Lightweight Structural Choices Operator for Technology Mapping

Technology mapping quality heavily depends on the subject graph structure. To overcome structural biases, operators construct choice nodes to enable mappings with improved node and level counts. Nevertheless, state-of-the-art structural choice operators scale poorly with graph size.We present the li...

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Vydané v:	2023 60th ACM/IEEE Design Automation Conference (DAC) s. 1 - 6
Hlavní autori:	Grosnit, Antoine, Zimmer, Matthieu, Tutunov, Rasul, Li, Xing, Chen, Lei, Yang, Fan, Yuan, Mingxuan, Bou-Ammar, Haitham
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 09.07.2023
Predmet:	Benchmark testing Complexity theory Design automation logic synthesis Machine learning structural bias problem structural choice operators
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