Monte Carlo simulation of nanoelectronic devices

Gamiz, F.; Godoy, A.; Donetti, L.; Sampedro, Carlos; Roldán, J.B.; Ruiz, Francisco G.; Tienda, I.; Rodríguez, Noel; Jiménez-Molinos, F.

doi:10.1007/s10825-009-0295-x

Cited by 5 publications

(2 citation statements)

References 63 publications

(77 reference statements)

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“…In this respect, in devices such as MOSFETs [ 64 , 65 ] (even multigate FETs [ 66 ]) or diodes [ 67 , 68 ], once a reasonable grid is established, the main differential equations are discretized and, in general, but for very scarce cases, convergence is searched for to obtain a solution. This is the main scheme to follow in drift-diffusion, hydrodynamic and Monte Carlo simulation approaches [ 69 ]. By contrast, in RRAMs the modeling paradigm is different due to the particularities of their operation.…”

Section: Introductionmentioning

confidence: 99%

On the Thermal Models for Resistive Random Access Memory Circuit Simulation

et al. 2021

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Resistive Random Access Memories (RRAMs) are based on resistive switching (RS) operation and exhibit a set of technological features that make them ideal candidates for applications related to non-volatile memories, neuromorphic computing and hardware cryptography. For the full industrial development of these devices different simulation tools and compact models are needed in order to allow computer-aided design, both at the device and circuit levels. Most of the different RRAM models presented so far in the literature deal with temperature effects since the physical mechanisms behind RS are thermally activated; therefore, an exhaustive description of these effects is essential. As far as we know, no revision papers on thermal models have been published yet; and that is why we deal with this issue here. Using the heat equation as the starting point, we describe the details of its numerical solution for a conventional RRAM structure and, later on, present models of different complexity to integrate thermal effects in complete compact models that account for the kinetics of the chemical reactions behind resistive switching and the current calculation. In particular, we have accounted for different conductive filament geometries, operation regimes, filament lateral heat losses, the use of several temperatures to characterize each conductive filament, among other issues. A 3D numerical solution of the heat equation within a complete RRAM simulator was also taken into account. A general memristor model is also formulated accounting for temperature as one of the state variables to describe electron device operation. In addition, to widen the view from different perspectives, we deal with a thermal model contextualized within the quantum point contact formalism. In this manner, the temperature can be accounted for the description of quantum effects in the RRAM charge transport mechanisms. Finally, the thermometry of conducting filaments and the corresponding models considering different dielectric materials are tackled in depth.

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Section: Introductionmentioning

confidence: 99%

On the Thermal Models for Resistive Random Access Memory Circuit Simulation

et al. 2021

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“…Section 2 introduces the MSB-EMC method (Saint-Martin et al, 2006a). A description of the MSB-EMC simulator (Gámiz et al, 2009) and the analysis of its computational cost is presented in Section 3. Section 4 explains the parallelisation technique of the MSB-EMC simulator and shows speed-up results.…”

Section: Introductionmentioning

confidence: 99%

Optimisation and parallelisation of a 2D MOSFET multi-subband ensemble Monte Carlo simulator

Valin

Sampedro

Seoane

et al. 2012

The International Journal of High Performance Computing Applica

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Multi-subband ensemble Monte Carlo simulators (MSB-EMC) are essential in semiconductor device modelling in order to study confinement effects when devices are scaled to gate lengths and silicon thicknesses approaching nanometre dimensions. To consider these effects it is necessary to solve the Schrödinger equation in the confinement direction, which has a high computational cost. In this paper we propose the parallelisation and optimisation of a 2D MSB-EMC simulator. The Open Multi-Processing (OpenMP) application program interface (API) is employed for the parallelisation and the simulations are performed using a multi-core machine. Numerical results show a speed-up of 7.40 when eight cores are used with a parallel efficiency higher than 90%.

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