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Memory bounds for the distributed execution of a hierarchical Synchronous Data-Flow graph

Authors :
Slaheddine Aridhi
Maxime Pelcat
Jean-Francois Nezan
Karol Desnos
Institut d'Électronique et des Technologies du numéRique (IETR)
Université de Nantes (UN)-Université de Rennes 1 (UR1)
Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)
Université européenne de Bretagne - European University of Brittany (UEB)
CIV Texas Instruments
Texas Instruments
Nantes Université (NU)-Université de Rennes 1 (UR1)
Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes)
Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)
Source :
ICSAMOS, Proceedings 2012 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation, 12th International Conference on Embedded Computer Systems: Architecture, Modeling and Simulation (SAMOS XII), 12th International Conference on Embedded Computer Systems: Architecture, Modeling and Simulation (SAMOS XII), Jul 2012, Agios Konstantinos, Greece. pp.160
Publication Year :
2012
Publisher :
IEEE, 2012.

Abstract

International audience; This paper presents an application analysis technique to define the boundary of shared memory requirements of Multiprocessor System-on-Chip (MPSoC) in early stages of development. This technique is part of a rapid prototyping process and is based on the analysis of a hierarchical Synchronous Data-Flow (SDF) graph description of the system application. The analysis does not require any knowledge of the system architecture, the mapping or the scheduling of the system application tasks. The initial step of the method consists of applying a set of transformations to the SDF graph so as to reveal its memory characteristics. These transformations produce a weighted graph that represents the different memory objects of the application as well as the memory allocation constraints due to their relationships. The memory boundaries are then derived from this weighted graph using analogous graph theory problems, in particular the Maximum-Weight Clique (MWC) problem. Stateof-the-art algorithms to solve these problems are presented and a heuristic approach is proposed to provide a near-optimal solution of the MWC problem. A performance evaluation of the heuristic approach is presented, and is based on hierarchical SDF graphs of realistic applications. This evaluation shows the efficiency of proposed heuristic approach in finding near optimal solutions.

Details

Database :
OpenAIRE
Journal :
2012 International Conference on Embedded Computer Systems (SAMOS)
Accession number :
edsair.doi.dedup.....c7906e6a4b455d012055c73ec757f582
Full Text :
https://doi.org/10.1109/samos.2012.6404170