Description
Describe the bug 🐞
The results of the Simple Interval Rootfinding benchmark claim a 33x speed-up compared to the MATLAB solver, however the conditions of the benchmark were not the same.
The main differences are:
- MATLAB is using a modified Dekker's algorithm, whereas the fast Julia result was using the Newton-Raphson method (that uses the derivative information)
- The default termination conditions of MATLAB and NonlinearSolve.jl are different.
- The Julia result was obtained on newer hardware
- The operating system was different
Expected behavior
The benchmarks should be "optimal, fair, and reproducible". This one fails in the "fair" comparison category.
When I run the MATLAB code on an Intel i7-11700K @3.60GHz (Rocketlake), the elapsed time is ~0.12 s or roughly the same as using the NonlinearSolve.jl bisection method. (Caveat - the hardware is different.)
Additional context
The benchmark was presented at JuliaCon 2023 (see https://youtu.be/O-2F8fBuRRg?si=GF24GyZEBek0Yi-Y&t=1022) with a claim of an additional 5-fold speed-up or a time of under 0.01 s. An un-merged pull request is mentioned in the video, but I was not able to locate it.