An Accurate Analytical SNM Modeling Technique for SRAMs Based on Butterworth Filter Function

V
VLSID
2007
20th International Conference on VLSI Design held jointly with 6th International Conference on Embedded Systems (VLSID'07)
Abstract - An Accurate Analytical SNM Modeling Technique for SRAMs Based on Butterworth Filter Function

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	Similar Articles Articles by Qikai Chen Articles by Arjun Guha Articles by Kaushik Roy

20th International Conference on VLSI Design held jointly with 6th International Conference on Embedded Systems (VLSID'07)

Bangalore, India

January 06-January 10

ISBN: 0-7695-2762-0

	ASCII Text	x
	Qikai Chen, Arjun Guha, Kaushik Roy, "An Accurate Analytical SNM Modeling Technique for SRAMs Based on Butterworth Filter Function," VLSI Design, International Conference on, pp. 615-620, 20th International Conference on VLSI Design held jointly with 6th International Conference on Embedded Systems (VLSID'07), 2007.

	BibTex	x
	@article{ 10.1109/VLSID.2007.29, author = {Qikai Chen and Arjun Guha and Kaushik Roy}, title = {An Accurate Analytical SNM Modeling Technique for SRAMs Based on Butterworth Filter Function}, journal ={VLSI Design, International Conference on}, volume = {0}, year = {2007}, issn = {1063-9667}, pages = {615-620}, doi = {http://doi.ieeecomputersociety.org/10.1109/VLSID.2007.29}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - VLSI Design, International Conference on TI - An Accurate Analytical SNM Modeling Technique for SRAMs Based on Butterworth Filter Function SN - 1063-9667 SP615 EP620 A1 - Qikai Chen, A1 - Arjun Guha, A1 - Kaushik Roy, PY - 2007 KW - null VL - 0 JA - VLSI Design, International Conference on ER -

Qikai Chen, Purdue University, West Lafayette, IN-47907, USA

Arjun Guha, Purdue University, West Lafayette, IN-47907, USA

Kaushik Roy, Purdue University, West Lafayette, IN-47907, USA

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/VLSID.2007.29

With the impact of process variations becoming increasingly pronounced in the sub-90nm regime, the stability of SRAM cells is considerably degraded. Static noise margin (SNM) is popularly used for SRAM stability measurement. Therefore, efficient techniques to estimate SNM are required for robust SRAM design. In this paper, we have proposed an analytical SRAM SNM modeling technique based on Butterworth function and coordinate transformation. The accuracy of the SNM model has been verified by changing of the SRAM design parameters, such as the relative sizes of the 6 transistors and device doping. With a wide range of design parameter change, less than 8% of estimation error is achieved by the proposed SNM model. The proposed SNM model has been applied to analyze the impact of process variations on SRAM SNM distribution. Also, the distribution of read SNM has been estimated for a range of design parameter variations.

Citation:

Qikai Chen, Arjun Guha, Kaushik Roy, "An Accurate Analytical SNM Modeling Technique for SRAMs Based on Butterworth Filter Function," vlsid, pp.615-620, 20th International Conference on VLSI Design held jointly with 6th International Conference on Embedded Systems (VLSID'07), 2007

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