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1 change: 1 addition & 0 deletions binder/Project.toml
Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
[deps]
BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
CUDSS = "45b445bb-4962-46a0-9369-b4df9d0f772e"
MadNLP = "2621e9c9-9eb4-46b1-8089-e8c72242dfb6"
MadNLPGPU = "d72a61cc-809d-412f-99be-fd81f4b8a598"
NLPModelsIpopt = "f4238b75-b362-5c4c-b852-0801c9a21d71"
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2 changes: 2 additions & 0 deletions docs/Project.toml
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@ CTModels = "34c4fa32-2049-4079-8329-de33c2a22e2d"
CTParser = "32681960-a1b1-40db-9bff-a1ca817385d1"
CTSolvers = "d3e8d392-8e4b-4d9b-8e92-d7d4e3650ef6"
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
CUDSS = "45b445bb-4962-46a0-9369-b4df9d0f772e"
CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
CommonSolve = "38540f10-b2f7-11e9-35d8-d573e4eb0ff2"
Expand Down Expand Up @@ -43,6 +44,7 @@ CTModels = "0.19"
CTParser = "0.9"
CTSolvers = "0.5"
CUDA = "6"
CUDSS = "0.7"
CairoMakie = "0.15"
Colors = "0.13"
CommonSolve = "0.2"
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3 changes: 3 additions & 0 deletions docs/src-literate/guided-tour.jl
Original file line number Diff line number Diff line change
Expand Up @@ -366,9 +366,12 @@ plot(plt_bang[1]; legend=:bottomright, xlabel="time", ylabel="altitude")
# Moving to the GPU is a single token, `:gpu`, which auto-completes to `(:collocation, :exa, :madnlp, :gpu)`. It requires the `:exa` modeler (hence `@def`, not the macro-free API — cf. the definition section) plus a CUDA-capable GPU.
#
# In a seminar or on Binder there is usually **no functional GPU**, so the call is *expected to fail* — that is the pedagogical point: the `:gpu` token needs a specific setup. We wrap it in a `try/catch` so the tour keeps running and shows the raised exception.
#
# The GPU stack is armed by **three** loads, not two: `MadNLPGPU`, `CUDA` and `CUDSS`. Miss the third and the failure you get is a missing package, not a missing device.

using MadNLPGPU
using CUDA
using CUDSS

try
global sol_gpu = solve(goddard, :gpu; grid_size=1000, display=false)
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150 changes: 62 additions & 88 deletions docs/src/assets/Manifest.toml

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2 changes: 2 additions & 0 deletions docs/src/assets/Project.toml
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@ CTModels = "34c4fa32-2049-4079-8329-de33c2a22e2d"
CTParser = "32681960-a1b1-40db-9bff-a1ca817385d1"
CTSolvers = "d3e8d392-8e4b-4d9b-8e92-d7d4e3650ef6"
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
CUDSS = "45b445bb-4962-46a0-9369-b4df9d0f772e"
CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0"
Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
CommonSolve = "38540f10-b2f7-11e9-35d8-d573e4eb0ff2"
Expand Down Expand Up @@ -43,6 +44,7 @@ CTModels = "0.19"
CTParser = "0.9"
CTSolvers = "0.5"
CUDA = "6"
CUDSS = "0.7"
CairoMakie = "0.15"
Colors = "0.13"
CommonSolve = "0.2"
Expand Down
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