DAKOTA
Revision as of 13:32, 3 December 2021 by Johnbullard (talk | contribs) (Add citation information from website)
Description
The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible, extensible interface between analysis codes and iterative systems analysis methods. DAKOTA contains algorithms for:
- optimization with gradient and nongradient-based methods;
- uncertainty quantification with sampling, reliability, stochastic expansion, and epistemic methods;
- parameter estimation with nonlinear least squares methods; and
- sensitivity/variance analysis with design of experiments and parameter study methods.
These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty.
Required Modules
Parallel
- intel
- openmpi
- dakota
System Variables
- HPC_DAKOTA_DIR - installation directory
- HPC_DAKOTA_BIN - program executable directory
- HPC_DAKOTA_LIB - library directory
- HPC_DAKOTA_INC - include file directory
Citation
If you publish research that uses DAKOTA you have to cite it as follows:
Please cite the Dakota User's Manual (or other appropriate manual) for the version you used (see SAND Reports). For example:
Adams, B.M., Bohnhoff, W.J., Dalbey, K.R., Ebeida, M.S., Eddy, J.P., Eldred, M.S., Hooper, R.W., Hough, P.D., Hu, K.T., Jakeman, J.D., Khalil, M., Maupin, K.A., Monschke, J.A., Ridgway, E.M., Rushdi, A.A., Seidl, D.T., Stephens, J.A., Swiler, L.P., and Winokur, J.G., "Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.15 User’s Manual," Sandia Technical Report SAND2020-12495, November 2021.
Previous versions of the User's Manual are available from the manuals page.