Programming Massively Parallel Architectures ...
Document type :
Communication dans un congrès avec actes
Title :
Programming Massively Parallel Architectures using MARTE: a Case Study
Author(s) :
de Oliveira Rodrigues, Antonio Wendell [Auteur]
Contributions of the Data parallelism to real time [DART]
Guyomarch, Frédéric [Auteur]
Contributions of the Data parallelism to real time [DART]
Dekeyser, Jean-Luc [Auteur]
Contributions of the Data parallelism to real time [DART]
Contributions of the Data parallelism to real time [DART]
Guyomarch, Frédéric [Auteur]

Contributions of the Data parallelism to real time [DART]
Dekeyser, Jean-Luc [Auteur]
Contributions of the Data parallelism to real time [DART]
Conference title :
2nd Workshop on Model Based Engineering for Embedded Systems Design (M-BED 2011) on Date Conference 2011
City :
Grenoble
Country :
France
Start date of the conference :
2011-03-14
Publication date :
2011-03-18
English keyword(s) :
GPU
OpenCL
MARTE
Embedded Systems
H.263
OpenCL
MARTE
Embedded Systems
H.263
HAL domain(s) :
Informatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
English abstract : [en]
Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially ...
Show more >Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially the GPUs(Graphics Processing Unit), have led the race of floating-point performance since 2003. While the performance improvement of general-purpose microprocessors has slowed significantly, the GPUs have continued to improve relentlessly. As of 2009, the ratio between many-core GPUs and multicore CPUs for peak floating-point calculation throughput is about 10 times. However, as parallel programming requires a non-trivial distribution of tasks and data, developers find it hard to implement their applications effectively. Aiming to improve the use of many-core processors, this work presents an case-study using UML and MARTE profile to specify and generate OpenCL code for intensive signal processing applications. Benchmark results show us the viability of the use of MDE approaches to generate GPU applications.Show less >
Show more >Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially the GPUs(Graphics Processing Unit), have led the race of floating-point performance since 2003. While the performance improvement of general-purpose microprocessors has slowed significantly, the GPUs have continued to improve relentlessly. As of 2009, the ratio between many-core GPUs and multicore CPUs for peak floating-point calculation throughput is about 10 times. However, as parallel programming requires a non-trivial distribution of tasks and data, developers find it hard to implement their applications effectively. Aiming to improve the use of many-core processors, this work presents an case-study using UML and MARTE profile to specify and generate OpenCL code for intensive signal processing applications. Benchmark results show us the viability of the use of MDE approaches to generate GPU applications.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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