Package: noloadj
NoLOAD_Jax: Non Linear Optimization by Automatic Differentiation using JaxWe are happy that you will use or develop the NoLOAD_Jax.
It is anOpen Sourceproject located on GitLab athttps://gricad-gitlab.univ-grenoble-alpes.fr/design_optimization/NoLoad_v2It aims atsolving constrained optimizationproblem for the design of engineering systemsProject PresentationNoLOAD_Jax:Please have a look to NoLOAD presentation :https://noload-jax.readthedocs.io/en/latest/A scientific article presenting NoLOAD is available here:Agobert Lucas, Hodencq Sacha, Delinchant Benoit, Gerbaud Laurent, Frederic Wurtz, “NoLOAD, Open Software for Optimal Design and Operation using Automatic Differentiation”, OIPE 2020, Poland, 09-2021.https://hal.archives-ouvertes.fr/hal-03352443Please cite us when you use NoLOAD.NoLOAD_Jax CommunityPlease use the git issues system to report an error:https://gricad-gitlab.univ-grenoble-alpes.fr/design_optimization/NoLoad_v2Otherwise you can also contact the developer team using the following email adress:benoit.delinchant@G2ELab.grenoble-inp.frInstallation HelpYou can install the library as a user or as a developer. Please follow the corresponding installation steps below.PrerequisitePlease install Python 3.8 or laterhttps://www.python.org/downloads/Installation as a userPlease install NoLOAD_Jax with pip using the command prompt.If you are admin on Windows or working on a virtual environmentpip install noloadjIf you want a local installation or you are not adminpip install --user noloadjIf you are admin on Linux:sudo pip install noloadjLaunch the examples to understand how the NoLOAD_Jax works:python noloadj/01-UnconstrainedMonoObjective.py
python noloadj/02-ConstrainedMonoObjective.py
python noloadj/03-ConstrainedMultiObjective.py
python noloadj/04-ConstrainedMonoObjective2.pyEnjoy your time using NoLOAD_Jax !GPUAs it uses the JAX library, NoLOAD_Jax can run on CPU (Central Processor Unit) or GPU (Graphics Processor Unit), where GPU offers better performances than CPU.
On Windows, only CPU can be used. To use GPU you may run NoLOAD on Ubuntu.
If you want to use GPU, you need to install CUDA and CuDNN on your computer then write on Pycharm terminal :pip install --upgrade pip
pip install -U "jax[cuda12_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.htmlIf you use GPU, you need to put these lines at the beginning of your "optimization" file to avoid memory issues :import os
os.environ['XLA_PYTHON_CLIENT_PREALLOCATE']='false'
os.environ['XLA_PYTHON_CLIENT_MEM_FRACTION']='0.50'To have more information, please have a look to :https://jax.readthedocs.io/en/latest/installation.htmlIPOPT AlgorithmNoLOAD_Jax runs with SLSQP optimization algorithm from Scipy.
To install IPOPT algorithm, please install an Anaconda environment and run this command on a terminal :conda install -c conda-forge cyipoptLibrary Installation RequirementsMatplotlib >= 3.0
Scipy >= 1.2
Jax >= 0.4.18
Jaxlib >= 0.4.18
Pandas >= 1.3.5
tk >= 0.1.0
openpyxl >= 3.1.2Main Authors:B. DELINCHANT, L. GERBAUD, F. WURTZ, L. AGOBERTPartners:Vesta-System:http://vesta-system.fr/Acknowledgments:LicenceThis code is under the Apache License, Version 2.0