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This process can be speeded up by implementing parallelized algorithms on a Graphical Processing Unit (GPU).
The working environment is represented by a Bump-surface entity, constantly updated by a parallel algorithm implemented on a graphical processing unit (GPU).
One runs on a graphical processing unit (GPU) and the other is executed on a cellular nonlinear network universal machine (CNN-UM).
To expedite the classification, the MOGA-MFNN is implemented on a graphical processing unit (GPU), which significantly increases the computation speed.
In this study, a high-order compact finite difference scheme for the solution of fluid flow problems is implemented to run on a Graphical Processing Unit (GPU) using Compute Unified Device Architecture CUDAA).
This study aims to evaluate the capability of a lattice-Boltzmann method (LBM) code deployed on a graphical processing unit (GPU) using a large eddy sub-grid turbulence model for cross-flow ventilation of an idealised cubical building at wind-tunnel scale.
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This means a single product with a central processing unit (for the standard mathematical computation of most chips) and a graphical processing unit (for games and video, and increasingly supercomputing).
In this paper, an approach is developed to perform explicit finite element simulations of contact-impact problems with a graphical processing unit (GPU) using a special edge-smooth triangular shell element based on ES-FEM.
We report on the design of a new plasma control system for the HBT-EP tokamak that utilizes a graphical processing unit (GPU) to magnetically control the 3D perturbed equilibrium state [1] of the plasma.
This chapter presents a graphical processing unit (GPU) implementation of the minimum spanning tree (MST) algorithm for undirected graphs.
A graphical processing unit (GPU) version of TUFLOW was used resulting in an 80x execution time speed-up compared to the central processing unit (CPU) version.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com