Scalable Uncertainty Quantification Documentation status Pipeline status Coverage report
SPUX - “Scalable Package for Uncertainty Quantification”.

SPUX is a modular framework for Bayesian inference and uncertainty quantification.
SPUX can be coupled with linear and nonlinear, deterministic and stochastic models.
SPUX supports model in any programming language (e.g. Python, R, Julia, C/C++, Fortran, Java).
SPUX scales effortlessly from serial run to parallel high performance computing clusters.
SPUX is application agnostic, with current examples in environmental dataset sciences.

SPUX is actively developed at Eawag, Swiss Federal Institute of Aquatic Science and Technology,
by researchers in the High Performance Scientific Computing Group,
For the scientific website of the SPUX project, please refer to

Documentation is available at
Source code repository is available at

You are welcome to browse through the results gallery of the models already coupled to spux at

This is free software, distributed under Apache (v2) License.

If you use this software, please cite (preprint available at
Šukys, J. and Kattwinkel, M.
"SPUX: Scalable Particle Markov Chain Monte Carlo
for uncertainty quantification in stochastic ecological models".
Advances in Parallel Computing - Parallel Computing is Everywhere,
IOS Press, (32), pp. 159–168, 2018.


Indices and tables