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decoder-design

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Devanik21 / A-Machine-Learning-Approach-for-Optimal-Power-Gating-in-Decoders

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The project uses an ML surrogate model (e.g., Random Forest) to instantly predict a decoder's PPA (Power, Performance, Area) based on design parameters optimizing trade-off, significantly boosting efficiency and enabling a faster, data-driven VLSI design flow .

machine-learning random-forest power-gating vlsi-design digital-circuit-optimization decoder-design low-power-electronics ppa-optimization
  • Updated Oct 26, 2025
  • Python

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