Benchmarks / Competitors
Competitor Benchmarks
This benchmark compars Basin against argmin, gomez, and nlopt. Each plot shows suboptimality, f(x) − f*, against wall-clock time on
log–log axes: how far down the objective each library gets, and how long
it spends getting there. Lower and further left is better.
Gradient Descent · Rosenbrock
Steepest descent with a More–Thuente line search: first-order, identical configuration on both sides.
Nelder–Mead · Rosenbrock
Derivative-free Nelder–Mead. Basin and argmin run from a bit-identical initial simplex (standard coefficients); gomez and nlopt construct their own simplex with their default coefficients.
L-BFGS · Rosenbrock
Limited-memory BFGS (m = 10), quasi-Newton; Basin and argmin both use a More–Thuente line search; nlopt uses its bundled L-BFGS (no line-search knob exposed).
NEWUOA · Styblinski–Tang
Powell's model-based derivative-free NEWUOA. Basin's implementation is based on the modernized version from PRIMA, whereas nlopt uses Powell's reference.
Measured 2026-06-21 on AMD Ryzen 9 7900 12-Core Processor
(linux/x64). All libraries run on the Vec<f64> backend (gomez through its
own bundled nalgebra::DVector<f64>). The GD,
NM, and L-BFGS cases run from the classic Rosenbrock start to a
200-iteration cap. Each point is the median wall-clock
time per iteration over repeated runs (nlopt, which exposes no
per-iteration hook, is sampled per function evaluation as a best-so-far
curve); the solvers are deterministic, so only the timing varies.
To watch basin's solvers converge interactively, try the visualizer.