Tangi Migot

Tangi Migot

Computational Mathematician

JuliaSmoothOptimizers at the JuliaCon 2022

less than 1 minute read

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I showed how to use JuliaSmoothOptimizers framework to PDE-constrained optimization problems modeled with PDENLPModels.jl at this year’s JuliaCon 2022/JuMP-dev 2022. The conference featured three talks on JuliaSmoothOptimizers in the JuMP-dev stream.

Dominique Orban gave a complete overview in 25 minutes (!!) of the JuliaSmoothOptimizers organization. The talk mentions all the key packages to model optimization problems (NLPModels.jl & Co), solve models (JSOSolvers.jl & Co) and do simple yet amazing benchmarks with SolverBenchmark.jl.

Geoffroy Leconte presented RipQP.jl a multi-precision algorithm for convex quadratic optimization. The multi-precision feature illustrates the strength of pure Julia implementations, and ensuing performance.

You can re-watch the three talks on Youtube:

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Unveiling JuliaSmoothOptimizers at JuMP-dev Workshop, JuliaCon 2023

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I am thrilled to share my experiences from the recent JuMP-dev workshop that took place at the JuliaCon 2023, held at MIT in Boston, USA. As a passionate researcher in the field of numerical optimization, this year’s conference was particularly special for me, as it marked my first in-person attendance after the previous year’s online edition (read about it here). You can check the replay of my talk on youtube.

PDENLPModels.jl published in JOSS

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I am very happy to announce the publication in the Journal of Open Source Software of the paper PDENLPModels.jl: A NLPModel API for optimization problems with PDE-constraints.