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An architecture-driven metric for simultaneous placement and global routing for FPGAs
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 37th Annual Design Automation Conference table of contents
Los Angeles, California, United States
Pages: 567 - 572  
Year of Publication: 2000
ISBN:1-58113-187-9
Authors
Yao-Wen Chang  Chip Implementation Center, National Science Council of Taiwan ROC, Hsinchu, Taiwan and Department of Computer and Information Science, National Chiao Tung University, Hsinchu 300, Taiwan
Yu-Tsang Chang
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
EDAC : Electronic Design Automation Consortium
IEEE-CAS : Circuits & Systems
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 3,   Downloads (12 Months): 15,   Citation Count: 5
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ABSTRACT

FPGA routing resources typically consist of segments of various lengths. Due to the segmented routing architectures, the traditional measure of wiring cost (wirelength, delay, congestion, etc) based on geometric distance and/or channel density is no longer accurate for FPGAs. Researchers have shown that the number of segments, instead of geometric (Manhattan) distance, traveled by a net is the most crucial factor in controlling the routing delay and cost in an FPGA. Further, the congestion information of a routing channel shall be measured by the available segments of specific lengths, instead of the density in a channel alone. In this paper, we propose an architecture-driven metric for simultaneous FPGA placement and global routing. The new metric considers the available segments and their lengths to optimize the wiring cost for placement and global routing. Experiments by employing a cluster growth placement and maze routing to demonstrate the new metric show respective average reductions of 8%, 20%, and 19% in the number of tracks used (area), maximum net delay, and average net delay based on the Lucent Technologies ORCA2C-like and the Xilinx XC4000EX-like architectures, compared with the traditional metric of geometric distance and channel density.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Yao-Wen Chang: colleagues
Yu-Tsang Chang: colleagues