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  • This paper introduces a new method for optimization of coverage-driven verification (CDV) that is based on evolutionary computing. In comparison to the classical CDV that utilizes random search, using this method the convergence to the maximum coverage is much faster, fewer transactions are used and no manual effort is required from the user. Moreover, the optimization is targeted to the verification process itself without the dependence on the circuit that is verified.
  • This paper introduces a new method for optimization of coverage-driven verification (CDV) that is based on evolutionary computing. In comparison to the classical CDV that utilizes random search, using this method the convergence to the maximum coverage is much faster, fewer transactions are used and no manual effort is required from the user. Moreover, the optimization is targeted to the verification process itself without the dependence on the circuit that is verified. (en)
Title
  • Application of Evolutionary Computing for Optimization of Functional Verification
  • Application of Evolutionary Computing for Optimization of Functional Verification (en)
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  • Application of Evolutionary Computing for Optimization of Functional Verification
  • Application of Evolutionary Computing for Optimization of Functional Verification (en)
skos:notation
  • RIV/00216305:26230/14:PU112077!RIV15-MSM-26230___
http://linked.open...avai/riv/aktivita
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  • P(LD12036), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
  • Šimková, Marcela
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  • 3732
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  • RIV/00216305:26230/14:PU112077
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  • Functional Verification, Optimization, Evolutionary Algorithms (en)
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  • [4CF227A4F654]
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  • Počítačové architektury a diagnostika 2014
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  • Šimková, Marcela
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number of pages
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  • Technická univerzita v Liberci
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  • 978-80-7494-027-9
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  • 26230
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