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Altogether, this gives you O(n) work and O(log n) span, but using just a single parallel prefix kernel, which may be more efficient in practice.
For example, here's a C++ implementation: https://github.com/MPLLang/parallel-ml-bench/blob/main/cpp/l...
And, here's an implementation in a functional language: https://github.com/MPLLang/parallel-ml-bench/blob/main/mpl/b...
I'm pretty sure this generalizes, too, to abstract multiplications and additions in any field (at first glance, seems like it should but I haven't done the formal proof yet).
Anyway, it would be interesting to compare this against the solution in the arxiv paper.
If you know more than others do, that's great, but instead of posting putdowns, please share some of what you know so the rest of us can learn.
The trouble with comments like this is that they degrade discussion put others down without really teaching us anything.
https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor...
https://news.ycombinator.com/newsguidelines.html