Solving Optimal Control Problems with Symbolic Universal Differential Equations
This tutorial has been been moved to Boltz.jl documentation. Refer to the the Symbolic Optimal Control tutorial for more details.
Appendix
julia
using InteractiveUtils
InteractiveUtils.versioninfo()
if @isdefined(LuxDeviceUtils)
if @isdefined(CUDA) && LuxDeviceUtils.functional(LuxCUDADevice)
println()
CUDA.versioninfo()
end
if @isdefined(AMDGPU) && LuxDeviceUtils.functional(LuxAMDGPUDevice)
println()
AMDGPU.versioninfo()
end
end
Julia Version 1.10.5
Commit 6f3fdf7b362 (2024-08-27 14:19 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 48 × AMD EPYC 7402 24-Core Processor
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-15.0.7 (ORCJIT, znver2)
Threads: 4 default, 0 interactive, 2 GC (on 2 virtual cores)
Environment:
JULIA_CPU_THREADS = 2
JULIA_DEPOT_PATH = /root/.cache/julia-buildkite-plugin/depots/01872db4-8c79-43af-ab7d-12abac4f24f6
LD_LIBRARY_PATH = /usr/local/nvidia/lib:/usr/local/nvidia/lib64
JULIA_PKG_SERVER =
JULIA_NUM_THREADS = 4
JULIA_CUDA_HARD_MEMORY_LIMIT = 100%
JULIA_PKG_PRECOMPILE_AUTO = 0
JULIA_DEBUG = Literate
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