FMI.jl is a free-to-use software library for the Julia programming language which integrates FMI (fmi-standard.org): load or create, parameterize, differentiate and simulate FMUs seamlessly inside the Julia programming language!

FMIFlux.jl is a free-to-use software library for the Julia programming language, which offers the ability to place FMUs (fmi-standard.org) everywhere inside of your ML topologies and still keep the resulting model trainable with a standard (or custom) FluxML training process.

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The current implementation of `LinearAlgebra.eigen` does not support sensitivities. DifferentiableEigen.jl offers an `eigen` function that is differentiable by every AD-framework with support for ChainRulesCore.jl or ForwardDiff.jl.

FMIExport.jl is a free-to-use software library for the Julia programming language which allows for the export of FMUs (fmi-standard.org) from any Julia-Code. FMIExport.jl is completely integrated into FMI.jl.

FMIImport.jl implements the import functionalities of the FMI-standard (fmi-standard.org) for the Julia programming language. FMIImport.jl provides the foundation for the Julia packages FMI.jl and FMIFlux.jl.

FMICore.jl implements the low-level equivalents of the C-functions and C-data types of the FMI-standard (fmi-standard.org) for the Julia programming language.

FMIBuild.jl holds dependencies that are required to compile and zip a Functional Mock-Up Unit (FMU) compliant to the FMI-standard (fmi-standard.org). Because this dependencies should not be part of the compiled FMU, they are out-sourced into this package. FMIBuild.jl provides the build-commands for the Julia package FMIExport.jl.

FMIZoo.jl is a collection of testing and example FMUs (fmi-standard.org) for the Julia libraries FMI.jl and FMIFlux.jl.

DistributedHyperOpt.jl is a package similar to HyperOpt.jl, but explicitly focusing on distributed (multi-processing) hyperparameter optimization by design.

Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event

FMIBase.jl provides the foundation for the Julia packages FMIImport.jl and FMIExport.jl.