article · 2019
Netlist Optimization by Gate Merging
Calebe Conceição, Ricardo Reis
Cited by 3Abstract and details only
Abstract
The small number of logic functions in a traditional cell library limits the optimization of digital design regarding transistors, wires, and vias count. It affects traditional quality metrics, like area and total wire length. Our new library free approach enables such optimization by using tools for automatic layout synthesis of any transistor network. Using the traditional cell-based design flow to generate the initial netlist, we postprocess it considering to replace groups of cells by a single new cell of equivalent logic, which is not available in the cell library. Tests were performed over a standard benchmark, using a predictive 45nm cell library. Our approach reduces on average the number of transistors of a circuit by 21% when compared to a traditional solution. When to other logic minimization tools, it reduces transistor count by 2%, and by consequence, we obtain an average reduction of 9% on the number of wire segments, 5% in total wire length and 6% fewer pins. It also impacts the traditional performance metrics, demanding in 5% less area.
Cite this paper
Conceição, C., & Reis, R. (2019). Netlist Optimization by Gate Merging. https://doi.org/10.1109/vlsi-soc.2019.8920291
Conceição, Calebe, and Ricardo Reis. “Netlist Optimization by Gate Merging.” 2019, pp. 236–37, https://doi.org/10.1109/vlsi-soc.2019.8920291.
Conceição, Calebe, and Ricardo Reis. 2019. “Netlist Optimization by Gate Merging.” https://doi.org/10.1109/vlsi-soc.2019.8920291.
Conceição, C. and Reis, R. (2019) ‘Netlist Optimization by Gate Merging’. Available at: https://doi.org/10.1109/vlsi-soc.2019.8920291.
@article{conceicao2019netlist,
title = {{Netlist Optimization by Gate Merging}},
author = {Conceição, Calebe and Reis, Ricardo},
pages = {236--237},
year = {2019},
doi = {10.1109/vlsi-soc.2019.8920291}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.