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K. Bard, B. Dewey, M.-T. Hsu, T. Mitchell, K. Moody, V. Rao, R. Rose, J. Soreff and S. Washburn, “Transistor Level Tools for High-End Processor Custom Circuit De sign at IBM,” IEEE Proceedings of the Journal, Vol. 95, No. 3, 2007, pp. 530-554. doi:10.1109/JPROC.2006.889385

has been cited by the following article:

• TITLE: Graph Modeling for Static Timing Analysis at Transistor Level in Nano-Scale CMOS Circuits

  AUTHORS: Abdoul Rjoub, Almotasem Bellah Alajlouni, Hassan Almanasrah

  KEYWORDS: Critical Path Estimation; Graph Models; MOSFETs; Sequential Circuits; Transistor Level; Static Timing Analysis

  JOURNAL NAME: Circuits and Systems, Vol.4 No.2, April 17, 2013

  ABSTRACT: The development and the revolution of nanotechnology require more and effective methods to accurately estimating the timing analysis for any CMOS transistor level circuit. Many researches attempted to resolve the timing analysis, but the best method found till the moment is the Static Timing Analysis (STA). It is considered the best solution because of its accuracy and fast run time. Transistor level models are mandatory required for the best estimating methods, since these take into consideration all analysis scenarios to overcome problems of multiple-input switching, false paths and high stacks that are found in classic CMOS gates. In this paper, transistor level graph model is proposed to describe the behavior of CMOS circuits under predictive Nanotechnology SPICE parameters. This model represents the transistor in the CMOS circuit as nodes in the graph regardless of its positions in the gates to accurately estimating the timing analysis rather than inaccurate estimating which caused by the false paths at the gate level. Accurate static timing analysis is estimated using the model proposed in this paper. Building on the proposed model and the graph theory concepts, new algorithms are proposed and simulated to compute transistor timing analysis using RC model. Simulation results show the validity of the proposed graph model and its algorithms by using predictive Nano-Technology SPICE parameters for the tested technology. An important and effective extension has been achieved in this paper for a one that was published in international conference.