Decomposition-aware layout optimization for 20/14nm standard cells

Wang, Lynn T. N.; Madhavan, Sriram; Malik, Shobhit; Chiu, Eric; Capodieci, Luigi

doi:10.1117/12.2046147

Cited by 3 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The DFM Pattern-based Optimizations (DFM-POP) provides automated design layout pattern correction based on context-aware patterns [5], enables early detection and fixing (repair by construction) of DRC+ into the in-design flow (Place and Route), with negligible physical or timing impacts during physical synthesis [2]. While all these methodologies improve the manufacturability of the design (fig.…”

Section: Auto-fixing Methodologies For Mas Scoringmentioning

confidence: 99%

Design for manufacturability (DFM) in-design fixing for improving manufacturability aware scoring (MAS)

Ruiz

Wang

Batarseh

et al. 2023

DTCO and Computational Patterning II

View full text Add to dashboard Cite

Design for Manufacturability (DFM) in-design fixing methodologies are developed to improve Manufacturability Aware Scoring (MAS). Two methodologies have been evaluated. For the first methodology, DFM recommended rules are inserted in the reference flow for rip-up-and-reroute, thus fixing DFM rule violations, improving the MAS score. For the second methodology, pattern classification is used to classify the recommended rules into patterns based on the profiling of multiple layout designs. A library of fixable patterns with corresponding fixes is built. The pattern library is then inserted in the rip-up-and-reroute flow to fix the DFM rule violations, improving the MAS score. The methodologies are demonstrated on 28nm technology. Results show an average fix rate of 89.1 % for a design with a core utilization of 0.6 and 78.4% with a core utilization of 0.6 for three DFM MAS enclosure rules, VIA2, VIA3 and VIA4 layers.

show abstract

Section: Auto-fixing Methodologies For Mas Scoringmentioning

confidence: 99%

Design for manufacturability (DFM) in-design fixing for improving manufacturability aware scoring (MAS)

Ruiz

Wang

Batarseh

et al. 2023

DTCO and Computational Patterning II

View full text Add to dashboard Cite

show abstract

“…Manufacturability Analysis and Scoring (MAS) is a well established DFM check that has been introduced for advanced semiconductor technology nodes <=55nm [1,2,3]. The deck analyzes designs for the usage of minimum ground rules.…”

Section: Introductionmentioning

confidence: 99%

Machine learning architecture evaluation for fast and accurate weak point detection

Lee

Schroeder

Rezaeifakhr

et al. 2023

DTCO and Computational Patterning II

View full text Add to dashboard Cite

This paper proposes a new methodology that can greatly accelerate Manufacturability Analysis & Scoring (MAS) deck runtime. The intention of this work is to provide a quick preview check to ensure that a new design will pass MAS signoff. Instead of running the deck on the full design, the input design is sampled down to a few random locations which are then analyzed. Furthermore, the actual MAS checks are replaced by an ML trained lookup methodology that keys off very simple design parameter like layer area density and layer perimeter density. The output of the deck is a simple PASS/FAIL statement and a range forecast for the MAS score based on a statistical assessment. We can demonstrate 4x runtime improvement while incurring minor tradeoffs for accuracy.

show abstract

Design technology co-optimization for N14 Metal1 layer

Duan

Chen

et al. 2016

2016 China Semiconductor Technology International Conference (CSTIC)

View full text Add to dashboard Cite

Decomposition-aware layout optimization for 20/14nm standard cells

Cited by 3 publications

References 6 publications

Design for manufacturability (DFM) in-design fixing for improving manufacturability aware scoring (MAS)

Design for manufacturability (DFM) in-design fixing for improving manufacturability aware scoring (MAS)

Machine learning architecture evaluation for fast and accurate weak point detection

Design technology co-optimization for N14 Metal1 layer

Contact Info

Product

Resources

About