Simulating the Behaviour of the Human Brain on NVIDIA GPU: cuHinesBatch & cuThomasBatch implementations
Understand the human brain is one of the century challenges. On this work we are going to achieve a small step towards this objective presenting a novel data layout in order to compute more efficiently the Hines algorithm on GPU. A more general tridiagonal solver is going to be presented too.
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/117810 |
| Acceso en línea: | https://hdl.handle.net/2117/117810 |
| Access Level: | acceso abierto |
| Palabra clave: | Parallel processing (Electronic computers) Multiprocessors Neurona Algoritme de Hines GPUs Multiprocessador Sistema Tri-diagonal Lineal Escalabilitat Algoritme de Thomas PCR CR Processament Paral·lel cuSPARSE CUDA Human Brain Neuron Hines Algorithm Parallel Computing Multicore Tridiagonal Linear Systems Scalability Thomas Algorithm Parallel Processing Processament en paral·lel (Ordinadors) Multiprocessadors Àrees temàtiques de la UPC::Informàtica |
| Sumario: | Understand the human brain is one of the century challenges. On this work we are going to achieve a small step towards this objective presenting a novel data layout in order to compute more efficiently the Hines algorithm on GPU. A more general tridiagonal solver is going to be presented too. |
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