LeXInt

KO | EN

gitlite — search

#ai #go #android #machine-learning #rust #docker #macos #java #nodejs #windows #awesome #awesome-list #vue #openai

(★ 11)

Time Integration Package

LeXInt Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

#  [LeXInt](#)

![Python](https://img.shields.io/badge/Python-FFD43B?style=for-the-badge&logo=python&logoColor=blue)
![C++](https://img.shields.io/badge/c++-%2300599C.svg?style=for-the-badge&logo=c%2B%2B&logoColor=white)
![nVIDIA](https://img.shields.io/badge/nVIDIA-%2376B900.svg?style=for-the-badge&logo=nVIDIA&logoColor=white)
![VS Code](https://img.shields.io/badge/VSCode-0078D4?style=for-the-badge&logo=visual%20studio%20code&logoColor=white)
![Github](https://img.shields.io/badge/GitHub-100000?style=for-the-badge&logo=github&logoColor=white)

[**Le**](#)ja interpolation for e[**X**](#)ponential [**Int**](#)egrators is a temporal integration package that comprises of a compilation of exponential integrators, specifically, the Exponential Rosenbrock (EXPRB) and Exponential Propagation Iterative Runge-Kutta (EPIRK) solvers.

The action of the matrix exponential or the $\varphi_l(z)$ functions on a vector is computed using the method of polynomial interpolation at Leja points. For homogenous linear PDEs, one can obtain the ***exact*** solution (in time) by directly computing the matrix exponential using the functions ``real_Leja_exp`` and/or ``imag_Leja_exp``, whereas for nonhomogenous linear PDEs, one can use ``real_Leja_phi_nl`` and/or ``imag_Leja_phi_nl``. The algorithmic details can be found in the cited literature.

## Requirements
- For Python:
  - Python 3.10 (or later)

- For C++:
  - gcc compiler

- For CUDA:
  - NVIDIA GPU
  - CUDA 11.2 (or later)
  - nvcc compiler

## Literature
The publications associated with this code:

- Deka, Moriggl, and Einkemmer (2025), *LeXInt: GPU-accelerated Exponential Integrators package*, SoftwareX, 29, 101949 
[[DOI]](https://doi.org/10.1016/j.softx.2024.101949) [[arXiv:2310.08344]](https://doi.org/10.48550/arXiv.2310.08344)

- Deka, Einkemmer, and Tokman (2023), *LeXInt: Package for Exponential Integrators employing Leja interpolation*, SoftwareX, 21, 101302 
[[DOI]](https://doi.org/10.1016/j.softx.2022.101302) [[arXiv:2208.08269]](https://doi.org/10.48550/arXiv.2208.08269)

Other related publications:
- Caliari et al. (2014), *Comparison of software for computing the action of the matrix exponential*, BIT Numer. Math., 54, 113 
[[DOI]](https://doi.org/10.1007/s10543-013-0446-0)

- Deka \& Einkemmer (2022), *Efficient adaptive step size control for exponential integrators*, Comput. Math. Appl., 123, 59 
[[DOI]](https://doi.org/10.1016/j.camwa.2022.07.011) [[arXiv:2102.02524]](https://doi.org/10.48550/arXiv.2102.02524)

- Deka \& Einkemmer (2022), *Exponential Integrators for Resistive Magnetohydrodynamics: Matrix-free Leja Interpolation and Efficient Adaptive Time Stepping*, ApJS, 259, 57 
[[DOI]](https://doi.org/10.3847/1538-4365/ac5177) [[arXiv:2108.13622]](https://doi.org/10.48550/arXiv.2108.13622)

- Hochbruck \& Ostermann (2010), *Exponential integrators*, Acta Numer., 19, 209 
[[DOI]](https://doi.org/10.1017/S0962492910000048)

## Future Prospects
We will MPI-parallelise the CUDA/C++ code.

## Contact
Pranab J. Deka (<pranab.deka@kuleuven.be>) 
Lukas Einkemmer (<lukas.einkemmer@uibk.ac.at>) 
Mayya Tokman (<mtokman@ucmerced.edu>)

In case you face issues using LeXInt, kindly contact Pranab J. Deka.

## Acknowledgements
Alexander Moriggl contributed to the development of the CUDA version.

LeXInt

LeXInt Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

LeXInt

LeXInt Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README