As a whole, the speedups claimed are not actually that great. Going from 1 core to 16k cores increases performance by 50x. That's not actually very good.
Like, I really truly love what the author has contributed to functional languages and Interaction Nets. He has good ideas, but while it's cool that this can be done, things like LLMs require very practical tuning.
Finally, the author has a history of making fantastical claims. Again, it's true there is a speedup, but in my view, this is like making an extremely slow language and then optimizing it and then announcing that you've figure out how to improve your language's performance by 50x. While true, it neglects the fact it was very slow to begin with.
It is "only" 50x because a single GPU core is 100x weaker than a CPU core!
Within CUDA cores, it is actually a linear speedup! It does 2k MIPS with 1 CUDA core, and ~28000 MIPS with 16k CUDA cores. If we double the performance of single-core GPU evaluation, we almost double the performance with 16k cores!
Great work BTW