Foundations and Trends® in Electronic Design Automation > Vol 7 > Issue 1–2

Electronic Design Automation with Graphic Processors: A Survey

Yangdong Deng, Institute of Microelectronics, Tsinghua University, China, dengyd@tsinghua.edu.cn Shuai Mu, Institute of Microelectronics, Tsinghua University, China, mus04ster@gmail.com
 
Suggested Citation
Yangdong Deng and Shuai Mu (2013), "Electronic Design Automation with Graphic Processors: A Survey", Foundations and Trends® in Electronic Design Automation: Vol. 7: No. 1–2, pp 1-176. http://dx.doi.org/10.1561/1000000028

Published: 26 Jun 2013
© 2013 Y. Deng and S. Mu
 
Subjects
Analog Design,  Logic Design,  Physical Design,  System Level Design,  Verification,  Computational Models and Complexity,  Data structures
 
Keywords
J.6 [Computer-Aided Engineering] - Computer-aided design (CAD)
AlgorithmsDesignPerformanceElectronic Design Automation (EDA)VLSIGPUGraphics ProcessorGPGPUlogic simulationcircuit simulationmatrixlinear algebrasparse matrixgraph traversalgraph algorithmdynamic programmingsimulated annealingstructured grid
 

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In this article:
1. Introduction
2. GPU Architecture and Programming Model
3. EDA Computing Patterns
4. Accelerating Key Design Patterns on GPUs
5. GPU-Accelerated EDA Applications
6. Conclusion and Future Work
Acknowledgments
References

Abstract

Today's Integrated Circuit (IC) architects depend on Electronic Design Automation (EDA) software to conquer the overwhelming complexity of Very Large Scale Integrated (VLSI) designs. As the complexity of IC chips is still fast increasing, it is critical to maintain the momentum towards growing productivity of EDA tools. On the other hand, single-core Central Processing Unit (CPU) performance is unlikely to see significant improvement in the near future. It is thus essential to develop highly efficient parallel algorithms and implementations for EDA applications, so that their overall productivity can continue to increase in a scalable fashion. Among various emergent parallel platforms, Graphics Processing Units (GPUs) now offer the highest single-chip computing throughput. A large body of research, therefore, has been dedicated to accelerating EDA applications with GPUs. This monograph is aimed to develop a timely review of the existing literature on GPU-based EDA computing. Considering the substantial diversity of VLSI CAD algorithms, we extend a taxonomy of EDA computing patterns, which can be used as basic building blocks to construct complex EDA applications. GPU-based acceleration techniques for these patterns are then reviewed. On such a basis, we further survey recent works on building efficient data-parallel algorithms and implementations to unleash the power of GPUs for EDA applications.

DOI:10.1561/1000000028
ISBN: 978-1-60198-680-1
188 pp. $99.00
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ISBN: 978-1-60198-681-8
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Table of contents:
1. Introduction
2. GPU Architecture and Programming Model
3. EDA Computing Patterns
4. Accelerating Key Design Patterns on GPUs
5. GPU-Accelerated EDA Applications
6. Conclusion and Future Work
Acknowledgments
References

Electronic Design Automation with Graphic Processors

Today's Integrated Circuit (IC) architects depend on Electronic Design Automation (EDA) software to conquer the overwhelming complexity of Very Large Scale Integrated (VLSI) designs. As the complexity of IC chips is still fast increasing, it is critical to maintain the momentum towards growing productivity of EDA tools. On the other hand, single-core Central Processing Unit (CPU) performance is unlikely to see significant improvement in the near future. It is thus essential to develop highly efficient parallel algorithms and implementations for EDA applications so that their overall productivity can continue to increase in a scalable fashion. Among various emergent parallel platforms, Graphics Processing Units (GPUs) now offer the highest single-chip computing throughput. A large body of research has therefore been dedicated to accelerating EDA applications with GPUs.

Electronic Design Automation with Graphic Processors is a timely state-of-the-art review of the existing literature on GPU-based EDA computing. Considering the substantial diversity of VLSI Computer Aided Design (CAD) algorithms, it puts forward a taxonomy of EDA computing patterns, which can be used as basic building blocks to construct complex EDA applications. GPU-based acceleration techniques for these patterns are then reviewed, and, building on this foundation, it goes on to survey recent works on building efficient data-parallel algorithms and implementations to unleash the power of GPUs for EDA applications.

 
EDA-028