research-article

On the use of GP-GPUs for accelerating compute-intensive EDA applications

Authors:

Valeria Bertacco,

Debapriya Chatterjee,

Nicola Bombieri,

Hiren D. PatelAuthors Info & Claims

DATE '13: Proceedings of the Conference on Design, Automation and Test in Europe

Pages 1357 - 1366

Published: 18 March 2013 Publication History

Abstract

General purpose graphics processing units (GP-GPUs) have recently been explored as a new computing paradigm for accelerating compute-intensive EDA applications. Such massively parallel architectures have been applied in accelerating the simulation of digital designs during several phases of their development -- corresponding to different abstraction levels, specifically: (i) gate-level netlist descriptions, (ii) register-transfer level and (iii) transaction-level descriptions. This embedded tutorial presents a comprehensive analysis of the best results obtained by adopting GP-GPUs in all these EDA applications.

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Cited By

Liang YSatria MRupnow KChen D(2016)An Accurate GPU Performance Model for Effective Control Flow Divergence OptimizationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2015.250130335:7(1165-1178)Online publication date: 1-Jul-2016
https://dl.acm.org/doi/10.1109/TCAD.2015.2501303
Chen XWang YLiang YXie YYang H(2014)Run-Time Technique for Simultaneous Aging and Power Optimization in GPGPUsProceedings of the 51st Annual Design Automation Conference10.1145/2593069.2593208(1-6)Online publication date: 1-Jun-2014
https://dl.acm.org/doi/10.1145/2593069.2593208

Index Terms

On the use of GP-GPUs for accelerating compute-intensive EDA applications

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Information & Contributors

Information

Published In

cover image ACM Conferences

DATE '13: Proceedings of the Conference on Design, Automation and Test in Europe

March 2013

1944 pages

ISBN:9781450321532

General Chair:
Enrico Macii
Politecnico di Torino, IT

Sponsors

EDAA: European Design Automation Association
ECSI
EDAC: Electronic Design Automation Consortium
SIGDA: ACM Special Interest Group on Design Automation
IEEE CEDA
The Russian Academy of Sciences: The Russian Academy of Sciences

Publisher

EDA Consortium

San Jose, CA, United States

Publication History

Published: 18 March 2013

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Research-article

Conference

DATE 13

Sponsor:

EDAA
EDAC
SIGDA
The Russian Academy of Sciences

DATE 13: Design, Automation and Test in Europe

March 18 - 22, 2013

Grenoble, France

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Overall Acceptance Rate 518 of 1,794 submissions, 29%

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Cited By

Liang YSatria MRupnow KChen D(2016)An Accurate GPU Performance Model for Effective Control Flow Divergence OptimizationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2015.250130335:7(1165-1178)Online publication date: 1-Jul-2016
https://dl.acm.org/doi/10.1109/TCAD.2015.2501303
Chen XWang YLiang YXie YYang H(2014)Run-Time Technique for Simultaneous Aging and Power Optimization in GPGPUsProceedings of the 51st Annual Design Automation Conference10.1145/2593069.2593208(1-6)Online publication date: 1-Jun-2014
https://dl.acm.org/doi/10.1145/2593069.2593208

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