Statistical Static Timing Analysis of VLSI as the Statistics of Correlated Extremes
The work
| Authors | Dmytro Mishagli; Eugene Koskin; Elena Blokhina |
|---|---|
| Editors | |
| Type | misc |
| Year | 2024 |
| Citekey | mishagli2024statistical |
Identifiers
| arXiv | 2401.03559 from its landing_page_url |
|---|
Access
| Landing page | https://arxiv.org/abs/2401.03559 |
|---|
Related
| Distinct from | abbasi2013formal |
|---|---|
| Distinct from | abuhaeyeh2026formally |
| Distinct from | parrot2023design |
From bibtex.
Abstract
In this study, a path-based Statistical Static Timing Analysis (SSTA) is formulated as a problem within the statistics of correlated extremes. For extreme value statistics with correlations, a novel approach to studying such systems, when the correlations are small, is developed. The approach considers a system from the first principals, starting from the multivariable characteristic function. Analytical solutions to the problem of weakly correlated extremes are obtained in the form of corrections to the Gumbel distribution. These solutions are compared with Monte Carlo simulations. The applicability limits of the proposed solutions are studied. An algorithm to estimate the covariance matrix of a timing graph is proposed.
A copy is held
pdf, 1.8 MB. Not published — it may be under copyright. The facts and links here are.
How it got here
| How it got here | agent via bibtex |
|---|---|
| Added | 2026-09-18 08:56 UTC |
| Approved by | a person 2026-09-18 10:03 UTC |
Cite it as
@misc{mishagli2024statistical,
title = {Statistical Static Timing Analysis of VLSI as the Statistics of Correlated Extremes},
author = {Dmytro Mishagli and Eugene Koskin and Elena Blokhina},
year = {2024},
}
This record lives at https://refs.drheap.org/mishagli2024statistical/ and will keep doing so.