2021
DOI: 10.1109/tcsi.2021.3109239
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Multi-Objective Digital Design Optimization via Improved Drive Granularity Standard Cells

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Cited by 6 publications
(3 citation statements)
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“…NSGA-II [36], one of the most popular MOEAs, has been adapted as the search tool in this and our related work [37]. The fast non-dominated sorting approach and diversity preservation strategies used ensure convergence while achieving a uniform spread of Pareto-optimal solutions [38].…”
Section: Preliminaries: Evolutionary Algorithmsmentioning
confidence: 99%
“…NSGA-II [36], one of the most popular MOEAs, has been adapted as the search tool in this and our related work [37]. The fast non-dominated sorting approach and diversity preservation strategies used ensure convergence while achieving a uniform spread of Pareto-optimal solutions [38].…”
Section: Preliminaries: Evolutionary Algorithmsmentioning
confidence: 99%
“…From all studies development since them, optimal digital synthesis is still a hot research topic even after more than two decades. Cao, Bale, and Trefzer have proposed multiobjective evolutionary optimization flow in [9]. Their work has shown that EDA solutions can be improved when provided a lager panel of cell libraries in a blend of multiple gate fanouts.…”
Section: A Digital Synthesis Literaturementioning
confidence: 99%
“…Integrated System-on-Chip (SoC) architectures are a composition of dissimilar blocks of intellectual property (IP) cores that operate at different levels of input voltage to meet the required time-related criteria [4][5][6]. Non-critical blocks consume less energy by operating at lower supply voltages (VDDL), sometimes in the sub-threshold region, while time-critical blocks require higher supply voltages (VDDH) to achieve the desired performance [7][8][9]. To ensure proper interaction between different voltage domains/cores, reliable LS circuits are necessary to maintain the signal integrity of the design, as depicted in Figure 1.…”
Section: Introductionmentioning
confidence: 99%