GPGPU implementation of the BFECC algorithm for pure advection equations
In the present work an implementation of the Back and Forth Error Compensation and Correction (BFECC) algorithm specially suited for running on General-Purpose Graphics Processing Units (GPGPUs) through Nvidia`s Compute Unified Device Architecture (CUDA) is analyzed in order to solve transient pure...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/8745 |
| Acceso en línea: | http://hdl.handle.net/11336/8745 |
| Access Level: | acceso abierto |
| Palabra clave: | Gpgpu Cuda Bfecc Semi-Lagrangian Level-Set Navier-Stokes https://purl.org/becyt/ford/2.3 https://purl.org/becyt/ford/2 |
| Sumario: | In the present work an implementation of the Back and Forth Error Compensation and Correction (BFECC) algorithm specially suited for running on General-Purpose Graphics Processing Units (GPGPUs) through Nvidia`s Compute Unified Device Architecture (CUDA) is analyzed in order to solve transient pure advection equations. The objective is to compare it to a previous explicit version used in a Navier-Stokes solver fully written in CUDA. It turns out that BFECC could be implemented with unconditional stable stability using Semi-Lagrangian time integration allowing larger time steps than Eulerian ones. |
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