Data-flow assisted behavioral partitioning for embedded systems

  • Authors:
  • Samir Agrawal;Rajesh K. Gupta

  • Affiliations:
  • Synopsys, Inc., 700 East Middlefield Road, Mountain View, CA;Department of Information and Computer Science, University of California, Irvine, Irvine, CA

  • Venue:
  • DAC '97 Proceedings of the 34th annual Design Automation Conference
  • Year:
  • 1997

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Abstract

In this paper we present a novel compiler-directed approach tosystem-level partitioning for a given description of system functionalityin a hardware description language (HDL). The algorithmis based on a definition-use analysis of the storage in the systemmodel to ensure that the resulting portions can be implemented in aloosely-coupled multi-rate execution model with minimal synchronizationbetween the portions. The cost of the hardware-softwareinterface, in terms of amount of buffering required, is computed accuratelyas a part of the partitioning cost function using a data-flowreaching analysis. The proposed algorithm has been implementedand experimental results show up to 65% improvement in buffersizes over the min-cut partitioning algorithm.