Deakin University
Browse

File(s) not publicly available

A statistical static timing analysis incorporating process variations with spatial correlations

journal contribution
posted on 2023-11-09, 04:48 authored by W Yu, HG Yang, Y Liu, J Huang, Borui Cai, R Chen
To evaluate effects of process variations on circuit delay accurately, this study proposes a Statistical Static Timing Analysis (SSTA) which incorporates process variations with spatial correlations. The algorithm applies a second order delay model that taking into account the non-Gaussian parameters - by inducting the notion of 'conditional variables', the 2D non-linear delay model is translated into 1D linear one; and by computing the tightness probability, mean, variance, second-order moment and sensitivity coefficients of the circuit arrival time, the sum and max operations of non-linear and non-Gaussian delay expressions are implemented. For the ISCAS89 benchmark circuits, as compared to Monte Carlo (MC) simulation, the average errors of 0.81%, -0.72%, 2.23% and -0.05%, in the mean, variance, 5% and 95% quantile points of the circuit delay are obtained respectively for the proposed method. The runtime of the proposed method is about 0.21% of the value of Monte Carlo simulation. The experimental results prove that the high accuracy of the SSTA is reliable.

History

Journal

Journal of Electronics and Information Technology

Volume

37

Pagination

468-476

Location

Beijing, China

ISSN

1009-5896

Language

chi

Issue

2

Publisher

Zhongguo ke xue yuan dian zi xue yan jiu suo

Usage metrics

    Research Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC