Effects of Heavy Ion and Proton Irradiation on a SLC NAND Flash Memory

Luza, Lucas Matana; Besser, Alexandre; Gupta, Viyas; Javanainen, Arto; Mohammadzadeh, Ali; Dilillo, Luigi

doi:10.1109/dft.2019.8875475

Cited by 3 publications

(2 citation statements)

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“…More directly related to the activities of the authors, [27] explores methods for testing memory devices and the outcome results based on two SRAM (Static Random Access Memory) laid out on a 90 nm and 65 nm technology node size. The radiation-induced effects on an SLC (Single Level Cell) NAND Flash under heavy-ions and proton irradiation were evaluated in [28], [29]. The occurrence of SELs on an MRAM (Magnetoresistive Random Access Memory) is presented in [30].…”

Section: Radiation-induced Effects On Memoriesmentioning

confidence: 99%

Impact of Atmospheric and Space Radiation on Sensitive Electronic Devices

Luza

Wrobel

Entrena

et al. 2022

2022 IEEE European Test Symposium (ETS)

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Studying the radiation effects on electronic devices is essential for avionics and space systems. The shrinking technology nodes and increasing density of devices enhance the sensitivity of electronic systems to ionizing radiation. Due to their crucial role, memories and processors are the highest contributors to soft errors in systems, making them the best candidates for studying these effects. This work introduces the radiation environment in space and atmosphere and the main effects that the different types of ionizing particles that are present in these environments may produce on electronic devices. Furthermore, mainly focusing on Single-Event Effects (SEEs), it presents approaches and tools for modeling SEEs and their impact on memories and microprocessors. Additionally, experimental results targeting a Commercial-Off-The-Shelf self-refresh Dynamic RAM are presented. These experiments are based on radiation test campaigns in particle accelerators with neutrons and protons. Finally, an overview of issues and mitigation techniques for microprocessors is exposed.

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Section: Radiation-induced Effects On Memoriesmentioning

confidence: 99%

Impact of Atmospheric and Space Radiation on Sensitive Electronic Devices

Luza

Wrobel

Entrena

et al. 2022

2022 IEEE European Test Symposium (ETS)

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“…In [18], the authors review the techniques and results of several radiation test campaigns on two commercial SRAMs (90 nm and 65 nm) technology nodes. Moreover, the effects on a SLC (Single Level Cell) NAND Flash under heavy-ions and proton irradiation were evaluated in [19]. Also, in [20], several tests on a MRAM show that the memory is prone to suffering from SELs.…”

Section: B Fault Model Evaluationmentioning

confidence: 99%

A Model-Based Framework to Assess the Reliability of Safety-Critical Applications

Luza

Ruospo

Bosio

et al. 2021

2021 24th International Symposium on Design and Diagnostics of Electronic Circuits &Amp; Systems (DDECS)

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Solutions based on artificial intelligence and brain-inspired computations like Artificial Neural Networks (ANNs) are suited to deal with the growing computational complexity required by state-of-the-art electronic devices. Many applications that are being deployed using these computational models are considered safety-critical (e.g., self-driving cars), producing a pressing need to evaluate their reliability. Besides, state-of-the-art ANNs require significant memory resources to store their parameters (e.g., weights, activation values), which goes outside the possibility of many resourceconstrained embedded systems. In this light, Approximate Computing (AxC) has become a significant field of research to improve memory footprint, speed, and energy consumption in embedded and high-performance systems. The use of AxC can significantly reduce the cost of ANN implementations, but it may also reduce the inherent resiliency of this kind of application. On this scope, reliability assessments are carried out by performing fault injection test campaigns. The intent of the paper is to propose a framework that, relying on the results of radiation tests in Commercial-Off-The-Shelf (COTS) devices, is able to assess the reliability of a given application. To this end, a set of different radiation-induced errors in COTS memories is presented. Upon these, specific fault models are extracted to drive emulation-based fault injections.

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