305 solve documentation

README.md

@@ -34,7 +34,7 @@
 [downloads-total-url]: https://juliapkgstats.com/pkg/OptimalControl
 
 The OptimalControl.jl package is the root package of the [control-toolbox ecosystem](https://github.com/control-toolbox).
-The control-toolbox ecosystem gathers Julia packages for mathematical control and applications. It aims to provide tools to model and solve optimal control problems with ordinary differential equations by direct and indirect methods.
+The control-toolbox ecosystem gathers Julia packages for mathematical control and applications. It aims to provide tools to model and solve optimal control problems with ordinary differential equations by direct and indirect methods, both on CPU and GPU.
 
 | **Name**          | **Badge**         |
 :-------------------|:------------------|

docs/make.jl

@@ -111,7 +111,7 @@ cp("./docs/Project.toml", "./docs/src/assets/Project.toml"; force=true)
 repo_url = "github.com/control-toolbox/OptimalControl.jl"
 
 makedocs(;
-    draft=false, # if draft is true, then the julia code from .md is not executed
+    draft=true, # if draft is true, then the julia code from .md is not executed
     # to disable the draft mode in a specific markdown file, use the following:
     # ```@meta
     # Draft = false
@@ -138,6 +138,7 @@ makedocs(;
             "Problem characteristics" => "manual-model.md",
             "Set an initial guess" => "manual-initial-guess.md",
             "Solve a problem" => "manual-solve.md",
+            "Solve on GPU" => "manual-solve-gpu.md",
             "Solution characteristics" => "manual-solution.md",
             "Plot a solution" => "manual-plot.md",
             "Compute flows" => [
@@ -163,4 +164,4 @@ makedocs(;
     plugins=[links],
 )
 
-deploydocs(; repo=repo_url * ".git", devbranch="main")
+deploydocs(; repo = repo_url * ".git", devbranch = "main", push_preview = true)

docs/src/index.md

@@ -1,6 +1,6 @@
 # OptimalControl.jl
 
-The OptimalControl.jl package is the root package of the [control-toolbox ecosystem](https://github.com/control-toolbox). The control-toolbox ecosystem gathers Julia packages for mathematical control and applications. It aims to provide tools to model and solve optimal control problems with ordinary differential equations by direct and indirect methods.
+The OptimalControl.jl package is the root package of the [control-toolbox ecosystem](https://github.com/control-toolbox). The control-toolbox ecosystem gathers Julia packages for mathematical control and applications. It aims to provide tools to model and solve optimal control problems with ordinary differential equations by direct and indirect methods, both on CPU and GPU.
 
 ## Installation
 

docs/src/manual-abstract.md

@@ -4,7 +4,7 @@ The full grammar of [OptimalControl.jl](https://control-toolbox.org/OptimalContr
 - pure Julia (and, as such, effortlessly analysed by the standard Julia parser),
 - as close as possible to the mathematical description of an optimal control problem. 
 
-While the syntax will be transparent to those users familiar with Julia expressions (`Expr`'s), we provide examples for every case that should be widely understandable. We rely heavily on [MLStyle.jl](https://thautwarm.github.io/MLStyle.jl) and its pattern matching abilities 👍🏽 for the semantic pass. Abstract definitions use the macro [`@def`](@ref).
+While the syntax will be transparent to those users familiar with Julia expressions (`Expr`'s), we provide examples for every case that should be widely understandable. We rely heavily on [MLStyle.jl](https://thautwarm.github.io/MLStyle.jl) and its pattern matching abilities 👍🏽 both for the syntactic and semantic pass. Abstract definitions use the macro [`@def`](@ref).
 
 ## [Variable](@id manual-abstract-variable)
 

docs/src/manual-solve-gpu.md

@@ -0,0 +1,13 @@
+# [Solve on GPU](@id manual-solve)
+
+```@meta
+CollapsedDocStrings = false
+```
+
+In this manual, we explain how to use the [`solve`](@ref) function from [OptimalControl.jl](https://control-toolbox.org/OptimalControl.jl) on GPU. We rely on [MadNLP](https://github.com/MadNLP/MadNLP.jl) and currently only provide support for NVIDIA thanks to [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl).
+
+```@docs; canonical=false
+solve(::CTModels.Model, ::Symbol...)
+```
+
+TBC