CPU-based Application Transformation to CUDA: Transformation of CPU-based Applications To Leverage on Graphics Processors using CUDA - Couverture souple

Mohd Nazlee, Anas; Hussin, Fawnizu Azmadi

 
9783659171215: CPU-based Application Transformation to CUDA: Transformation of CPU-based Applications To Leverage on Graphics Processors using CUDA
Couverture souple
ISBN 10 : 3659171212 ISBN 13 : 9783659171215
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

Scientific computation requires a great amount of computing power especially in floating-point operation but a high-end multi-cores processor is currently limited in terms of floating point operation performance and parallelization. Recent technological advancement has made parallel computing technically and financially feasible using Compute Unified Device Architecture (CUDA) developed by NVIDIA. This research focuses on measuring the performance of CUDA and implementing CUDA for a scientific computation involving the process of porting the source code from CPU to GPU using direct integration technique. The ported source code is then optimized by managing the resources to achieve performance gain over CPU. It is found that CUDA is able to boost the performance of the system up to 69 times in Parboil Benchmark Suite. Successful attempt at porting Serpent encryption algorithm and Lattice Boltzmann Method provided up to 7 times throughput performance gain and up to 10 times execution time performance gain respectively over the CPU. Direct integration guideline for porting the source code is then produced based on the two implementations.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Scientific computation requires a great amount of computing power especially in floating-point operation but a high-end multi-cores processor is currently limited in terms of floating point operation performance and parallelization. Recent technological advancement has made parallel computing technically and financially feasible using Compute Unified Device Architecture (CUDA) developed by NVIDIA. This research focuses on measuring the performance of CUDA and implementing CUDA for a scientific computation involving the process of porting the source code from CPU to GPU using direct integration technique. The ported source code is then optimized by managing the resources to achieve performance gain over CPU. It is found that CUDA is able to boost the performance of the system up to 69 times in Parboil Benchmark Suite. Successful attempt at porting Serpent encryption algorithm and Lattice Boltzmann Method provided up to 7 times throughput performance gain and up to 10 times execution time performance gain respectively over the CPU. Direct integration guideline for porting the source code is then produced based on the two implementations.

Biographie de l'auteur

Anas Mohd Nazlee received Masters of Science and Bachelors of Engineering in Electrical and Electronics Engineering from Universiti Teknologi PETRONAS, Malaysia in 2012 and 2009 respectively. Currently he is working as Design Engineer with Intel Microelectronics (M) Sdn. Bhd.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3659171212
ISBN 13 
9783659171215
Reliure
Broché
Nombre de pages
88
Coordonnées du fabricant
non disponible
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