NDLI: FastRoute3.0: a fast and high quality global router based on virtual capacity

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FastRoute3.0: a fast and high quality global router based on virtual capacity

Content Provider	ACM Digital Library
Author	Zhang, Yanheng Xu, Yue Chu, Chris
Abstract	As an easily implemented approach, ripup and reroute has been employed by most of today's global routers, which iteratively applies maze routing to refine solution quality. But traditional maze routing is susceptible to get stuck at local optimal results. In this work, we will present a fast and high quality global router FastRoute3.0, with the new technique named virtual capacity. Virtual capacity is proposed to guide the global router at maze routing stage to achieve higher quality results in terms of overflow and runtime. During maze routing stage, virtual capacity works as a substitute for the real edge capacity in calculating the maze routing cost. There are two sub techniques included: (1) virtual capacity initialization, (2) virtual capacity update. Before the maze routing stage, FastRoute3.0 initializes the virtual capacity by subtracting the predicted overflow generated by adaptive congestion estimation (ACE) from the real edge capacity. And in the following maze routing iterations, we further reduce the virtual capacity by the amount of existing overflow (edge usage minus real edge capacity) for the edges that are still congested. To avoid excessive "pushing-away" of routing wires, the virtual capacity is increased by a fixed percentage of the existing overflow if edge usage is smaller than real edge capacity. Experimental results show that FastRoute3.0 is highly proficient dealing with ISPD98, ISPD07 and ISPD08 benchmark suites. The results outperform published ripup and reroute based academic global routers in both routability and runtime. In particular, (1) FastRoute3.0 completes routing all the ISPD98 benchmarks. (2) For ISPD07 and ISPD08 global routing contest benchmarks, it generates 12 out of 16 congestion free solutions. (3) The total runtime is enhanced greatly.
Starting Page	344
Ending Page	349
Page Count	6
File Format	PDF
ISBN	9781424428205
ISSN	10923152
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-11-10
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software Computer Science Applications

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