The impact of intrinsic device fluctuations on CMOS SRAM cell stability

By A. Bhavnagarwala, Xinghai Tang, James D. Meindl. IEEE J. Solid State Circuits, 2001

737 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ba73897be49836ac21bacab1918046786bb95ce3

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In Electrical and Electronic Engineering

Citations in the corpus

Review and Reexamination of Reliability Effects Related to NBTI-Induced Statistical Variations (2007, background): “Both yield [18]–[21] and reliability [17], [22], [23] concerns”
A read-static-noise-margin-free SRAM cell for low-VDD and high-speed applications (2006, background): “Unlike the situation with the threshold voltage (Vth) of CMOS logic transistors, however, since the read-static-noise-margin (SNM) deteriorates with decreases in supply voltage (VDD) and increases with the transistor mismatch accompanied by geometry scaling [1]–[3], there are severe limits to the de”
Impact of Line-Edge Roughness on FinFET Matching Performance (2007, background): “In the majority of the reported work, SNM refers to the read operation of six-transistor (6-T) SRAM bit-cells [21], [23],”
Read Stability and Write-Ability Analysis of SRAM Cells for Nanometer Technologies (2006, methodology): “Several analytical models of the static noise margin (SNM) have been developed to optimize the cell design, to predict the effect of parameter changes on the SNM [2] and to assess the impact of intrinsic parameter variations on the cell stability [3].”
Process Variation Tolerant 3T1D-Based Cache Architectures (2007, background): “Also, there are serious concerns about the continued scalability of SRAM-based memories [3].”
Characterization of a Novel Nine-Transistor SRAM Cell (2008, methodology): “The static voltage transfer characteristics of the 6T and 9T SRAM cells during a read operation are shown in Fig. 3. The read SNM is the side length of the maximum nested square between voltage transfer characteristics of the two data storage nodes during a read access, as shown in Fig. 3 [ 5 ].”
A 160 mV Robust Schmitt Trigger Based Subthreshold SRAM (2007, background): “Process variations limit the circuit operation in the subthreshold region, particularly the memories [2], [ 3 ].”
A 256 kb 65 nm 8T Subthreshold SRAM Employing Sense-Amplifier Redundancy (2008, background): “2(a), fails to operate in subbecause of reduced signal levels and increased variation [8].”
Mixture importance sampling and its application to the analysis of SRAM designs in the presence of rare failure events (2006, background): “1 Process variability impact on SRAM cells The threshold voltage fluctuations of the SRAM cell transistors are impacted by the random dopant fluctuations and may be considered as six independent Gaussian random variables, δvti, i=1 to 6 [13].”
FPGA Intrinsic PUFs and Their Use for IP Protection (2007, background): “In [7], the authors show that microscopic variations in the dopant atoms in the channel region of the MOSFET induce diﬀerences in the threshold voltage V t of the transistors of an SRAM cell.”
Use ECP, not ECC, for hard failures in resistive memories (2010, background): “As resistive memories are scaled to smaller dimensions, lifetime variability may become more pronounced, making it crucial for error-correcting schemes to handle numerous early cell failures gracefully.”
An 8T-SRAM for Variability Tolerance and Low-Voltage Operation in High-Performance Caches (2008, background): “AS VARIABILITY concerns mount in future CMOS technologies, SRAM cell stability, which depends on delicately balanced transistor characteristics, becomes a significant concern [1].”
Modeling of failure probability and statistical design of SRAM array for yield enhancement in nanoscaled CMOS (2005, methodology): “This assumption is valid if we are considering the V t variation due to RDF [1]–[3].”
Static noise margin variation for sub-threshold SRAM in 65-nm CMOS (2006, methodology): “Previous work has shown that above-threshold SNM is nearly linear with , and modeling its slope as constant allows an approximation of the joint PDF for SNM [9].”