scholarly journals Modeling of GIDL–Assisted Erase in 3–D NAND Flash Memory Arrays and Its Employment in NOR Flash–Based Spiking Neural Networks

Author(s):  
Gerardo Malavena

AbstractSince the very first introduction of three-dimensional (3–D) vertical-channel (VC) NAND Flash memory arrays, gate-induced drain leakage (GIDL) current has been suggested as a solution to increase the string channel potential to trigger the erase operation. Thanks to that erase scheme, the memory array can be built directly on the top of a $$n^+$$ n + plate, without requiring any p-doped region to contact the string channel and therefore allowing to simplify the manufacturing process and increase the array integration density. For those reasons, the understanding of the physical phenomena occurring in the string when GIDL is triggered is important for the proper design of the cell structure and of the voltage waveforms adopted during erase. Even though a detailed comprehension of the GIDL phenomenology can be achieved by means of technology computer-aided design (TCAD) simulations, they are usually time and resource consuming, especially when realistic string structures with many word-lines (WLs) are considered. In this chapter, an analysis of the GIDL-assisted erase in 3–D VC nand memory arrays is presented. First, the evolution of the string potential and GIDL current during erase is investigated by means of TCAD simulations; then, a compact model able to reproduce both the string dynamics and the threshold voltage transients with reduced computational effort is presented. The developed compact model is proven to be a valuable tool for the optimization of the array performance during erase assisted by GIDL. Then, the idea of taking advantage of GIDL for the erase operation is exported to the context of spiking neural networks (SNNs) based on NOR Flash memory arrays, which require operational schemes that allow single-cell selectivity during both cell program and cell erase. To overcome the block erase typical of nor Flash memory arrays based on Fowler-Nordheim tunneling, a new erase scheme that triggers GIDL in the NOR Flash cell and exploits hot-hole injection (HHI) at its drain side to accomplish the erase operation is presented. Using that scheme, spike-timing dependent plasticity (STDP) is implemented in a mainstream NOR Flash array and array learning is successfully demonstrated in a prototype SNN. The achieved results represent an important step for the development of large-scale neuromorphic systems based on mature and reliable memory technologies.

2011 ◽  
Vol 50 (10) ◽  
pp. 100204 ◽  
Author(s):  
Myounggon Kang ◽  
Wookghee Hahn ◽  
Il Han Park ◽  
Youngsun Song ◽  
Hocheol Lee ◽  
...  

2019 ◽  
Vol 7 ◽  
pp. 1085-1093 ◽  
Author(s):  
Sung-Tae Lee ◽  
Suhwan Lim ◽  
Nag Yong Choi ◽  
Jong-Ho Bae ◽  
Dongseok Kwon ◽  
...  

2020 ◽  
Vol 20 (7) ◽  
pp. 4138-4142
Author(s):  
Sung-Tae Lee ◽  
Suhwan Lim ◽  
Nagyong Choi ◽  
Jong-Ho Bae ◽  
Dongseok Kwon ◽  
...  

NAND flash memory which is mature technology has great advantage in high density and great storage capacity per chip because cells are connected in series between a bit-line and a source-line. Therefore, NAND flash cell can be used as a synaptic device which is very useful for a high-density synaptic array. In this paper, the effect of the word-line bias on the linearity of multi-level conductance steps of the NAND flash cell is investigated. A 3-layer perceptron network (784×200×10) is trained by a suitable weight update method for NAND flash memory using MNIST data set. The linearity of multi-level conductance steps is improved as the word line bias increases from Vth −0.5 to Vth +1 at a fixed bit-line bias of 0.2 V. As a result, the learning accuracy is improved as the word-line bias increases from Vth −0.5 to Vth+1.


2015 ◽  
Vol 36 (7) ◽  
pp. 678-680 ◽  
Author(s):  
Davide Resnati ◽  
Christian Monzio Compagnoni ◽  
Giovanni M. Paolucci ◽  
Carmine Miccoli ◽  
Alessandro S. Spinelli ◽  
...  

2011 ◽  
Vol 50 (10R) ◽  
pp. 100204 ◽  
Author(s):  
Myounggon Kang ◽  
Wookghee Hahn ◽  
Il Han Park ◽  
Youngsun Song ◽  
Hocheol Lee ◽  
...  

2006 ◽  
Vol 53 (4) ◽  
pp. 1813-1818 ◽  
Author(s):  
G. Cellere ◽  
A. Paccagnella ◽  
A. Visconti ◽  
M. Bonanomi ◽  
S. Beltrami

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