Alpha-particle-induced SER of embedded SRAMs affected by variations in process parameters and by the use of process options

Heijmen, T.; Kruseman, B.

doi:10.1016/j.sse.2005.10.025

Cited by 26 publications

(8 citation statements)

References 8 publications

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“…Effects of variability on error rate in the literature has mostly been addressed through critical charge modeling in different process corners or analytical modeling [4][5][6][7][8][9][10] or through critical charge spread modeling with monte-carlo drawing of transistor parameters [11][12][13][14]. Few alpha experimental results are available in the literature and no neutron data has ever been reported.…”

Section: Introductionmentioning

confidence: 99%

Experimental characterization of process corners effect on SRAM alpha and neutron Soft Error Rates

Gasiot

Glorieux

Uznanski

et al. 2012

2012 IEEE International Reliability Physics Symposium (IRPS)

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This paper shows alpha and neutron experimental Soft Error Rate characterization of a SRAM test vehicle processed with different process corners in order to emulate the variability encountered in volume production. It allows assessing large variability effects with few samples that are compatible with accelerated SER testing. This allows investigating the effect of variability in mass-production on soft error rate of decananometric technologies. Keywords-Process corner; Soft Error Rate; alpha and neutron experiments;manufacturing process variability; volume productionI.

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Section: Introductionmentioning

confidence: 99%

Experimental characterization of process corners effect on SRAM alpha and neutron Soft Error Rates

Gasiot

Glorieux

Uznanski

et al. 2012

2012 IEEE International Reliability Physics Symposium (IRPS)

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“…Experimental results of Heijmen and Kruseman of Philips demonstrated that if two chip designs contain embedded SRAM instances of the same type, then the SER can be different with as much as 40% [20]. Additionally, significant batch-to-batch and sample-to-sample variations in SER have been observed.…”

Section: Scaling Of Sram Sermentioning

confidence: 99%

Soft Errors from Space to Ground: Historical Overview, Empirical Evidence, and Future Trends

Heijmen

2010

Frontiers in Electronic Testing

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Soft errors induced by radiation, which started as a rather exotic failure mechanism causing anomalies in satellite equipment, have become one of the most challenging issues that impact the reliability of modern electronic systems, also in ground-level applications. Many efforts have been spent in the last decades to measure, model, and mitigate radiation effects, applying numerous techniques approaching the problem at various abstraction levels. This chapter presents a historical overview of the soft-error subject and treats several "disaster stories" from the past. Furthermore, scaling trends are discussed for the most sensitive circuit types.

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“…Recently, researchers have attempted to calculate the critical charge nominal value as well as addressing the impact of process variations on the critical charge in memory elements such as SRAM cells and flip-flops. However, most of this research is conducted by using Monte Carlo analysis tools [1], [16]- [18], which are time consuming and provide little design insights. Moreover, these Monte Carlo analysis tools are not scalable with technology.…”

Section: Introductionmentioning

confidence: 99%

A Design-Oriented Soft Error Rate Variation Model Accounting for Both Die-to-Die and Within-Die Variations in Submicrometer CMOS SRAM Cells

Mostafa

Anis

Elmasry

2010

IEEE Trans. Circuits Syst. I

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Submicrometer static random access memory cells are more susceptible to particle strike soft errors and increased statistical process variations, in advanced nanometer CMOS technologies. In this paper, analytical models for the critical charge variations accounting for both die-to-die and within-die variations are proposed. The derived models are verified and compared to Monte Carlo simulations by using industrial 65-nm CMOS technology. This paper provides new design insights such as the impact of the coupling capacitor, one of the most common soft error mitigation techniques, on the critical charge variability, especially, at lower supply voltages. It demonstrates that two extreme values of this coupling capacitor exist. The first value results in maximum relative variations and the other results in minimum relative variations. Therefore, the circuit designers can utilize these results to design the coupling capacitor to limit the variations under power and performance constraints in early design cycles. The derived analytical models account for the impact of the supply voltage and different particle strike conditions. These results are particularly important for soft error tolerant and variation tolerant designs in submicrometer technologies, especially, for low power operations.Index Terms-Deep submicrometer, process variations, reliability, soft errors, static random access memory (SRAM).

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Alpha-particle-induced SER of embedded SRAMs affected by variations in process parameters and by the use of process options

Cited by 26 publications

References 8 publications

Experimental characterization of process corners effect on SRAM alpha and neutron Soft Error Rates

Experimental characterization of process corners effect on SRAM alpha and neutron Soft Error Rates

Soft Errors from Space to Ground: Historical Overview, Empirical Evidence, and Future Trends

A Design-Oriented Soft Error Rate Variation Model Accounting for Both Die-to-Die and Within-Die Variations in Submicrometer CMOS SRAM Cells

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