Efficient and Accurate Statistical Timing Analysis for Non-Linear Non-Gaussian Variability With Incremental Attributes

Title of thesis: EFFICIENT AND ACCURATE STATISTICAL TIMING ANALYSIS FOR NON-LINEAR NON-GAUSSIAN VARIABILITY WITH INCREMENTAL ATTRIBUTES Ashish Dobhal, Master of Science, 2006 Thesis directed by: Assistant Professor Ankur Srivastava Department of Electrical and Computer Engineering For four decades, the semiconductor industry has distinguished itself by the rapid pace of improvement in its products. The principal categories of improvement trends are integration level, Cost, speed, power, compactness and functionality. Most of these trends have resulted principally from the industry's ability to exponentially decrease the minimum feature size used to fabricate integrated circuits. Of course, the most frequently cited trend is in integration level, which is usually expressed as Moore's Law (that is, the number of components per chip doubles every 24 months). With the aggressive scaling of the recent technologies, process variability is growing. Dealing with variability has beco...

• Type: Conference
• Year: 2007
• Where: VLSID
• Authors: Ashish Dobhal, Vishal Khandelwal, Ankur Srivastava
• Keywords: Computer Architecture, NON-LINEAR NON-GAUSSIAN VARIABILITY, Process Variability, Transistor Channel, VLSID 2007