alt Hacker News…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.
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> I had thought Xilinx ISE and Altera Quartus had the market cornered on the most difficult environments to get running, …
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.
That's why _LEAN_ open source is really required, and that includes the SDK.
You haven’t lived until you have done a model training run where different stages require mutually incompatible nvidia driver revisions and everything on top.