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The obtained array is optimal with respect to the number of processing elements (PEs) for a given problem size.
Second, we perform the accommodation of index spaces to the projection direction to obtain hexagonal SA with optimal number of processing elements (PE) for a given problem size.
The performed static-scaling studies can serve as a guide for users to be able to select an appropriate discretization for a given problem size.
This Galerkin method exhibits more rapid convergence, for a given problem size, than any other scheme hitherto reported, as demonstrated by a benchmark of the magnetic diffusion problem and by comparison to numerous kinematic dynamos from the literature.
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We also find a rich, regular pattern, in which phase transitions for longer implicates or prime implicates are less steep at a given problem size and all the phase transitions sharpen with increasing problem size.
A given problem size has a fixed number of samples (unit of work).
The efficiency, speed-up, and runtime are expressed as functions of the number of processors scaled by the number of processors that gives the minimal runtime for the given problem size.
For a given problem or application, once the size of the processing signal is decided, e i is also known.
The job validity test V, is true only when the size of valid jobs is greater than the size of machines for a given problem.
For a given problem, convergence of the SPH solution is seen to increase with decreasing particle size and spacing.
Many upgrading alternatives can be generated for a given problem.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com