LEARNING-BASED PLACEMENT FOR CONGESTION MITIGATION

Abstract: mechanisms to control cell density in circuit layouts to mitigate placement congestion that learn from post-route target outputs of an electronic design automation system and implement an empirical bayes mechanisms to adapt the target to a specific component placer's achievable outputs. the disclosed mechanisms solve for component placement on a global scale and obviate the application of incremental congestion estimation and mitigation.

Inventor(s): Anthony Dimitri Armand Agnesina, Rongjian Liang, Geraldo Pradipta, Anand Kumar Rajaram, Haoxing Ren

CPC Classification: G06F30/32 (ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models ))

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