Examples here: https://github.com/ericcropp/Impact-T_Examples/
Additional information on these examples: Running Impact-T on s3df
Current release info
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:
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
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
Code Block wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/Miniconda3-latest-Linux-x86_64.sh
Code Block bash /tmp/Miniconda3-latest-Linux-x86_64.sh -p /sdf/home/c/<UNIX_USERNAME>/conda/
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 |
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conda activate <NEW_ENV_NAME> |
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 |
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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 |
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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 |
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conda install jupyterlab |
- Run jupyter and click on the link to open in your browser:
Code Block |
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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-Impact in parallel one can use mpi
- install the mpi version of impact-t
Code Block conda install -c conda-forge impact-t=*=mpi_openmpi*
More information here: impact-T