Title :
Efficient ANN-based interconnect delay and crosstalk modeling
Author_Institution :
Dept. of Electr. Eng., Hartford Univ., West Hartford, CT
Abstract :
The dominance of system performance by interconnect delay in deep-submicron design presents many challenges to physical design tool developers. This paper presents an efficient ANN-based technique for modeling interconnect crosstalk in integrated circuits. ANN models for user-defined interconnect primitives called wirecells are trained and tested using a database created using a suitable simulation package. For fixed wirecell length and geometry, inputs to the ANN include signal frequency, input voltage amplitude, near and far end termination impedances. Outputs derived from the ANN include crosstalk voltage peak and RMS values and spectral composition. Experimental results demonstrate the ability of this approach to successfully predict coupled noise in modest cpu times compared with existing approaches
Keywords :
SPICE; VLSI; circuit layout CAD; circuit optimisation; crosstalk; electromagnetic coupling; feedforward neural nets; integrated circuit interconnections; integrated circuit layout; integrated circuit modelling; learning (artificial intelligence); multilayer perceptrons; timing; EM coupling; RMS values; SPICE; VLSI; coupled noise; crosstalk voltage peak; database generation; efficient ANN-based technique; end termination impedances; feedforward neural net; input voltage amplitude; integrated circuits; interconnect crosstalk modeling; interconnect delay modeling; learning; local experts; multilayer perceptron; signal frequency; simulation package; spectral composition; timing driven layout design; user-defined interconnect primitives; wirecells; Circuit simulation; Circuit testing; Crosstalk; Delay; Integrated circuit interconnections; Integrated circuit modeling; Integrated circuit packaging; Spatial databases; System performance; Voltage;
Conference_Titel :
Microelectronics, 2000. Proceedings. 2000 22nd International Conference on
Conference_Location :
Nis
Print_ISBN :
0-7803-5235-1
DOI :
10.1109/ICMEL.2000.838793