fec

Oh! Gotcha! I put a table in the README that lays it all out https://github.com/brian-armstrong/fec#performance tldr: My library matches or beats libfec's SSE2 assembly for convolutional codes and pretty steadily beats it in Reed-Solomon. For the convolutional codes, my crate is using a generic, templated decoder rather than hand-written assembly, so it was nice to see that I could match the performance.

Performance result are presented here as far as I understand: https://github.com/brian-armstrong/fec#performance

I wrote libcorrect in C in 2016 and wanted to revisit it in Rust. Instead of doing just a direct conversion, I went down the rabbit hole of making Rust's std::simd work for me. I ended up with a templated, generic Viterbi decoder for convolutional codes that dispatches the decode at runtime depending on which instruction sets are available. For small rates and orders, the entire decode lives in registers. Larger codes work through memory but take advantage of some acceleration structures. I also spent some time building a tool to find optimal (max d_free) conv codes for a given rate and order. Of course, there are better mechanisms available today, but I'm happy to talk through anything I learned in the process.