Generator Functions
Here we list many generator functions included with libEnsemble.
Important
See the API for generator functions here.
Sampling
-
Various generators for sampling a space. The non-persistent function is called as needed.
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Various persistent generators (persists on a worker) for sampling a space. After the initial batch each generator creates
p
new random points for everyp
points that are returned. Persistent sampling with variable resources
Various persistent sampling generators that assign different resources to each simulation.
Optimization
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Asynchronously Parallel Optimization Solver for finding Multiple Minima (APOSMM).
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Bayesian optimization with a Gaussian process driven by an Ax multi-task algorithm.
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Distributed evolutionary algorithms (community example)
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Distributed optimization methods for minimizing sums of convex functions. (community example)
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Samples uniformly in non-persistent mode then runs an NLopt local optimization runs in persistent mode.
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Multiobjective multidisciplinary design optimization using the VTMOP Fortran package. (community example)
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Bayesian Optimization package for determining optimal input parameter configurations for applications/executables using ytopt. (community example)
Modeling and Approximation
Finite-difference parameter finder
Uses ECNoise to determine a suitable finite difference parameters for a mapping
F
fromR^n
toR^m
.-
Gaussian Process-based adaptive sampling using gpcam.
-
Modular Bayesian calibration/inference framework using Surmise (demonstration of cancelling previous issued simulations).
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Evaluates points generators by the Tasmanian sparse grid library