pySDC is a Python implementation of the spectral deferred correction approach and its flavors, esp. the parallel-in-time extension PFASST. It is intended for rapid prototyping and educational purposes. New ideas can be tested and first toy problems can be easily implemented.
The pySDC project is a Python implementation of the spectral deferred correction (SDC) approach and its flavors, esp. the multilevel extension MLSDC and the parallel-in-time variant PFASST. It is intended for rapid prototyping and educational purposes. New ideas like e.g. sweepers or predictors can be tested and first toy problems can be easily implemented.
The code is hosted on GitHub, see https://github.com/Parallel-in-Time/pySDC, and PyPI, see https://pypi.python.org/pypi/pySDC.
pip install pySDC will give you a core version of pySDC to work with, working with the developer version is most often the better choice. We thus recommend to checkout the code from GitHub and install the dependencies e.g. by using a conda environment.
For this, pySDC ships with environment files which can be found in the folder
etc/. Use these as e.g.
conda env create --yes -f etc/environment-base.yml
To check your installation, run
pytest pySDC/tests -m NAME
NAME corresponds to the environment you chose (
base in the example above).
You may need to update your
PYTHONPATH by running
in particular if you want to run any of the playgrounds, projects or tutorials.
import statements there assume that the
pySDC's base directory is part of
For many examples,
LaTeX is used for the plots, i.e. a decent installation of this is needed in order to run those examples.
petsc4py, a C++ compiler is required (although installation may go through at first).
For more details on
pySDC, check out http://www.parallel-in-time.org/pySDC.
This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 955701 (TIME-X).
The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Belgium, France, Germany, and Switzerland.
This project also received funding from the German Federal Ministry of Education and Research (BMBF) grant 16HPC047.
The project also received help from the Helmholtz Platform for Research Software Engineering - Preparatory Study.