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This leads to important advantages in terms of simplicity of implementation for both parallelism and adaptivity at sector boundaries.
We use a hybrid parallel implementation for both shared and distributed memory multi-core host systems comprising CUDA-capable devices.
The development activity includes the project, the synthesis and the assembly of the on-board avionics equipment, together with the software implementation for both data collection and some basic GNC algorithms.
We provide an implementation for both methods.
For no-flux boundary conditions, there is a simple implementation for both lattice and lattice-free models.
High satisfaction predicts implementation, for both continuous and utility versions of the scale, and for both staff and service users.
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There are user-level UNIX implementations for both, to export UNIX file trees to the network.
Regression can be accomplished through the Adaptive Model Rules Regressor, which includes implementations for both vertical and horizontal parallelism.
Implementations for both, parametric and non-parametric methods are available through the R packages SuperCurve (Hu et al., 2007) and RPPanalyzer (Mannsperger et al., 2010a).
We compare the results of MDLS to the exact Pareto front, as well as to two metaheuristics also analyzed by Florios et al., NSGA-II and SPEA2; they use standard implementations for both.
On the contrary, we denote the traditional ADER implementation, for which both the spatial WENO reconstruction and the LSDG predictor are performed on the conserved variables, as 'ADER-Cons'.
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