designing a suckless bignum library

Let's design a suckless bignum library. (I'm not part of suckless though, just curious about replacing GMP).

I researched a bit into algorithms and the rundown is this:
* long multiplication: O(n^2)
* karatsuba O(n^1.5)
* Toom-Cook, fourier transform based methods - even faster but only used for numbers 10k digits+ long. Much more complex.

So we should probably use karatsuba for all multiplications. Squaring can be done a bit faster than multiplying two different numbers sometimes.

Now I suggest programming it in assembly, that gives you access to the carry bit (C doesn't get you that). Of course we will use libc and the normal C calling conventions so that it's a regular C library.

What to do about memory management? e.g. if you want to add two numbers do we need to allocate a new 'number' as long as the largest to write the result into or do it destructively "x <- x + y"? Maybe the library should support both - then a calculator program would figure out the best primitives to use for a given computation.

It might be nice to also support things like (big modulus) modular arithmetic and polynomials. stuff like exponentiation and modular inverses have interesting algorithms.

What other integer operations would we want? I don't really want to do anything with arb. prec. real numbers - arithmetic with rationals could be done though.

>>48
Indeed libtom is very close to what
>>42
is suggesting - a good compromise in not being too slow for somewhat general use, but still far from a good choice for heavy (ie non-crypto) number crunching. That's why it might be wiser to strive for some absolute reductionism (fe specialize to embedded and crypto, and then you can do a lot under 2kloc without being too slow) and not directly compete with tommath.

The problem here is that general fast infinite precision is simply collection of dozens of algorithms (libtom is far beyond 2kloc suckless limit :), the more you specialize for various cases (including heuristics to auto choose method to do something, for easier use), the "faster" is the lib overall. The disadvantage is eventually you end up with a kitchen sink like GMP, NTT or ARPREC.

>>43
Engineering is empirical - hearsays and superstitions. You can find rigorous proofs of complexity of individual algorithms, but not for bignum in general, as that depends on what number theoretic tricks you actually decide to implement.

>>48

Assembly

Ah, just drop it. Hand written asm (of which there is not immense amount in GMP, just inner loop kernels) can squeeze say, 10-20% more. But that makes sense only after you exhausted algorithmic optimizations which can be often much faster. For example NTT or ARPREC can be still magnitude faster than GMP in some cases (say, non-modular multiplication), despite being pure C++.

I think that tommath indeed is pretty close to to GMP in terms of implemented tricks, but lacks ntt, and asm kernels IIRC.