Parallel Computing Procedure for Dynamic Relaxation Method on GPU Using NVIDIAs CUDA

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Parallel Computing Procedure for Dynamic Relaxation Method on GPU Using NVIDIAs CUDA

Popis výsledku v původním jazyce

This paper introduces a procedure for parallel computing with the Dynamic Relaxation method (DR) on a Graphic Processing Unit (GPU). This method facilitates the consideration of a variety of nonlinearities in an easy and explicit manner. Because of the presence of inertial forces, a static problem leads to a transient dynamic problem where the Central Difference Method is used as a method for direct integration of equations of motion which arise from the Finite Element model. The natural characteristicof this explicit method is that the scheme can be easily parallelized. The assembly of a global stiffness matrix is not required. Due to slow convergence of this method, the high performance which GPUs provide is strongly suitable for this kind of computation. NVIDIAs CUDA is used for general-purpose computing on graphics processing units (GPGPU) for NVIDIa GPUs with CUDA capability.

Název v anglickém jazyce

Parallel Computing Procedure for Dynamic Relaxation Method on GPU Using NVIDIAs CUDA

Popis výsledku anglicky

This paper introduces a procedure for parallel computing with the Dynamic Relaxation method (DR) on a Graphic Processing Unit (GPU). This method facilitates the consideration of a variety of nonlinearities in an easy and explicit manner. Because of the presence of inertial forces, a static problem leads to a transient dynamic problem where the Central Difference Method is used as a method for direct integration of equations of motion which arise from the Finite Element model. The natural characteristicof this explicit method is that the scheme can be easily parallelized. The assembly of a global stiffness matrix is not required. Due to slow convergence of this method, the high performance which GPUs provide is strongly suitable for this kind of computation. NVIDIAs CUDA is used for general-purpose computing on graphics processing units (GPGPU) for NVIDIa GPUs with CUDA capability.

Druh

O - Ostatní výsledky

CEP obor

JM - Inženýrské stavitelství

OECD FORD obor

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Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů