Transient Noise Failures in SRAM Cells: Dynamic Noise Margin Metric

Abstract

Current nanometric IC processes need to assess the robustness of memories under any possible source of disturbance: process and mismatch variations, bulk noises, supply rings variations, temperature changes, aging and environmental aggressions such as RF or on-chip couplings. In the case of SRAM cells, the static immunity to such perturbations is well characterized by means of the Static Noise Margin (SNM) defined as the maximum applicable series voltage at the inputs which causes no change in the data retention nodes. In addition, a significant number of disturbance sources present a transient behavior which has to be taken in consideration. In this paper, a metric to evaluate the cell robustness in the presence of transient voltage signals is proposed. Sufficiently high energy noise signals will compel the cell to flip to a failure state. On the other hand, sufficiently low energy noise signals will not be able to flip the cell and the state will be preserved. The Dynamic Noise Margin (DNM) metric is defined as the minimum energy of the voltage pulses able to flip the cell. A case example of transient voltage noise pulses on a 6T SRAM cell using 45nm technology has been studied. Simulation results show the use of the proposed metric as an indicator of cell robustness in the presence of transient voltage noise.

Dynamic voltage scaling for SEU-tolerance in low-power memories

“…Re cently, many previous works proposed different analysis meth ods [6], [20], [21], [23] the tolerability of memory cell to the external noise and energy particle such as glitches, alpha and neutron particles causing SEDs that are not instantaneous.…”

SEU-Aware Low-Power Memories Using a Multiple Supply Voltage Array Architecture

“…This means that DNM can more accurately quantify the tolerance of a memory cell to realistic external noise since SEUs from alpha and neutron particles have both temporal and voltage level components. Previous researchers have proposed many different analysis methods to compute DNM [8,22,23,25].…”