Deeper sparsely nets can be optimal

Valeriu Beiu, Hanna E. Makaruk

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

The starting points of this paper are two size-optimal solutions: (i) one for implementing arbitrary Boolean functions [1]; and (ii) another one for implementing certain sub-classes of Boolean functions [2]. Because VLSI implementations do not cope well with highly interconnected nets - the area of a chip grows with the cube of the fan-in [3] - this paper will analyse the influence of limited fan-in on the size optimality for the two solutions mentioned. First, we will extend a result from Home & Hush [1] valid for fan-in A = 2 to arbitrary fan-in. Second, we will prove that size-optimal solutions are obtained for small constant fan-in for both constructions, while relative minimum size solutions can be obtained for fan-ins strictly lower than linear. These results are in agreement with similar ones proving that for small constant fan-ins (Δ = 6 ... 9), there exist VLSI-optimal (i.e., minimising AT2 ) solutions [4], while there are similar small constants relating to our capacity of processing information [5].

Original languageEnglish
Pages (from-to)201-210
Number of pages10
JournalNeural Processing Letters
Volume8
Issue number3
DOIs
Publication statusPublished - 1998
Externally publishedYes

Keywords

  • Limited fan-in
  • Size complexity
  • Threshold gates
  • VLSI complexity

ASJC Scopus subject areas

  • Software
  • Neuroscience(all)
  • Computer Networks and Communications
  • Artificial Intelligence

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