Proceedings of the European Conference on Design Automation.
DOI: 10.1109/edac.1991.206469
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Concurrent min-max simulation

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Cited by 10 publications
(7 citation statements)
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“…Increasing process variation in sub-micron devices has prompted research in various directions, including Monte-Carlo techniques [14,18,27], bounded delay simulation [4,11,12,17,25], statistical timing analysis [2,3,26,28] and the classical bounded delay timing analysis [7]. Timing analysis finds corners in the design process in a vector independent manner by using specified gate delays.…”
Section: Introductionmentioning
confidence: 99%
“…Increasing process variation in sub-micron devices has prompted research in various directions, including Monte-Carlo techniques [14,18,27], bounded delay simulation [4,11,12,17,25], statistical timing analysis [2,3,26,28] and the classical bounded delay timing analysis [7]. Timing analysis finds corners in the design process in a vector independent manner by using specified gate delays.…”
Section: Introductionmentioning
confidence: 99%
“…Our simulator produces timing results more accurate than those obtainable with previous polynomial-time min-max timing simulation algorithms [3,22], particularly in the presence of nested reconvergent fanouts. Our polynomial-time reconvergerit fanout analysis is also able to detect some event-orderlings not detectable with a previously published exponential-time simulator [ 191.…”
Section: Introductionmentioning
confidence: 72%
“…Note that G9.del[Al] = [4,9] and G7.del[Al] = [2,7], so the transitions on G7 and G9 would appear to overlap if we used only the del arrays, as in [3]. If we were to analyze these circuits using the reconvergent fanout analysis proposed in [22], then we would find that in subcircuit Kanehara-0, a glitch is produced at Y 1 by P-machines originating from A1 ad A2, and also by an S-machine originating from G1. The analysis in [22] would therefore indicate the presence of a glitch on Y 1.…”
Section: Ifmentioning
confidence: 98%
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