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The aim of this first part is to present the physical problems and the robust and accurate numerical schemes that are implemented for computing stationary solutions, to show a few computational examples and to explain how the basic GPELab functions work.
A methodology based on image subtraction was implemented for computing soil porosity and NAPL volumes in each 0.35 mm × 0.35 mm × 1 mm voxel of the columns.
Improvements have been implemented for prospective studies.
The numerical procedure is based on the finite-volume approach and is implemented for parallel computing.
An Apache Hadoop cloud computing platform was implemented for decreasing computation time, and pathway information from the KEGG was applied for discovering meaningful biological correlations.
To ensure the reliability and accuracy of the GPU-based program, double precision floating and intrinsic functions are implemented for the explicit FE computing.
This approach could be implemented, for instance, with parallel computing in order to tackle computational costly real-world problems.
The compute intensive operations (e.g. the matrix-vector multiplications and the assembly of the sensitivity matrix) were realized as compute kernels, which were implemented for both, CPU and GPU hardware.
The statistical test described above can be implemented for any location and size of the segment s under that probing window, and the P-value can be computed.
The constraint is implemented by computing the probabilities of possible patterns for cell division for any fixed number of CSCs.
Distance-based reconstruction of gene order phylogeny can be implemented by computing breakpoint and inversion distances.
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