Add performance benchmark

[tmigot]

We can get inspiration from this:
https://github.com/lanl-ansi/rosetta-opf/blob/main/nlpmodels.jl / https://discourse.julialang.org/t/ac-optimal-power-flow-in-various-nonlinear-optimization-frameworks/78486

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First step is to have benchmarks to measure potential regressions:

• Add benchmark folder
• Pkg benchmark grad
• Pkg benchmark jac
• Pkg benchmark hess
• Pkg benchmark jprod
• Pkg benchmark jtprod
• Pkg benchmark hprod
• Add NLS variants
• Add JuMP in the benchmark for local run
• Parallelize for local run
• Add benchmark README
• Add PkgBenchmark CI
• Add push results from Benchmark CI
• Store benchmark result in the package
• Add documentation page listing available benchmarks

[gdalle]

Coming up in https://github.com/gdalle/SparsityDetectionComparison

[gdalle]

Here are the comparison results between JuMP, SCT and Symbolics for the first 90% or so of the OptimizationProblems.jl suite. A couple of the last problems take a really long time (probably for Symbolics) and I haven't yet narrowed down which ones. But I think the trend is clear.