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Gate Delay Estimation With Library Compatible Current Source Models and Effective Capacitance.

Authors :
Garyfallou, Dimitrios
Simoglou, Stavros
Sketopoulos, Nikolaos
Antoniadis, Charalampos
Sotiriou, Christos P.
Evmorfopoulos, Nestor
Stamoulis, George
Source :
IEEE Transactions on Very Large Scale Integration (VLSI) Systems; May2021, Vol. 29 Issue 5, p962-972, 11p
Publication Year :
2021

Abstract

As process geometries shrink below 45 nm, accurate and efficient gate-level timing analysis becomes even more challenging. Modern VLSI interconnects are more resistive, signals no longer resemble saturated ramps, and gate input pins exhibit a significant Miller effect. Over recent years, the semiconductor industry has adopted current source models (CSMs) for accurate gate modeling. Industrial gate models, however, are precharacterized assuming capacitive loads, which poses significant challenges to the approximation of the highly resistive load interconnect with an effective capacitance (C<subscript>eff</subscript>). In fact, most related works are either computationally expensive or unable to approximate the output slew. Furthermore, they require additional precharacterization and ignore the Miller effect. In this article, we present an iterative methodology for fast and accurate gate delay estimation. The proposed approach accurately computes the driver output waveform, using closed-form formulas to calculate a C<subscript>eff</subscript> per waveform segment, while accounting for their interdependence. Thus, it allows for variable analysis resolution exploiting an accuracy/runtime tradeoff. In contrast to prior works, our approach is compatible with conventional CSMs and considers the impact of Miller capacitance. We evaluate our method on representative driver-load test circuits consisting of interconnects with arbitrary RC characteristics and ASU ASAP 7-nm standard cells. The proposed method achieves 1.3% and 2.5% delay and slew root-mean-square percentage error (RMSPE) against SPICE, respectively. In addition, it provides high efficiency, as it converges in 2.3 iterations on average. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10638210
Volume :
29
Issue :
5
Database :
Complementary Index
Journal :
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Publication Type :
Academic Journal
Accession number :
150071200
Full Text :
https://doi.org/10.1109/TVLSI.2021.3061484