Title
Architecture-Aware Analytical Yield Model for Read Access in Static Random Access Memory
Abstract
We prove analytically that the yield of static random access memory (SRAM) is intrinsically a function of its architecture owing to the correlation among cell failures. In addition, architecture-aware analytical yield models are proposed for read access. The yield results using the proposed models show that the most dominant factor determining yield is the variation in the voltage difference between bitlines due to the cell leakage current variation according to the SRAM architecture. The models also show the possibility that the most dominant factor determining the yield can change with the relative ratios among the amounts of changes in the correlation, recovery sample space, distributions of the sense amplifier enable time, voltage difference between bitlines, as well as sense amplifier offset voltage, memory capacity, and redundancy scheme. The proposed yield models show that combined row and column redundancy ensures the highest yield, whereas column redundancy is the most efficient.
Year
DOI
Venue
2015
10.1109/TVLSI.2014.2321897
IEEE Trans. VLSI Syst.
Keywords
Field
DocType
process variation,architecture,sense amplifier enable time,recovery sample space,bitlines,leakage currents,relative ratios,yield,column redundancy,sram chips,architecture-aware analytical yield models,row redundancy,static random access memory,correlation,redundancy,static random access memory (sram),redundancy scheme,voltage difference,memory capacity,cell leakage current variation,sram architecture,read access failure,read access,sense amplifier offset voltage,yield.,mathematical model
Sense amplifier,Input offset voltage,Leakage (electronics),Computer science,Voltage,Real-time computing,Electronic engineering,Static random-access memory,Redundancy (engineering),Process variation,Sample space
Journal
Volume
Issue
ISSN
23
4
1063-8210
Citations 
PageRank 
References 
0
0.34
16
Authors
5
Name
Order
Citations
PageRank
Heechai Kang1152.06
Jisu Kim221128.11
Hanwool Jeong3428.47
Younghwi Yang4195.15
Seong-ook Jung533253.74