A Variability Source for Nanosheet GAA Transistors for sub-7nm Nodes

Vardhan, P. Harsha; Ganguly, Swaroop; Ganguly, Udayan

doi:10.1109/vlsi-tsa.2019.8804670

Cited by 1 publication

(2 citation statements)

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“…In addition, due to the nano-meter device scaling, atomic level random variations have become prominent [4][5][6][7][8][9][10][11]. In this paper, we assumed that the random variables that have such pdf are the values for the six threshold voltages (Vth) for the six MOSFET devices that make up the 1bit cell for the 6Tstatic random access memory (SRAM).…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we assumed that the random variables that have such pdf are the values for the six threshold voltages (Vth) for the six MOSFET devices that make up the 1bit cell for the 6Tstatic random access memory (SRAM). Those variations for the random variables are mainly caused by the atomic scaled ion-implantation dose fluctuation and gate-oxide electron trap/de-trap phenomena [4][5][6][7][8][9][10][11] and divided into the two random variations caused by (1) the Random Spatial Variation (RSV) and (2) the Random Temporal Variation (RTV). As a result, the tail length of the minimum operating voltage (VDDMIN) pdf distribution of the SRAM has become spatially and temporally longer [12] because both variations of the RSV and the RTV become larger.…”

Section: Introductionmentioning

confidence: 99%

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A Richardson-Lucy Algorithm Based Blind Deconvolution to Decouple the Two Unknown Spatial-Temporal SRAM Margin Variations

Yamauchi

Somha

2023

J. Phys.: Conf. Ser.

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A Richardson-Lucy algorithm (RLA) based blind deconvolution with a new filter design technique was successfully developed. This allowed decoupling and retrieving of the information of the two unknown factors at once for the Random Temporal Variation (RTV) and the Random Spatial Variation (RSV). The variations of SRAM operating voltage (VDDMIN) are caused by the two coupled factors of RTV and RSV. Thus, this decoupling technique is prerequisite for the margin analysis. The designs of the device characteristics and the screening test conditions based on the analysis results were briefly demonstrated. The proposed filter design technique for the RLA based blind deconvolution allowed to circumvent the ill-conditioning ringing phenomena. This gives to enjoy the advantage in convergence speed and simplicity of the RLA. The relative errors of the blind-deconvolution for the RSV and RTV distributions were reduced to less than 0.3% within only 300-iteration cycles compared with the conventional one.

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