Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2011-05-23
Computer Science
Distributed, Parallel, and Cluster Computing
Symposium en Architectures nouvelles de machines (SympA'14) (2011)
Scientific paper
Nowadays, the High Performance Computing is part of the context of embedded systems. Graphics Processing Units (GPUs) are more and more used in acceleration of the most part of algorithms and applications. Over the past years, not many efforts have been done to describe abstractions of applications in relation to their target architectures. Thus, when developers need to associate applications and GPUs, for example, they find difficulty and prefer using API for these architectures. This paper presents a metamodel extension for MARTE profile and a model for GPU architectures. The main goal is to specify the task and data allocation in the memory hierarchy of these architectures. The results show that this approach will help to generate code for GPUs based on model transformations using Model Driven Engineering (MDE).
Dekeyser Jean-Luc
Guyomarc'H Frédéric
Oliveira Rodrigues Antonio Wendell de
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