Showing posts with label Circuit Simulator. Show all posts
Showing posts with label Circuit Simulator. Show all posts

Apr 30, 2021

[paper] Dynamic Simulation of a-IGZO TFT Circuits Using AFCM

Y. Hernández-Barrios1, J. N. Gaspar-Angeles1, M. Estrada1, B. Íñiguez2, And A. Cerdeira1
Dynamic Simulation of a-IGZO TFT Circuits Using the Analytical Full Capacitance Model (AFCM)
IEEE Journal of the Electron Devices Society, vol. 9, pp. 464-468, 2021, 
doi: 10.1109/JEDS.2020.3045347

1 SEES, Departamento de Ingeniería Eléctrica, CINVESTAV-IPN, Mexico City 07360, Mexico
2 Departament d’Enginyeria Electrònica, Elèctrica i Automàtica, URV, Tarragona 43007, Spain

Abstract: The Analytical Full Capacitance Model (AFCM) for amorphous oxide semiconductors thin film transistors (AOSTFTs) is first validated, using a 19-stages Ring Oscillator (RO) fabricated and measured. The model was described in Verilog-A language to use it in a circuit simulator in this case SmartSpice from Silvaco. The model includes the extrinsic effects related to specific overlap capacitances present in bottom-gate AOSTFT structures. The dynamic behavior of the simulated circuit, when the TFT internal capacitances are increased or decreased and for different supply voltages of 10, 15 and 20 V, is compared with measured characteristics, obtaining a very good agreement. Afterwards, the AFCM is used to simulate the dynamic behavior of a pixel control circuit for a light emitting diode active matrix display (AMOLED), using an AOSTFT.

FIG: Fabricated and measured 19-stages Ring Oscillator (RO)
of amorphous oxide semiconductors (AOS) thin film transistors (TFTs) 

Aknowlwgement: This work was supported in part by the Consejo Nacional de Ciencia y Tecnología (CONACYT) under Project 237213 and Project 236887; in part by the H2020 program of the European Union under Contract 645760 (DOMINO); in part by contract “Thin Oxide TFT SPICE Model” with Silvaco Inc., under Grant T12129S; and in part by ICREA Academia 2013 from ICREA Institute and the Spanish Ministry of Economy and Competitiveness under Project TEC2015-67883-R GREENSENSE.

 

Nov 30, 2020

[paper] SPICE-level Crossbar-array Circuit Simulator

Fan Zhang1 and Miao Hu2 
CCCS: Customized SPICE-level Crossbar-array Circuit Simulator
for In-Memory Computing
IEEE/ACM International Conference on Computer-Aided Design
(ICCAD ’20) November 2– 5, 2020, Virtual Event, USA. 
ACM, New York, NY, USA, 8 pages.
DOI: 10.1145/3400302.3415627
1Arizona State University Tempe, Arizona
2Binghamton University Binghamton, New York


ABSTRACT: Resistive crossbar arrays are known for their unique structure to implement analog in-memory vector-matrix-multiplications (VMM). However, general-purpose circuit simulators, such as HSPICE and HSIM, are too slow for large scale crossbar array simulations with consideration of circuit parasitics. Although there are some specific simulators designed for crossbar arrays, they mainly focus on area/power/delay estimation rather than accurate SPICE-level simulation, thus could not model its functionality on analog in-memory computing. In this paper, we firstly give a SPICE-level modeling of resistive crossbar array with consideration of circuit parasitics in MATLAB. We also propose efficient methods to further speedup simulations by model simplifications. Last but not least, ResNet-20 on CIFAR-10 is applied to demonstrate the work. With the proposed model simplification methods, simulation speed can be improved by ~31X with tolerable errors, and more than 5X speedup is achieved on ResNet-20 while the accuracy drop is 6%.

Figure: Implement the ResNet on the crossbar with sub-block optimization. 

RELATED WORK: Other than general-purpose circuit simulators, specific simulation platforms have been proposed for crossbar-based application analysis; examples include: 
[MNSIM] L. Xia, B. Li, T. Tang, P. Gu, X. Yin, W. Huangfu, P. Chen, S. Yu, Y. Cao, Y. Wang, Y. Xie, and H. Yang. MNSIM: Simulation platform for memristor-based neuromorphic computing system. In 2016 Design, Automation Test in Europe Conference Exhibition (DATE). 469–474.
[NeuroSim] P. Chen, X. Peng, and S. Yu. 2018. NeuroSim: A Circuit-Level Macro Model for Benchmarking Neuro-Inspired Architectures in Online Learning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 37, 12 (Dec 2018), 3067–3080.