korali is a high performance framework for optimization, sampling and Bayesian uncertainty quantification of large scale computational models.

The framework is based on the TORC task-parallel library for clusters, which is designed to provide unified programming and runtime support for computing platforms that range from single-core systems to hybrid multicore-GPU clusters and heterogenous Grid based supercomputers.

For the documentation of korali go here.