A resource-level parallel approach for global-routing-based routing congestion estimation and a method to quantify estimation accuracy

2014 ◽  
Author(s):  
Wen-Hao Liu ◽  
Zhen-Yu Peng ◽  
Ting-Chi Wang
Keyword(s):  
Estimation Accuracy ◽  
Global Routing ◽  
Resource Level ◽  
Routing Congestion

scholarly journals FastRoute: An Efficient and High-Quality Global Router

VLSI Design ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Min Pan ◽  
Yue Xu ◽  
Yanheng Zhang ◽  
Chris Chu
Keyword(s):  
Steiner Tree ◽  
Large Scale ◽  
Routing Algorithms ◽  
Global Routing ◽  
Optimal Solutions ◽  
Global Level ◽  
High Quality ◽  
Great Demand ◽  
Tree Construction ◽  
Routing Congestion

Modern large-scale circuit designs have created great demand for fast and high-quality global routing algorithms to resolve the routing congestion at the global level. Rip-up and reroute scheme has been employed by the majority of academic and industrial global routers today, which iteratively resolve the congestion by recreating the routing path based on current congestion. This method is proved to be the most practical routing framework. However, the traditional iterative maze routing technique converges very slowly and easily gets stuck at local optimal solutions. In this work, we propose a very efficient and high-quality global router—FastRoute. FastRoute integrates several novel techniques: fast congestion-driven via-aware Steiner tree construction, 3-bend routing, virtual capacity adjustment, multisource multi-sink maze routing, and spiral layer assignment. These techniques not only address the routing congestion measured at the edges of global routing grids but also minimize the total wirelength and via usage, which is critical for subsequent detailed routing, yield, and manufacturability. Experimental results show that FastRoute is highly effective and efficient to solve ISPD07 and ISPD08 global routing benchmark suites. The results outperform recently published academic global routers in both routability and runtime. In particular, for ISPD07 and ISPD08 global routing benchmarks, FastRoute generates 12 congestion-free solutions out of 16 benchmarks with a speed significantly faster than other routers.

scholarly journals Performance Driven Global Routing Through Gradual Refinement

VLSI Design ◽  
2002 ◽  
Vol 15 (3) ◽  
pp. 595-604 ◽  
Author(s):  
Jiang Hu ◽  
Sachin S. Sapatnekar
Keyword(s):  
Global Routing ◽  
Timing Constraints ◽  
Probabilistic Estimation ◽  
The Wire ◽  
Routing Congestion ◽  
Number Of Bends

We propose a heuristic for VLSI interconnect global routing that can optimize routing congestion, delay and number of bends, which are often competing objectives. Routing flexibilities under timing constraints are obtained and exploited to reduce congestion subject to timing constraints. The wire routes are determined through gradual refinement according to probabilistic estimation on congestions so that the congestion is minimized while the number of bends on wires is limited. The experiments on both random generated circuits and benchmark circuits confirm the effectiveness of this method.

Experimental research of indoor navigation system based on broadcast signals

2020 ◽  
Vol 49 (5) ◽  
pp. 49-57
Author(s):  
A. V. Ksendzuk ◽  
E. A. Surmin ◽  
V. V. Kachesov ◽  
S. O. Zhdanov ◽  
K. S. Shakhalov
Keyword(s):  
Navigation System ◽  
Open Space ◽  
Position Estimation ◽  
Indoor Navigation ◽  
Estimation Accuracy ◽  
Satellite Systems ◽  
Indoor Navigation System ◽  
Point To Point ◽  
Navigation Signals ◽  
Navigation Equipment

Results of an experimental study of a local navigation system based on the processing signals from broadcast sources presented. The results of the development of processing algorithms for point-to-point coordinates estimation of the object are presented. The results of the development of algorithms for trajectories estimation are presented. In performed simulation the possibility of obtaining submeter position estimation accuracy in the proposed system is shown. Development results of the navigation module demonstrator are presented. The results of experimental work in difficult navigation conditions, in the presence of shading, reflections and other factors, are presented. It is shown that the developed navigation module allows in the open space near buildings which partially obscuring the satellite systems signals to obtain accuracy higher than the GNSS navigation equipment. In indoor environment in the absence of satellite navigation signals, the developed module shows positioning accuracy not worse than 1.5 meters and provides a measurement rate 1 Hz and better.

scholarly journals Multilayer Soil Moisture Mapping at a Regional Scale from Multisource Data via a Machine Learning Method

2019 ◽  
Vol 11 (3) ◽  
pp. 284 ◽  
Author(s):  
Linglin Zeng ◽  
Shun Hu ◽  
Daxiang Xiang ◽  
Xiang Zhang ◽  
Deren Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Regional Scale ◽  
Remotely Sensed ◽  
Temporal Variations ◽  
Training Data ◽  
Estimation Accuracy ◽  
Learning Approaches ◽  
Remotely Sensed Data ◽  
Deep Soil

Soil moisture mapping at a regional scale is commonplace since these data are required in many applications, such as hydrological and agricultural analyses. The use of remotely sensed data for the estimation of deep soil moisture at a regional scale has received far less emphasis. The objective of this study was to map the 500-m, 8-day average and daily soil moisture at different soil depths in Oklahoma from remotely sensed and ground-measured data using the random forest (RF) method, which is one of the machine-learning approaches. In order to investigate the estimation accuracy of the RF method at both a spatial and a temporal scale, two independent soil moisture estimation experiments were conducted using data from 2010 to 2014: a year-to-year experiment (with a root mean square error (RMSE) ranging from 0.038 to 0.050 m3/m3) and a station-to-station experiment (with an RMSE ranging from 0.044 to 0.057 m3/m3). Then, the data requirements, importance factors, and spatial and temporal variations in estimation accuracy were discussed based on the results using the training data selected by iterated random sampling. The highly accurate estimations of both the surface and the deep soil moisture for the study area reveal the potential of RF methods when mapping soil moisture at a regional scale, especially when considering the high heterogeneity of land-cover types and topography in the study area.

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