Regularising Transformations for Integral Dependencies

  • Graham M. Megson
  • Lucia Rapanotti


The high-level synthesis of parallel algorithms characterised by irregular data dependencies is a challenging task for algorithm designers. In this paper we show that for problems specified as systems of integral recurrence equations, a systematic derivation of regular arrays is possible. The approach combines established techniques based on the space-time mapping of regular (typically linear) data dependencies onto processor arrays, with systematic ways of regularising the data dependencies through powerful forms of localisation. The methods we present are applicable to a range of combinatorial problems, including the Knapsack problem, which we adopt as a case study.


Knapsack Problem Index Function Data Dependence Systolic Array Index Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 1995

Authors and Affiliations

  • Graham M. Megson
    • 1
  • Lucia Rapanotti
    • 1
  1. 1.Department of Computing ScienceThe UniversityNewcastle upon TyneUK

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