JuliaSmoothOptimizers / JuliaSmoothOptimizers/ADNLPModels.jl
Add performance benchmark
- Dominant language
- Julia
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Description
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:
- [x] Add benchmark folder
- [x] Pkg benchmark grad
- [x] Pkg benchmark jac
- [x] Pkg benchmark hess
- [x] Pkg benchmark jprod
- [x] Pkg benchmark jtprod
- [x] Pkg benchmark hprod
- [x] Add NLS variants
- [ ] Add JuMP in the benchmark for local run
- [ ] Parallelize for local run
- [ ] Add benchmark README
- [x] Add PkgBenchmark CI
- [ ] Add push results from Benchmark CI
- [ ] Store benchmark result in the package
- [ ] Add documentation page listing available benchmarks
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Assessment
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