Two-level Partitioning of Image Processing Algorithms for the Parallel Map-oriented Machine

  • Authors:
  • Reiner W. Hartenstein;Juergen Becker;Rainer Kress

  • Affiliations:
  • University of Kaiserslautern, Erwin-Schrödinger-Straβe, D-67663 Kaiserslautern, Germany;University of Kaiserslautern, Erwin-Schrödinger-Straβe, D-67663 Kaiserslautern, Germany;University of Kaiserslautern, Erwin-Schrödinger-Straβe, D-67663 Kaiserslautern, Germany

  • Venue:
  • CODES '96 Proceedings of the 4th International Workshop on Hardware/Software Co-Design
  • Year:
  • 1996

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Abstract

The partitioning of image processing algorithms with a novel hardware/software co-design framework (CoDe-X) is presented in this paper, where a new Xputer-architecture (parallel Map-oriented Machine) is used as universal accelerator based on a reconfigurable datapath hardware for speeding-up image processing applications. CoDe-X accepts C-programs and carries out both, the profiling-driven host/accelerator partitioning for performance optimization, and the resource-driven sequential/structural partitioning of the accelerator source code to optimize the utilization of its reconfigurable datapath resources.