No, it's 10x faster than an experimental, completely performance-unoptimized LSTM model that is far from state-of-the-art on its own. From the paper:
"Regarding the speed, our results show that our implementation is much faster than lstm-compress[8] with a similar model and gain. The speed improvement comes from the more optimized matrix multiplication implementation and the larger batch size (16 instead of 1)."
Of most interest here is the library used, LibNC, which might allow us to speed up cmix a bit (even making it 2x faster would already help a lot in testing).
Disclaimer: I've worked on cmix with its author
From the conclusion:
“We presented a practical implementation of an LSTM based lossless compressor. Although it is slow, its description is simple and the memory consumption is reasonable compared to compressors giving a similar compression ratio. It would greatly benefit from a dedicated hardware implementation.”
I only skimmed through the paper, but looks to me like this might be a 10X improvement over other LSTM compression methods, not state-of-the-art compression.
That said, I’m far from being an expert in compression and was hoping from someone in HN to explain how relevant this is in their discipline.
I would add that lstm-compress from Byron Knoll, the author of CMIX, already achieved comparable compression ratios at 10x the speed, as is shown in the paper.