Elena Ioana Vatajelu

Elena Ioana Vatajelu

Director:

Dr. Joan Figueras Pàmies

Reading day:

Friday, 30th September 2011 

Abstract: 

The PhD thesis is focused on the analysis of the robustness of static random access memory (SRAM) cell in nanometric technologies. Starting with an analysis on the state of the art, the subject is introduced and its importance is revealed. The SRAM robustness is defined as the maximum level of noise that can be tolerated by the cell when used in a system while still maintaining the correct operation. The second chapter of the dissertation is focused on the analysis of the SRAM cell robustness under DC disturbances. First, an overview of the existing static robustness metrics is presented with special emphasis on the Static Noise Margin (SNM) metric, which is widely used today. In this dissertation two new strategies for static noise margin evaluation have been proposed and their accuracies demonstrated by comparison against other existing metrics. The sensitivity of the SRAM cell static robustness, i.e. Static Noise Margin, to the process, voltage, temperature and environmental fluctuations is analyzed.

The third chaper is dedicated to dynamic robustness analysis of the SRAM cell. A brief description of the dynamic behavior of the SRAM cell based on the methods of nonlinear system theory is presented. Then, the existing dynamic robustness metrics are summarized with emphasis on the SRAM cell robustness to single event upsets (SEU). Recent Dynamic Noise Margin metrics have also been studied. In this dissertation two new strategies for dynamic robustness evaluation have been proposed. The first strategy evaluates the functionality margins of the SRAM cell during data retention, read/write operation modes by means of phase-plane analysis. The second strategy proposes new dynamic noise metric for SRAM cell robustness analysis assuming internal dynamic voltage noise sources disturbing cell.  Simulation results show the use of the proposed metric as an indicator of cell robustness in the presence of transient voltage noise. 
In the fourth chapter the functionality of the SRAM cell is statistically analyzed. A new method (Satisfiability Boundary - Statistical Integration (SB-SI)) for statistical analysis of SRAM cell behaviour under process variability is described.  The efficency of this method is demonstrated by comparison against accelerated Monte Carlo simulations.  Using the previously described SB-SI method, the robustness on the SRAM cell is evaluated in data retention mode, under diffrent supply voltages and environmental conditions. Then the functionality of the cell is evaluated assuming certain circuit performance. in the fifth chapter methos to mitigate the effect of process variability on the SRAM cell functionality are introduced, and the satisfiability 
boundary concept is used to compare this methods. 
The main original contributions of this thesis are: 1) new metrics for static robustness analysis, 2) new metrics for dynamic robustness analysis, 3) new method of statistical analysis, 4) new method for qualitative estimation of assist techniques efficiency.