A few years ago my coauthor and I was wondering if we could reduce the number of multiplications used for hashing algorithms. We had a construction and a 100 page proof, but we were not 100% sure it was correct. Now we have a full Lean proof, so we decided to publish it.
I made this website to make it easy for anyone how has polynomials to evaluate to see how it would be done using our method, as well as a number of previous approaches by Knuth and others.
It keeps flipping back to 'monic' from e.g. 'ln(1+x)' when switching between algorithms, and then seems to lock to 'monic'? (Am I missing something?)
Also I am curious, in your version vs. horner , how do both algorithms map onto number of fmadd operations?
Would this be applicable to fast hashes like WyHash and xxh3 or are those not using polynomials? Is this mainly for faster cryptographic hashes?
I guess it’s not faster than using a table for CRC8?
From the abstract, a name that many on HN would recognize:
> We also give an injective polynomial construction for universal hashing that uses N multiplications to hash 2N values with a single random key. This improves the best previous construction by Daniel J. Bernstein (this http URL).
What is the tradeoff between multiplication and addition?
Just a few years ago, mults were slower, but I think now (Intel i9) mult, add and fma are the same.
I think multiplications are faster to do in computer land than adds? I too am curious.
Also could use analysis of dependencies to see what can happen in parallel. Or for that matter, some real benchmarks.
"monic" is a separate switch from the example functions radio-selector. Enabling "monic" removes the leading coefficient.