DAKOTA
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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
- {{#lowercase:DAKOTA}}
System Variables
- HPC_{{#uppercase:DAKOTA}}_DIR - installation directory
- HPC_{{#uppercase:DAKOTA}}_BIN - program executable directory
- HPC_{{#uppercase:DAKOTA}}_LIB - library directory
- HPC_{{#uppercase:DAKOTA}}_INC - include file directory
{{#if: |==Citation== If you publish research that uses DAKOTA you have to cite it as follows: