Π4U (Pi4U) is our HPC framework for Bayesian uncertainty quantification of large scale computational models.
The latest version of the Pi4U framework can be downloaded from here: pi4u_0.5.0.tar.gz (13.10.2017)
Previous public version: pi4u_0.4.1.tar.gz (22.03.2016)
Tutorial: (pdf) – (updated 13.10.2017)
Poster about Pi4U: (pdf)
Presentation at the Europar 2015 conference: (pdf)
Related publications
Pi4U framework
– Hadjidoukas P.E., Angelikopoulos P., Papadimitriou C., Koumoutsakos P., Pi4U: A high performance computing framework for Bayesian uncertainty quantification of complex models. J. Comput. Phys., 284:1–21, 2015 (doi) (pdf)
– Hadjidoukas P.E., Angelikopoulos P., Kulakova L., Papadimitriou C., Koumoutsakos P., Exploiting Task-Based Parallelism in Bayesian Uncertainty Quantification. EuroPar 2015, LLCS 2015, 9233, 532 (doi) (pdf)
Applications
– Kulakova L., Angelikopoulos P., Hadjidoukas P. E., Papadimitriou C., Koumoutsakos P., Approximate Bayesian Computation for Granular and Molecular Dynamics Simulations. Proceedings of the Platform for Advanced Scientific Computing Conference PASC’16, 2016 (doi) (pdf)
– Hadjidoukas P.E, Angelikopoulos P., Rossinelli D., Alexeev D., Papadimitriou C., Koumoutsakos P., Bayesian uncertainty quantification and propagation for discrete element simulations of granular materials. Comput. Methods Appl. Mech. Engrg., 282:218-238, 2014 (doi) (pdf)
TORC: Task-Based Runtime Library