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A better method is to run the impact_bmad container here, which has a conda env with lume impact setup inside it and then navigate to your lume impact notebook and run it once in jupyterlab in the container.

Examples here  

Examples here:  https://github.com/ericcropp/Impact-T_Examples/

Additional information on these examples: Running Impact-T on s3df

Useful links:

Documentation
Documentation
Github

github

Current release info

NameDownloadsVersionPlatforms
Conda Recipe
Conda Downloads
Conda Version

Conda Platforms

Installing Non-MPI Lume-Impact

This method uses tunneling to connect to jupyter lab. To use jupyter lab through ondemand additional steps need to be done.

Prerequisites:

ssh to the iana node with tunneling enable:

  1. Ssh into s3df login node with port forwarding (5555 can be changed to any preferred port):

    Code Block
     ssh -L 5555:localhost:5555 <SLAC UNIX USERNAME>@s3dflogin.slac.stanford.edu
  2. Connect to Iana compute cluster :

    Code Block
     ssh -L 5555:localhost:5555 iana


(First time only) Install conda via miniconda:

This will install conda to the home directory

  1. Code Block
    wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/Miniconda3-latest-Linux-x86_64.sh
  2. Code Block
    bash /tmp/Miniconda3-latest-Linux-x86_64.sh -p /sdf/home/c/<UNIX_USERNAME>/conda/
  3. Create a new Conda environment

    Code Block
    conda create -n <NEW_ENV_NAME> -c conda-forge python=3.8 dask distributed ipykernel numpy scipy deap h5py pint matplotlib mpi4py 

Install Lume-Impact for the conda environment used to activate jupyterlab as shown below:

Code Block
conda activate <NEW_ENV_NAME>
Installing lume-impact from the conda-forge channel can be achieved by adding conda-forge to your channels with:


Code Block
conda config --add channels conda-forge

conda config --set channel_priority strict

Once the conda-forge channel has been enabled, lume-impact can be installed with:




Code Block
conda install lume-impact


Install other packages (optional):


Code Block
conda config --add channels conda-forge
conda install pydantic=1.10
conda install xopt=1.4.1


It is possible to list all of the versions of lume-impact available on your platform with:




Code Block
conda search lume-impact --channel conda-forge


Run a jupyterlab server with the impact conda env activated:

  • ** do only first time ** install jupyter lab if not installed: 
Code Block
conda install jupyterlab
  • Run jupyter and click on the link to open in your browser:
Code Block
 jupyter lab --no-browser --port 5555  


Impact-T Executables

Here impact is the conda env you are using.

Impact-T is available through conda-forge and can be installed via:

conda create -n impact source activate impact 

or conda activate impact 

For non-MPI conda install -c conda-forge impact-t

After these steps, the IMPACT-T executable ImpactTexe or ImpactTexe-mpi, respectively, will be in your PATH environment variable and is thus ready to use like any regular command-line command.

If the Impact-T executables are still not found, then you should go to the conda env folder, find the executables and manually add them to your path.




Visit https://github.com/impact-lbl/IMPACT-T for these and further instructions, including those to build from source.

MPI Lume-Impact

To use

Lune

run Lume-Impact in parallel one can use mpi. These steps follow this notebook.

  1. install the mpi version of impact-t instead of the regular impact-t when creating the conda env (nb: this is the same env with xopt, jupyterlab, lume-impact etc)
  2. Code Block
    conda install -c conda-forge impact-t=*=mpi_openmpi*

    3. configure the settings to point to where your impact-t executable is. It should be in the conda env files. Here eric used an conda env called xopt

    1. Code Block
      'command': '/sdf/home/c/cropp/conda/envs/xopt/bin/ImpactTexe',    
      'command_mpi': '/sdf/home/c/cropp/conda/envs/xopt/bin/ImpactTexe-mpi',

More information here: impact-T