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Constraint-driven identification of application specific instructions in the DURASE system

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Author

  • Kevin Martin
  • Christophe Wolinski
  • Krzysztof Kuchcinski
  • Antoine Floch
  • Francois Charot

Summary, in English

This paper presents a new constraint-driven method for fast identification of computational patterns that is a part of <em>DURASE</em> system (Generic Environment for Design and Utilization of Reconfigurable Application-Specific Processors Extensions). The patterns identified by our system form a base for application specific instruction selection and processor extension generation. Our method identifies all computational patterns directly from an application graph satisfying all architectural and technological constraints imposed by target processors and FPGA devices. The considered constraints include a number of inputs and outputs, a number of operators, and a delay of the pattern critical path. Therefore the identified patterns can be well tailored to target processors. Our approach uses heavily constraint programming methods, which makes it possible to mix graph isomorphism constraints with other constraints in one formal environment. We have extensively evaluated our algorithm on MediaBench and MiBench benchmarks with tough architectural and technological constraints. The obtained patterns have good coverage of application graphs while limiting number of operators and fulfill architectural and technological constraints.

Publishing year

2009

Language

English

Pages

194-203

Publication/Series

Embedded Computer Systems: Architectures, Modeling, and Simulation / Lecture notes in computer science

Volume

5657

Document type

Conference paper

Publisher

Springer

Topic

  • Computer Science

Conference name

SAMOS IX: International Workshop on Systems, Architectures, Modeling and Simulation

Conference date

2009-07-20 - 2009-07-23

Conference place

Samos, Greece

Status

Published

Project

  • Embedded Applications Software Engineering

Research group

  • EDSLab

ISBN/ISSN/Other

  • ISSN: 1611-3349
  • ISSN: 0302-9743
  • ISBN: 978-3-642-03137-3