Distinct ρ-Based DGMOSFET Analysis for Ternary Content Addressable Memory at Sub-nm VLSI Technology

International Journal of Electrical and Electronics Engineering
© 2023 by SSRG - IJEEE Journal
Volume 10 Issue 12
Year of Publication : 2023
Authors : Hameed Pasha Mohammad, Meghana Kulkarni, Sandeep Kyatanavar, H.C. Hadimani
pdf
How to Cite?

Hameed Pasha Mohammad, Meghana Kulkarni, Sandeep Kyatanavar, H.C. Hadimani, "Distinct ρ-Based DGMOSFET Analysis for Ternary Content Addressable Memory at Sub-nm VLSI Technology," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 12, pp. 37-53, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I12P105

Abstract:

A leading-edge sub-nm digital logic technology related to Ternary Content Addressable Memory (TCAM) based binary-memory cell by scaling the CMOS technology has increased the implications of leakage-current and power-analysis for memory design. Conventional TCAM designs have a dynamic CMOS circuit architecture to improve matching speed; however, these implementations have to overcome design limitations, such as process variations of Short-Channel Effects (SCEs). To minimize the SCEs, in this work, a distinct ρ-based DGMOSFET TCAM circuit, binary-memory cell for low-power, available speed-and-area TCAM, using a particular ρ-based binary-memory switch for non-volatile memory data storage is designed. Simulation-based on a distinct ρ-based binary-memory mathematical model analyzed by sub-nm-MOS model parameters. The proposed design analysis and simulation results show better value improvement in delay and energy/bit/search for 64x64-bit TCAM comparatively.

Keywords:

TCAM, SCE, DGMOSFET, Sub-nm, Low power.

References:

[1] K. Prasanth et al., “High Speed, Low Matchline Voltage Swing and Search Line Activity TCAM Cell Array Design in 14nm FinFET Technology,” Emerging Trends in Electrical, Communications, and Information Technologies, vol. 569, 2020.
[Google Scholar] [Publisher Link]
[2] Akshay Krishna Ramanathan et al., “Monolithic 3D+-IC Based Massively Parallel Compute-in-Memory Macro for Accelerating Database and Machine Learning Primitives,” 2020 IEEE International Electron Devices Meeting, pp. 28.5.1-28.5.4, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Leonid Yavits, Roman Kaplan, and Ran Ginosar, “GIRAF: General Purpose In-Storage Resistive Associative Framework,” IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 2, pp. 276-287, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Kai Ni et al., “Ferroelectric Ternary Content Addressable Memory for One-Shot Learning,” Nature Electronics, vol. 2, no. 11, pp. 521- 529, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Guillaume Marcais et al., “Locality Sensitive Hashing for the Edit Distance,” Bioinformatics, vol. 35, no. 14, pp. i127-i135, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Mohammad M.A. Taha, and Christof Teuscher, “Approximate Memristive In-Memory Hamming Distance Circuit,” ACM Journal on Emerging Technologies in Computing Systems, vol. 16, no. 2, pp. 1-14, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Oscar Castaneda et al., “PPAC: A Versatile in-Memory Accelerator for Matrix-Vector-Product-Like Operations,” 2019 IEEE 30th International Conference on Application-Specific Systems, Architectures and Processors, New York, USA, pp. 149-156, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Mannhee Cho, and Youngmin Kim, “Nanoelectromechanical Memory Switch Based Ternary Content-Addressable Memory,” 2020 International SoC Design Conference, Yeosu, Korea, pp. 274-275, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Jae Seong Lee, Jisoo Yoon, and Woo Young Choi, “In-Memory Nearest Neighbor Search with Nanoelectromechanical Ternary Content Addressable Memory,” IEEE Electron Device Letters, vol. 43, no. 1, pp. 154-157, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Jae Seong Lee, and Woo Young Choi, “Nanoelectromechanical-Switch-Based Ternary Content-Addressable Memory (NEMTCAM),” IEEE Transactions on Electron Devices, vol. 68, no. 10, pp. 4903-4909, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Gwangryeol Baek, Jisoo Yoon, and Woo Young Choi, “Tri-State Nanoelectromechanical Memory Switches for the Implementation of a High-Impedance State,” IEEE Access, vol. 8, pp. 202006–202012, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Ik Joon Chang, Yesung Kang, and Youngmin Kim, “Channel Length Biasing for Improving Read Margin of the 8T SRAM at Near Threshold Operation,” Electronics, vol. 8, no. 6, pp. 1-9, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Jae Seong Lee, Jisoo Yoon, and Woo Young Choi, “In-Memory nearest Neighbor Search with Nanoelectromechanical Ternary Content-Addressable Memory,” IEEE Electron Device Letters, vol. 43, no. 1, pp. 154-157, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Nima Taheri Nejad, “Sixor: Single-Cycle in-Memristor XOR,” IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 29, no. 5, pp. 925-935, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] M.G. Sarwar Murshed et al., “Machine Learning at the Network Edge: A Survey,” ACM Computing Surveys, vol. 54, no. 8, pp. 1-37, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Khaled Humood et al., “High-Density Reram Crossbar with Selector Device for Sneak Path Reduction,” 31st International Conference on Microelectronics, Cairo, Egypt, pp. 244-248, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Guodong Yin et al., “Enabling Lower-Power Charge-Domain Nonvolatile In-Memory Computing with Ferroelectric FETs,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 68, no. 7, pp. 2262-2266, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Papanasam Esakki et al., “Improved Dielectrically Modulated Quad Gate Schottky Barrier MOSFET Biosensor,” Micromachines, vol. 14, no. 3, pp. 1-15, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Dibyendu Chowdhury et al., “A Novel Dielectric Modulated Gate-Stack Double-Gate Metal-Oxide-Semiconductor Field-Effect Transistor-Based Sensor for Detecting Biomolecules,” Sensors, vol. 23, no. 6, pp. 1-18, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Isamu Hayashi et al., “A 250‐MHz 18‐Mb Full Ternary CAM with Low‐Voltage Matchline Sensing Scheme in 65‐nm CMOS,” IEEE Journal of Solid-State Circuits, vol. 48, no. 11, pp. 2671-2680, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Le Zheng, Sangho Shin, and Sung-Mo Steve Kang, “Memristor‐Based Ternary Content Addressable Memory (mTCAM) for Data‐ Intensive Computing,” Semiconductor Science and Technology, vol. 29, no. 10, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Sumit Kale, “Investigation of Dual Metal Gate Schottky Barrier MOSFET for Suppression of Ambipolar Current,” IETE Journal of Research, vol. 69, no. 1, pp. 404-409, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Monika Kumari et al., “2-D Analytical Modeling and Simulation of Dual Material, Double Gate, Gate Stack Engineered, Junctionless MOSFET Based Biosensor with Enhanced Sensitivity,” Silicon, vol. 14, pp. 4473-4484, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Sumit Kale, and Madduri Sai Chandu, “Dual Metal Gate Dielectric Engineered Dopant Segregated Schottky Barrier MOSFET with Reduction in Ambipolar Current,” Silicon, vol. 14, pp. 935-941, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Basudha Dewan, Shalini Chaudhary, and Menka Yadav, “Evaluating the Performance Parameters of Triple Metal Dual Gate Vertical Tunnel FET Biosensor,” 2022 IEEE International Students’ Conference on Electrical, Electronics and Computer Science, Bhopal, India, pp. 1-5, 2022.
[CrossRef] [Google Scholar] [Publisher Link]