Name
Title | ||
|---|---|---|
Statistically Validating the Impact of Process Variations on Analog and Mixed Signal Designs |
Abstract | ||
|---|---|---|
Process variation presents a practical challenge on the performance of analog and mixed signal (AMS) circuits. This paper proposes a Monte Carlo-Jackknife (MC-JK) technique, a variant of Monte Carlo method, to verify process variation affecting the performance and functionality of AMS designs. We use a behavioral model to which we encompass device variation due to $65nm$ technology process. Next, we conduct hypothesis testing based on the MC-JK technique combined with Latin hypercube sampling in a statistical run-time verification environment. Experimental results demonstrate the robustness of our approach in verifying AMS circuits. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2742060.2742122 | ACM Great Lakes Symposium on VLSI |
Field | DocType | Citations |
Monte Carlo method,And mixed signal,Computer science,Behavioral modeling,Robustness (computer science),Electronic engineering,Process variation,Electronic circuit,Statistical hypothesis testing,Latin hypercube sampling | Conference | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ibtissem Seghaier | 1 | 4 | 2.90 |
| Mohamed H. Zaki | 2 | 109 | 15.49 |
| Sofiène Tahar | 3 | 915 | 110.41 |