Routing Cost Prediction at Placement Stage Using Machine Learning Technique
碩士 === 國立中央大學 === 電機工程學系 === 106 === The placement results have large impacts on routing results. In order to keep circuit performance and eliminate non-ideal effects, we have to predict routing cost at layout placement stage. Most of current approaches use semi-perimeter method to predict the routi...
Main Authors: | Hwa-Yi Tseng, 曾華逸 |
---|---|
Other Authors: | Chien-Nan Liu |
Format: | Others |
Language: | zh-TW |
Published: |
2017
|
Online Access: | http://ndltd.ncl.edu.tw/handle/2t283w |
Similar Items
-
EMC-driven placement for MCM
by: Tseng,Yau_Hwa, et al.
Published: (1996) -
Routability-driven Macro Placement with Machine-Learning Technique
by: Yu-Yin Kuo, et al.
Published: (2017) -
Placement and routing in VLSI design problem using single row routing technique
by: Johar, Farhana, et al.
Published: (2007) -
Development of a Two-Stage ESS-Scheduling Model for Cost Minimization Using Machine Learning-Based Load Prediction Techniques
by: Minsu Park, et al.
Published: (2019-06-01) -
Study on the Placement and Routing Techniques for FPGA Design
by: Jan-Nam Lin, et al.
Published: (2000)