Rethinking Reinforcement Learning based Logic Synthesis

Combinational profiles of sequential benchmark circuits

Franc Brglez, David Bryan, and Krzysztof Kozminski · 1989

Earlier work this paper cites.

Logic synthesis and optimization benchmarks user guide: version 3.0

Saeyang Yang · 1991

Earlier work this paper cites.

Policy gradient methods for reinforcement learning with function approximation

Richard S Sutton, David A McAllester, Satinder P Singh, and Yishay Mansour · 2000

Earlier work this paper cites.

Abc: A system for sequential synthesis and verification

Alan Mishchenko et al · 2007

Earlier work this paper cites.

The epfl combinational benchmark suite

Luca Amarú, Pierre-Emmanuel Gaillardon, and Giovanni De Micheli · 2015

Earlier work this paper cites.

A synthesis-parameter tuning system for autonomous design-space exploration

Matthew M Ziegler, Hung-Yi Liu, George Gristede, Bruce Owens, Ricardo Nigaglioni, and Luca P Carloni · 2016

Cited alongside, same era.

A parallelized iterative improvement approach to area optimization for lut-based technology mapping

Gai Liu and Zhiru Zhang · 2017

Cited alongside, same era.

Deep learning for logic optimization algorithms

Winston Haaswijk, Edo Collins, Benoit Seguin, Mathias Soeken, Frédéric Kaplan, Sabine Süsstrunk, and Giovanni De Micheli · 2018

Cited alongside, same era.

Reinforcement learning: An introduction

Richard S Sutton and Andrew G Barto · 2018

Cited alongside, same era.

Developing synthesis flows without human knowledge

Cunxi Yu, Houping Xiao, and Giovanni De Micheli · 2018

Cited alongside, same era.

Scalable generic logic synthesis: One approach to rule them all

Heinz Riener, Eleonora Testa, Winston Haaswijk, Alan Mishchenko, Luca Amarù, Giovanni De Micheli, and Mathias Soeken · 2019

Later among the works it cites.

Drills: Deep reinforcement learning for logic synthesis

Abdelrahman Hosny, Soheil Hashemi, Mohamed Shalan, and Sherief Reda · 2020

Later among the works it cites.

Exploring logic optimizations with reinforcement learning and graph convolutional network

Keren Zhu, Mingjie Liu, Hao Chen, Zheng Zhao, and David Z Pan · 2020

Later among the works it cites.

Boils: Bayesian optimisation for logic synthesis

Antoine Grosnit, Cédric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, and Haitham Bou-Ammar · 2022

Closest in time.

Himap: A heuristic and iterative logic synthesis approach

Xing Li, Lei Chen, Fan Yang, Mingxuan Yuan, Hongli Yan, and Yupeng Wan · 2022

Closest in time.