Skeletons for parallel image processing: an overview of the SKIPPER project

  • Authors:

  • Jocelyn Sérot;Dominique Ginhac

  • Affiliations:

  • LASMEA, UMR 6602 CNRS, University Blaise Pascal de Clermont-Ferrand, Campus des Cézeaux, F-63177 Aubière, France;LE2I, FRE 2309 CNRS, University of Burgundy, F-21078 Dijon, France

  • Venue:
  • Parallel Computing - Special issue: Advanced environments for parallel and distributed computing
  • Year:
  • 2002

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Abstract

This paper is a general overview of the SKIPPER project, run at Blaise Pascal University between 1996 and 2002. The main goal of the SKIPPER project was to demonstrate the applicability of skeleton-based parallel programming techniques to the fast prototyping of reactive vision applications. This proiect has produced several versions of a full-fledged integrated parallel programming environment (PPE). These PPEs have been used to implement realistic vision applications, such as road following or vehicle tracking for assisted driving, on embedded parallel platforms embarked on semi-autonomous vehicles. All versions of SKIPPER share a common front-end and repertoire of skeletons--presented in previous papers--but differ in the techniques used for implementing skeletons. This paper focuses on these implementation issues, by making a comparative survey, according to a set of four criteria (efficiency, expressivity, portability, predictability), of these implementation techniques. It also gives an account of the lessons we have learned, both when dealing with these implementation issues and when using the resulting tools for prototyping vision applications.