[SPACECADET3D]

Nice, I will check this out in more detail later. I had a quick look at the benchmarks and it looks like you compare f64 hyperreal with numericas 128 bit implementation, which will fall back to using arb-prec GMP. There is also F64(simply wrapping around f64), and now DoubleFloat with 106 bits precision, which should be much faster. There is also the ErrorPropagatingFloat wrapper that may be of interest.

For simple numerical operations, using an entire Symbolica Atom will introduce a large amount of overhead. It should only be used if the expression contains symbols as well. But perhaps I misunderstood the point of the benchmark?

[timschmidt]

Hyperreal doesn't have any f64 mode. All math done with hyperreals is at infinite precision using a Rational of two BigUInts and a recursive real Computable. Real provides a cohesive interface over both allowing for easy scalar math. Computables are handled symbolically through a set of deterministic reduction rules until approximation is required, to preserve precision and reduce complexity. Approximation only happens at explicit public API boundaries like .to_f64_lossy() not used except for IO.

Hyperreal gets performance back through caching observed facts about the numbers it's representing at creation, and through operations, and specializing dispatch for predicates and geometric operations. Using this approach throughout the stack allows us to avoid computing on the full representation or collapsing it into an approximation. Instead asking questions like "do we know if it's definitely zero, definitely not, or unknown?" or "is it rational?" or "does it have a known sign, or unknown?" and so on. Each question specializes dispatch further, and some eliminate the need for it entirely.

Asking questions using the cached facts is approximately as fast as computing with f64s. So we do that whenever possible throughout the stack. But then when you actually need to do the exact computation, hyperreal does that too, and can approximate it out to whatever precision you'd like. f32 and f64 being common, but others being supported as well. The downside is that calculating quickly with them requires this sort specialization, but the work's been done for the geometry functions.

I'll look into DoubleFloat and ErrorPropagatingFloat for benches. I should mention that numerica@128bit beat the other pure rust bignum crates I tested. The benchmarks are mostly just to give me an understanding of the performance shapes of the implementation choices of high precision numeric libraries alongside hyperreal.

[SPACECADET3D]

Thanks for the clarification! Hyperreal sounds very useful for zero testing (at the moment I use ErrorPropagatingFloat for this, but it is fickle), I will play around with this in the near future.

[timschmidt]

Yes, it should be useful for that. Hyperreal's trig and approximate functions performance is also stellar. Perhaps the biggest compromise in terms of the math supported by hyperreals at the moment is that although Rational equality can be exactly tested, Computable equality is currently structural. So it's possible to end up with two mathematically equivalent Computables which aren't structurally equal. Because it's not a full CAS.

It's still possible to approximate them both, and test them against each other, but since the whole architecture is built to reduce, avoid, and cache approximations because they're expensive, it's not the default.

[SPACECADET3D]

In the end the zero test problem is undecidable for reasonably complicated expressions, so sadly there is no guarantee that you can rewrite one Computable into another even if they evaluate to the same. For polynomials you can do finite field evaluation tests to prove equality with a likelihood bound of your choosing. That may be interesting for hyperreal too.

[timschmidt]

Yes. One of those problems with no neat solution, and worse no performant one. :)

You might find this bit of performance engineering interesting: https://github.com/timschmidt/hyperreal/blob/8a016808f4b0ba3...

The matrix math layer wanted that kind of optimization to avoid worst case operations.