Dakota 6.8

Released: May 15, 2018
Release Highlights:

  • dprepro was completely re-written and has many new features, including the ability to execute arbitrary Python scripting in templates
  • Dakota's graphical user interface (GUI) was updated with many new features and bugfixes
  • Dakota now includes a suite of gradient-based optimization algorithms from the SNL-developed Rapid Optimization Library (ROL).
  • Bayesian calibration capabilities received several enhancements, including improved concurrency in evaluating optimal experimental designs

Dakota 6.7

Released: November 15, 2017
Release Highlights:

  • Graphical user interface improvements including support for a number of additional visualization types, and more...
  • Substantial improvements to multi-level and multi-fidelity methods, including greater flexbility in model hierarchies, and more...
  • Dakota now requires a C++11-compliant compiler, together with CMake 3.1 or newer (recommend 3.6 or greater).


The Dakota project delivers both state-of-the-art research and robust, usable software for optimization and UQ. Broadly, the Dakota software's advanced parametric analyses enable design exploration, model calibration, risk analysis, and quantification of margins and uncertainty with computational models. The Dakota toolkit provides a flexible, extensible interface between such simulation codes and its iterative systems analysis methods, which include:

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