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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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