Combining GEANT4 and TIARA for Neutron Soft Error-Rate Prediction of 65 nm Flip-Flops

Uznanski, Slawosz; Gasiot, Gilles; Roché, Philippe; Semikh, S. S.; Autran, J.L.

doi:10.1109/tns.2011.2170853

Cited by 15 publications

(4 citation statements)

References 18 publications

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“…Data are transmitted between the master and slave latch using a pass gate. In this study, we include in the modeled structure all drains of all the transistors present in the flip-flop, unlike to our previous simulation works that only considered the bistable transistors [6,28]. In this way, all of the possible upset mechanisms can be taken into account.…”

Section: Flip-flop Circuitmentioning

confidence: 99%

Charge Collection Physical Modeling for Soft Error Rate Computational Simulation in Digital Circuits

Autran¹,

Munteanu²,

Moindjie³

et al. 2016

Modeling and Simulation in Engineering Sciences

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This chapter describes a new computational approach for accurately modeling radiation-induced single-event transient current and charge collection at circuit level. This approach, called random-walk drift-diffusion (RWDD), is a fast Monte Carlo particle method based on a random-walk process that takes into account both diffusion and drift of carriers in a non-constant electric field both in space and time. After introducing the physical insights of the RWDD model, the chapter details the practical implementation of the method using an object-oriented programming language and its parallelization on graphical processing units. Besides, the capability of the approach to treat multiple node charge collection is presented. The chapter also details the coupling of the model either with an internal routine or with SPICE for circuit solving. Finally, the proposed approach is illustrated at device and circuit level, considering four different test vehicles in 65 nm technologies: a stand-alone transistor, a CMOS inverter, a SRAM cell and a flip-flop circuit. RWDD results are compared with data obtained from a full three-dimensional (3D) numerical approach (TCAD simulations) at transistor level. The importance of the circuit feedback on the charge-collection process is also demonstrated for devices connected to other circuit nodes.

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Section: Flip-flop Circuitmentioning

confidence: 99%

Charge Collection Physical Modeling for Soft Error Rate Computational Simulation in Digital Circuits

Autran¹,

Munteanu²,

Moindjie³

et al. 2016

Modeling and Simulation in Engineering Sciences

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“…Such "errors" are now unacceptable in today scaled technologies, so several research groups have developed Monte-Carlo methods to include the generation and transport of low energy -rays. Concerning Single-Event Effects, this has been made for several primary particles [28], [29], [34]- [38] like protons, electrons, or heavy ions based on dedicated tools and codes [39]- [41]. Based on those tools, an example of the distribution of radial energy deposition calculated for a 5.5 MeV/am in a slab of silicon is presented in Fig.…”

Section: A Origin Of Set: Energy Transfer From a Particle To A Materialsmentioning

confidence: 99%

Modeling Single Event Transients in Advanced Devices and ICs

Artola

Gaillardin

Hubert

et al. 2015

IEEE Trans. Nucl. Sci.

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The ability for Single Event Transients (SETs) to induce soft errors in Integrated Circuits (ICs) was predicted for the first time by Wallmark and Marcus in the early 60's [1] and was confirmed to be a serious issue thirty years later. In the 90's microelectronic technologies reached the "deep submicron" era, allowing high density ICs working at frequencies faster than hundreds of MHz. This new paradigm changed the status of SETs to become a major source of reliability losses. Huge efforts have thus been made to characterize SETs in microelectronics, either using experiments or by simulation, in order to reveal key factors leading to SET occurrence, propagation and capture in modern ICs. In this context, modeling and simulation are of primary importance to get accurate SET predictions. This paper focuses on modeling SETs in innovative electronic devices which involves modeling steps at different scales, from ionizing particle to circuit response. After a brief review of the state-of-the art of modeling at each scale, this paper will discuss current capabilities and intrinsic limitations of SET modeling, the incoming challenges in advanced devices and ICs, and finally the methodologies to improve SET simulation and prediction for future technologies.

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“…The initial version of TIARA [26][27] was a standalone C++ native code dynamically linked with IC CAD flow through the coupling with a SPICE solver. The code has been developed such that the addition of new radiation environments, physical models or new circuit architecture should be quite simple.…”

Section: The Tiara-g4 Monte Carlo Simulation Codementioning

confidence: 99%