Fast Monte-Carlo analysis method of ring oscillators with neural networks

Tae Hoon Choi; Hanwool Jeong; Seong Ook Jung

doi:10.23919/ELINFOCOM.2018.8330633

Fast Monte-Carlo analysis method of ring oscillators with neural networks

Tae Hoon Choi, Hanwool Jeong, Seong Ook Jung

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Because of the slow speed of SPICE Monte-Carlo (MC) simulation, the limited number of MC samples causes inaccuracy for statistical analysis of ring oscillators. In this paper, we propose the MC simulation method of ring oscillators with artificial neural networks, which shows 5 order faster than SPICE. It is shown that the figure of merits of the ring oscillator can be accurately estimated through simple neural networks training with random samples of SPICE data.

Original language	English
Title of host publication	International Conference on Electronics, Information and Communication, ICEIC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-4
Number of pages	4
ISBN (Electronic)	9781538647547
DOIs	https://doi.org/10.23919/ELINFOCOM.2018.8330633
Publication status	Published - 2018 Apr 2
Event	17th International Conference on Electronics, Information and Communication, ICEIC 2018 - Honolulu, United States Duration: 2018 Jan 24 → 2018 Jan 27

Publication series

Name	International Conference on Electronics, Information and Communication, ICEIC 2018
Volume	2018-January

Other

Other	17th International Conference on Electronics, Information and Communication, ICEIC 2018
Country	United States
City	Honolulu
Period	18/1/24 → 18/1/27

All Science Journal Classification (ASJC) codes

Information Systems
Computer Networks and Communications
Computer Science Applications
Signal Processing
Electrical and Electronic Engineering

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Choi, T. H., Jeong, H., & Jung, S. O. (2018). Fast Monte-Carlo analysis method of ring oscillators with neural networks. In International Conference on Electronics, Information and Communication, ICEIC 2018 (pp. 1-4). (International Conference on Electronics, Information and Communication, ICEIC 2018; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ELINFOCOM.2018.8330633

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abstract = "Because of the slow speed of SPICE Monte-Carlo (MC) simulation, the limited number of MC samples causes inaccuracy for statistical analysis of ring oscillators. In this paper, we propose the MC simulation method of ring oscillators with artificial neural networks, which shows 5 order faster than SPICE. It is shown that the figure of merits of the ring oscillator can be accurately estimated through simple neural networks training with random samples of SPICE data.",

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Choi, TH, Jeong, H & Jung, SO 2018, Fast Monte-Carlo analysis method of ring oscillators with neural networks. in International Conference on Electronics, Information and Communication, ICEIC 2018. International Conference on Electronics, Information and Communication, ICEIC 2018, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 17th International Conference on Electronics, Information and Communication, ICEIC 2018, Honolulu, United States, 18/1/24. https://doi.org/10.23919/ELINFOCOM.2018.8330633

Fast Monte-Carlo analysis method of ring oscillators with neural networks. / Choi, Tae Hoon; Jeong, Hanwool; Jung, Seong Ook.

International Conference on Electronics, Information and Communication, ICEIC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4 (International Conference on Electronics, Information and Communication, ICEIC 2018; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Because of the slow speed of SPICE Monte-Carlo (MC) simulation, the limited number of MC samples causes inaccuracy for statistical analysis of ring oscillators. In this paper, we propose the MC simulation method of ring oscillators with artificial neural networks, which shows 5 order faster than SPICE. It is shown that the figure of merits of the ring oscillator can be accurately estimated through simple neural networks training with random samples of SPICE data.

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Choi TH, Jeong H, Jung SO. Fast Monte-Carlo analysis method of ring oscillators with neural networks. In International Conference on Electronics, Information and Communication, ICEIC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-4. (International Conference on Electronics, Information and Communication, ICEIC 2018). https://doi.org/10.23919/ELINFOCOM.2018.8330633