For high entropy data (=somewhat random data), FSE is quite comparable to Huffman in compression speed.
For low entropy (lots of high probability symbols, like zeroes), Huffman is about 2-3x faster. But on the flipside, FSE achieves markedly higher compression ratio.
I think FSE is worth the speed tradeoff vs Huffman in most cases.
"FSE achieves markedly higher compression ratio". I do not thin it is true, FSE/ANS achieves slightly better ratios in general.
Zstd uses both Huffman (for large alphabets) and FSE (for small alphabets).
Comments
For high entropy data (=somewhat random data), FSE is quite comparable to Huffman in compression speed.
For low entropy (lots of high probability symbols, like zeroes), Huffman is about 2-3x faster. But on the flipside, FSE achieves markedly higher compression ratio.
I think FSE is worth the speed tradeoff vs Huffman in most cases.
"FSE achieves markedly higher compression ratio". I do not thin it is true, FSE/ANS achieves slightly better ratios in general. Zstd uses both Huffman (for large alphabets) and FSE (for small alphabets).