-in memory and DSPs.
Drivers still need tweaking, most of the time, since most are still built assuming an amd64 world.
oh a double wide surprise for the AI industry? just what we needed.