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A study on unroutable placement recognition

Published: 30 March 2014 Publication History

Abstract

To avoid producing unroutable placement solutions, many state-of-the-art routability-driven placers iteratively invoke global routers to evaluate their placement solutions and then perform routability optimization. However, using a global router to evaluate hard-to-route placement solutions may spend considerable runtime and it cannot guarantee that a placement is truly unroutable to any router. This paper presents an unroutable placement recognizer based on a window-based layout scanning algorithm, which can confirm some placements that are exactly unroutable among a set of hard-to-route placements. In addition, if a placement is recognized to be unroutable, the recognizer can point out unroutable regions and report a lower bound of total overflow for the placement. The experimental results reveal that the proposed recognizer can find out 16 placements that are definitely unroutable among 23 widely used hard-to-route global routing benchmarks.

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Cited By

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  • (2017)Routability Optimization for Industrial Designs at Sub-14nm Process Nodes Using Machine LearningProceedings of the 2017 ACM on International Symposium on Physical Design10.1145/3036669.3036681(15-21)Online publication date: 19-Mar-2017
  • (2016)BEOL stack-aware routability prediction from placement using data mining techniques2016 IEEE 34th International Conference on Computer Design (ICCD)10.1109/ICCD.2016.7753259(41-48)Online publication date: Oct-2016
  • (2015)ISPD 2015 Benchmarks with Fence Regions and Routing Blockages for Detailed-Routing-Driven PlacementProceedings of the 2015 Symposium on International Symposium on Physical Design10.1145/2717764.2723572(157-164)Online publication date: 29-Mar-2015

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cover image ACM Conferences
ISPD '14: Proceedings of the 2014 on International symposium on physical design
March 2014
180 pages
ISBN:9781450325929
DOI:10.1145/2560519
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 30 March 2014

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ISPD'14
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ISPD'14: International Symposium on Physical Design
March 30 - April 2, 2014
California, Petaluma, USA

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ISPD '14 Paper Acceptance Rate 14 of 40 submissions, 35%;
Overall Acceptance Rate 62 of 172 submissions, 36%

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Cited By

View all
  • (2017)Routability Optimization for Industrial Designs at Sub-14nm Process Nodes Using Machine LearningProceedings of the 2017 ACM on International Symposium on Physical Design10.1145/3036669.3036681(15-21)Online publication date: 19-Mar-2017
  • (2016)BEOL stack-aware routability prediction from placement using data mining techniques2016 IEEE 34th International Conference on Computer Design (ICCD)10.1109/ICCD.2016.7753259(41-48)Online publication date: Oct-2016
  • (2015)ISPD 2015 Benchmarks with Fence Regions and Routing Blockages for Detailed-Routing-Driven PlacementProceedings of the 2015 Symposium on International Symposium on Physical Design10.1145/2717764.2723572(157-164)Online publication date: 29-Mar-2015

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