Xplace: An Extremely Fast and Extensible Global Placement Framework

Lixin Liu; Bangqi Fu; Martin D. F. Wong; Evangeline F. Y. Young

doi:10.1145/3489517.3530485

Xplace: An Extremely Fast and Extensible Global Placement Framework

Lixin Liu, Bangqi Fu, Martin D. F. Wong, Evangeline F. Y. Young

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Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

16 Citations (Scopus)

Abstract

Placement serves as a fundamental step in VLSI physical design. Recently, GPU-based global placer DREAMPlace[1] demonstrated its superiority over CPU-based global placers. In this work, we develop an extremely fast GPU accelerated global placer Xplace which achieves around 2x speedup with better solution quality compared to DREAMPlace. We also plug a novel Fourier neural network into Xplace as an extension to further improve the solution quality. We believe this work not only proposes a new, fast, extensible placement framework but also illustrates a possibility to incorporate a neural network component into a GPU accelerated analytical placer.

Original language	English
Title of host publication	59th ACM/IEEE Design Automation Conference, DAC 2022
Publisher	Association for Computing Machinery (ACM)
Pages	1309-1314
Number of pages	6
ISBN (Print)	9781450391429
DOIs	https://doi.org/10.1145/3489517.3530485
Publication status	Published - 13 Jul 2022
Event	59th ACM/IEEE Design Automation Conference, DAC 2022 - San Francisco, United States Duration: 10 Jul 2022 → 14 Jul 2022 https://www.dac.com/About/Conference-Archive/59th-DAC-2022 (Conference website) https://www.dac.com/Portals/0/DAC%2059/59DAC%20Onsite%20Guide_v3.pdf?ver=GbBS5sBuhmEVJWVEz9CNIg%3d%3d (Conference programme) https://dl.acm.org/doi/proceedings/10.1145/3489517 (Conference proceedings)

Publication series

Name	ACM/IEEE Design Automation Conference - Proceedings
ISSN (Print)	0738-100X

Conference

Conference	59th ACM/IEEE Design Automation Conference, DAC 2022
Country/Territory	United States
City	San Francisco
Period	10/07/22 → 14/07/22
Internet address	https://www.dac.com/About/Conference-Archive/59th-DAC-2022 (Conference website) https://www.dac.com/Portals/0/DAC%2059/59DAC%20Onsite%20Guide_v3.pdf?ver=GbBS5sBuhmEVJWVEz9CNIg%3d%3d (Conference programme) https://dl.acm.org/doi/proceedings/10.1145/3489517 (Conference proceedings)

Scopus Subject Areas

Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering
Modelling and Simulation

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10.1145/3489517.3530485

Cite this

@inproceedings{7c412d215b18482195a40cf56b92d584,

title = "Xplace: An Extremely Fast and Extensible Global Placement Framework",

abstract = "Placement serves as a fundamental step in VLSI physical design. Recently, GPU-based global placer DREAMPlace[1] demonstrated its superiority over CPU-based global placers. In this work, we develop an extremely fast GPU accelerated global placer Xplace which achieves around 2x speedup with better solution quality compared to DREAMPlace. We also plug a novel Fourier neural network into Xplace as an extension to further improve the solution quality. We believe this work not only proposes a new, fast, extensible placement framework but also illustrates a possibility to incorporate a neural network component into a GPU accelerated analytical placer.",

author = "Lixin Liu and Bangqi Fu and Wong, {Martin D. F.} and Young, {Evangeline F. Y.}",

note = "Funding Information: This research was partially supported by ACCESS - AI Chip Center for Emerging Smart Systems, Hong Kong SAR. Publisher Copyright: {\textcopyright} 2022 ACM.; 59th ACM/IEEE Design Automation Conference, DAC 2022 ; Conference date: 10-07-2022 Through 14-07-2022",

year = "2022",

month = jul,

day = "13",

doi = "10.1145/3489517.3530485",

language = "English",

isbn = "9781450391429",

series = "ACM/IEEE Design Automation Conference - Proceedings",

publisher = "Association for Computing Machinery (ACM)",

pages = "1309--1314",

booktitle = "59th ACM/IEEE Design Automation Conference, DAC 2022",

address = "United States",

url = "https://www.dac.com/About/Conference-Archive/59th-DAC-2022, https://www.dac.com/Portals/0/DAC%2059/59DAC%20Onsite%20Guide_v3.pdf?ver=GbBS5sBuhmEVJWVEz9CNIg%3d%3d, https://dl.acm.org/doi/proceedings/10.1145/3489517",

}

Liu, L, Fu, B, Wong, MDF & Young, EFY 2022, Xplace: An Extremely Fast and Extensible Global Placement Framework. in 59th ACM/IEEE Design Automation Conference, DAC 2022. ACM/IEEE Design Automation Conference - Proceedings, Association for Computing Machinery (ACM), pp. 1309-1314, 59th ACM/IEEE Design Automation Conference, DAC 2022, San Francisco, California, United States, 10/07/22. https://doi.org/10.1145/3489517.3530485

Xplace: An Extremely Fast and Extensible Global Placement Framework. / Liu, Lixin; Fu, Bangqi; Wong, Martin D. F. et al.
59th ACM/IEEE Design Automation Conference, DAC 2022. Association for Computing Machinery (ACM), 2022. p. 1309-1314 (ACM/IEEE Design Automation Conference - Proceedings).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AB - Placement serves as a fundamental step in VLSI physical design. Recently, GPU-based global placer DREAMPlace[1] demonstrated its superiority over CPU-based global placers. In this work, we develop an extremely fast GPU accelerated global placer Xplace which achieves around 2x speedup with better solution quality compared to DREAMPlace. We also plug a novel Fourier neural network into Xplace as an extension to further improve the solution quality. We believe this work not only proposes a new, fast, extensible placement framework but also illustrates a possibility to incorporate a neural network component into a GPU accelerated analytical placer.

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Xplace: An Extremely Fast and Extensible Global Placement Framework

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