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| author | B. Watson <yalhcru@gmail.com> | 2020-10-11 16:10:57 -0400 |
|---|---|---|
| committer | Willy Sudiarto Raharjo <willysr@slackbuilds.org> | 2020-10-17 09:36:43 +0700 |
| commit | 2c3623e58a45e056122804dbcc875d9d7f08f126 (patch) | |
| tree | b57f3442aa9e53f98fc2ccd7867fdb7e7f9e4752 | |
| parent | c4b8c52a0783e0e8d0a994b5c1f508f46f22cb60 (diff) | |
| download | slackbuilds-2c3623e58a45e056122804dbcc875d9d7f08f126.tar.gz | |
academic/dakota: Fix README.
Signed-off-by: B. Watson <yalhcru@gmail.com>
Signed-off-by: Willy Sudiarto Raharjo <willysr@slackbuilds.org>
| -rw-r--r-- | academic/dakota/README | 20 |
1 files changed, 11 insertions, 9 deletions
diff --git a/academic/dakota/README b/academic/dakota/README index 452cf802ea..3a0d5dbe15 100644 --- a/academic/dakota/README +++ b/academic/dakota/README @@ -1,14 +1,16 @@ The Dakota toolkit provides a flexible, extensible interface between analysis codes and iteration 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 capabilities. These capabilities may be used on -their own or as components within advanced strategies such as -surrogate-based optimization, mixed integer nonlinear programming, or -optimization under 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 capabilities. These capabilities may +be used on their own or as components within advanced strategies such +as surrogate-based optimization, mixed integer nonlinear programming, +or optimization under uncertainty. -Optional dependency: openmpi (for distributed memory parallel capabilities) +Optional dependency: openmpi (for distributed memory parallel +capabilities) -You can build with multiple jobs by setting the MAKEFLAGS environment variable. +You can build with multiple jobs by setting the MAKEFLAGS environment +variable. |