TY - GEN
T1 - Model Auto Extraction for Gate-All-Around Silicon Nanowire MOSFETs Using A Decomposition-Based Many-Objective Evolutionary Algorithm
AU - Yang, Ya Shu
AU - Li, Yiming
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The merits of decomposition-based many-objective evolutionary algorithms are known in solving many-objective optimization problem (MaOP). Device model extraction is one of MaOPs, in this work, we first time apply a decomposition-based many-objective evolutionary algorithm with two types of adjustments for the direction vectors (MaOEA/D-2ADV) to model auto extraction of MOSFETs. This approach can fast extract 65 nm devices and sub-5-nm gate-all-around (GAA) silicon (Si) nanowire (NW) MOSFETs. The results of this study indicate that the automatic extraction by using the MaOEA/D-2ADV converges accurately, rapidly, and stably. It can not only jump out local traps but optimize final results efficiently for various devices. Compared with measured results, the accuracy of extracted ID-VG, ID-VD, gm, and gds are less than 1% within a few minutes.
AB - The merits of decomposition-based many-objective evolutionary algorithms are known in solving many-objective optimization problem (MaOP). Device model extraction is one of MaOPs, in this work, we first time apply a decomposition-based many-objective evolutionary algorithm with two types of adjustments for the direction vectors (MaOEA/D-2ADV) to model auto extraction of MOSFETs. This approach can fast extract 65 nm devices and sub-5-nm gate-all-around (GAA) silicon (Si) nanowire (NW) MOSFETs. The results of this study indicate that the automatic extraction by using the MaOEA/D-2ADV converges accurately, rapidly, and stably. It can not only jump out local traps but optimize final results efficiently for various devices. Compared with measured results, the accuracy of extracted ID-VG, ID-VD, gm, and gds are less than 1% within a few minutes.
KW - compact model parameter extraction
KW - conventional planar devices
KW - evolutionary algorithm
KW - MaOEA/D-2ADV
KW - Model auto extraction
KW - MOSFETs
KW - nanosheet
KW - nanowire
UR - http://www.scopus.com/inward/record.url?scp=85133801551&partnerID=8YFLogxK
U2 - 10.1109/ISQED54688.2022.9806274
DO - 10.1109/ISQED54688.2022.9806274
M3 - Conference contribution
AN - SCOPUS:85133801551
T3 - Proceedings - International Symposium on Quality Electronic Design, ISQED
BT - Proceedings of the 23rd International Symposium on Quality Electronic Design, ISQED 2022
PB - IEEE Computer Society
T2 - 23rd International Symposium on Quality Electronic Design, ISQED 2022
Y2 - 6 April 2022 through 7 April 2022
ER -