Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2011-07-04
Computer Science
Distributed, Parallel, and Cluster Computing
Compumag 2011
Scientific paper
The electrical and electronic engineering has used parallel programming to solve its large scale complex problems for performance reasons. However, as parallel programming requires a non-trivial distribution of tasks and data, developers find it hard to implement their applications effectively. Thus, in order to reduce design complexity, we propose an approach to generate code for hybrid architectures (e.g. CPU + GPU) using OpenCL, an open standard for parallel programming of heterogeneous systems. This approach is based on Model Driven Engineering (MDE) and the MARTE profile, standard proposed by Object Management Group (OMG). The aim is to provide resources to non-specialists in parallel programming to implement their applications. Moreover, thanks to model reuse capacity, we can add/change functionalities or the target architecture. Consequently, this approach helps industries to achieve their time-to-market constraints and confirms by experimental tests, performance improvements using multi-GPU environments.
Dekeyser Jean-Luc
Guyomarc'H Frédéric
Menach Yvonnick Le
Oliveira Rodrigues Antonio Wendell de
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