Hierarchical sequence compaction for power estimation

  • Authors:
  • Radu Marculescu;Diana Marculescu;Massoud Pedram

  • Affiliations:
  • Department of Electrical Engineering Systems, University of Southern California, Los Angeles, CA;-;Department of Electrical Engineering Systems, University of Southern California, Los Angeles, CA

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

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Abstract

This paper presents an effective technique forcompacting a large sequence of input vectors into a muchsmaller one such that when the two sequences are applied toany circuit, the resulting power dissipations are nearly thesame. Specifically, this paper introduces the hierarchicalmodeling of Markov chains as a flexible framework forcapturing not only complex spatiotemporal correlations, butalso dynamic changes in the characteristics of the inputsequence. The new framework has a high degree ofadaptability, i.e. the hierarchical model is dynamically grownaccording to the sequence behavior. Experimental resultsdemonstrate that large compaction ratios can be obtainedwithout a significant loss in accuracy (less than 5% on average)of power estimates.