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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91253完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 胡璧合 | zh_TW |
| dc.contributor.advisor | Pi-Ho Hu | en |
| dc.contributor.author | 方少甫 | zh_TW |
| dc.contributor.author | Shao-Fu Fang | en |
| dc.date.accessioned | 2023-12-20T16:09:16Z | - |
| dc.date.available | 2023-12-21 | - |
| dc.date.copyright | 2023-12-20 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2023-10-06 | - |
| dc.identifier.citation | [1] C. C. Wu et al., "High performance 22/20nm FinFET CMOS devices with advanced high-K/metal gate scheme," 2010 International Electron Devices Meeting, San Francisco, CA, 2010, pp. 27.1.1-27.1.4.
[2] S. . -W. Chang et al., "First Demonstration of CMOS Inverter and 6T-SRAM Based on GAA CFETs Structure for 3D-IC Applications," 2019 IEEE International Electron Devices Meeting (IEDM), 2019, pp. 11.7.1-11.7.4. [3] S. Subramanian et al., "First Monolithic Integration of 3D Complementary FET (CFET) on 300mm Wafers," 2020 IEEE Symposium on VLSI Technology, 2020, pp. 1-2. [4] R. Chau, "Process and Packaging Innovations for Moore’s Law Continuation and Beyond," 2019 IEEE International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2019, pp. 1.1.1-1.1.6. [5] R. S. Patti, "Three-Dimensional Integrated Circuits and the Future of System-on-Chip Designs," 2006 Proceedings of the IEEE, 2006, pp. 1214-1224. [6] S. Datta, S. Dutta, B. Grisafe, J. Smith, S. Srinivasa and H. Ye, "Back-End-of-Line Compatible Transistors for Monolithic 3-D Integration," 2019 IEEE Micro, 2019, pp. 8-15. [7] T. Song et al., "A 10 nm FinFET 128 Mb SRAM With Assist Adjustment System for Power, Performance, and Area Optimization," in IEEE Journal of Solid-State Circuits, vol. 52, no. 1, pp. 240-249, Jan. 2017. [8] S. M. Salahuddin, K. A. Shaik, A. Gupta, B. Chava, M. Gupta, P. Weckx, J. Ryckaert and A. Spessot,"SRAM With Buried Power Distribution to Improve Write Margin and Performance in Advanced Technology Nodes," in IEEE Electron Device Letters, vol. 40, no. 8, pp. 1261-1264, Aug. 2019. [9] G. Sisto et al., "IR-Drop Analysis of Hybrid Bonded 3D-ICs with Backside Power Delivery and μ- & n- TSVs," 2021 IEEE International Interconnect Technology Conference (IITC), Kyoto, Japan, 2021, pp. 1-3. [10] W. Chakraborty, K. Ni, J. Smith, A. Raychowdhury and S. Datta, "An Empirically Validated Virtual Source FET Model for Deeply Scaled Cool CMOS," 2019 IEEE International Electron Devices Meeting (IEDM), 2019, pp. 39.4.1-39.4.4. [11] B. Patra et al., "Cryo-CMOS Circuits and Systems for Quantum Computing Applications," in IEEE Journal of Solid-State Circuits, vol. 53, no. 1, pp. 309-321, Jan. 2018. [12] J. Y. -. Sun, Yuan Taur, R. H. Dennard and S. P. Klepner, "Submicrometer-channel CMOS for low-temperature operation," in IEEE Transactions on Electron Devices, vol. 34, no. 1, pp. 19-27, Jan. 1987. [13] A. Beckers, F. Jazaeri, A. Ruffino, C. Bruschini, A. Baschirotto and C. Enz, "Cryogenic characterization of 28 nm bulk CMOS technology for quantum computing," 2017 47th European Solid-State Device Research Conference (ESSDERC), 2017, pp. 62-65. [14] J. Chang et al., "12.1 A 7nm 256Mb SRAM in high-k metal-gate FinFET technology with write-assist circuitry for low-VMIN applications," 2017 IEEE International Solid-State Circuits Conference (ISSCC), 2017, pp. 206-207. [15] H. -L. Chiang et al., "Design Technology Co-Optimization for Cold CMOS Benefits in Advanced Technologies," 2021 IEEE International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2021, pp. 13.2.1-13.2.4. [16] V. P. -H. Hu et al., "High-Density and High-Speed 4T FinFET SRAM for Cryogenic Computing," 2021 IEEE International Electron Devices Meeting (IEDM), 2021, pp. 8.6.1-8.6.4. [17] V. P.-H. Hu and C.-J. Liu, "Static Noise Margin Analysis for Cryo-CMOS SRAM Cell," IEEE International Symposium on Radio-Frequency Integration Technology (RFIT), Taiwan, August 2021. [18] S. -F. Fang and V. P. -H. Hu, "Stability and Performance Optimization of 6T SRAM Cell at Cryogenic Temperature," 2023 7th IEEE Electron Devices Technology & Manufacturing Conference (EDTM), Seoul, Korea, Republic of, 2023, pp. 1-3. [19] W. Chakraborty et al., "Cool-CMOS Technology for Next Generation High Performance Computing," 2021 International Symposium on VLSI Technology, Systems and Applications (VLSI-TSA), 2021, pp. i-i. [20] D. Prasad et al., "Cryo-Computing for Infrastructure Applications: A Technology-to-Microarchitecture Co-optimization Study," 2022 International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2022, pp. 23.5.1-23.5.4. [21] R. Joshi, J. Timmerwilke, K. Tien, M. Yeck and S. Chakraborty, "A 0.31V Vmin Cryogenic SRAM in 14 nm FinFET for Quantum Computing," 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits), Honolulu, HI, USA, 2022, pp. 232-233. [22] B. Patra et al., "Cryo-CMOS Circuits and Systems for Quantum Computing Applications," in IEEE Journal of Solid-State Circuits, vol. 53, no. 1, pp. 309-321, Jan. 2018. [23] S. Sekiguchi, M. -J. Ahn, T. Mizutani, T. Saraya, M. Kobayashi and T. Hiramoto, "Subthreshold Swing in Silicon Gate-All-Around Nanowire and Fully Depleted SOI MOSFETs at Cryogenic Temperature," in IEEE Journal of the Electron Devices Society, vol. 9, pp. 1151-1154, 2021. [24] P. Wang, X. Peng, W. Chakraborty, A. I. Khan, S. Datta and S. Yu, "Cryogenic Benchmarks of Embedded Memory Technologies for Recurrent Neural Network based Quantum Error Correction," 2020 IEEE International Electron Devices Meeting (IEDM), 2020, pp. 38.5.1-38.5.4. [25] X. -K. Cheng, T. -C. Tung and T. -H. Tsai, "A Low-Power Current Readout for 77K Cryo-CMOS Quantum Systems with In-Circuit Model Extraction and Embedded Leakage-Based Temperature Monitoring," 2022 International Symposium on VLSI Technology, Systems and Applications (VLSI-TSA), Hsinchu, Taiwan, 2022, pp. 1-2. [26] Y. Hu et al., "Cryo-CMOS Model-Enabled 8-Bit Current Steering DAC Design for Quantum Computing," 2022 IEEE International Symposium on Circuits and Systems (ISCAS), Austin, TX, USA, 2022, pp. 3413-3417. [27] P. Wang, X. Peng, W. Chakraborty, A. Khan, S. Datta and S. Yu, "Cryogenic Performance for Compute-in-Memory Based Deep Neural Network Accelerator," 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 2021, pp. 1-4. [28] T. Hiramoto et al., "Effect of Random Potential Fluctuations on Threshold Voltage Variability in Bulk MOSFETs at Cryogenic Temperature," 2022 6th IEEE Electron Devices Technology & Manufacturing Conference (EDTM), Oita, Japan, 2022, pp. 381-383. [29] K. Okamoto et al., "Cryogenic CMOS Performance Analysis Including BEOL Characteristics at 4K for Quantum Controller Application," 2022 IEEE International Interconnect Technology Conference (IITC), San Jose, CA, USA, 2022, pp. 139-141, [30] V. Moroz et al., "Challenges in Design and Modeling of Cold CMOS HPC Technology," 2021 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD), Dallas, TX, USA, 2021, pp. 107-110. [31] M. Cassé et al., "FDSOI for cryoCMOS electronics: device characterization towards compact model," 2022 International Electron Devices Meeting (IEDM), San Francisco, CA, USA, 2022, pp. 34.6.1-34.6.4. [32] M. Lapedus, "FeFETs are a promising next-gen memory based on well understood material," 2018, https://semiengineering.com/a-new memory-contender/ [33] Xue, X.; Sai Kumar, A.; Khalaf, O.I.; Somineni, R.P.; Abdulsahib, G.M.; Sujith, A.; Dhanuja, T.; Vinay, M.V.S. Design and Performance Analysis of 32 × 32 Memory Array SRAM for Low-Power Applications. Electronics 2023, 12, 834. [34] H. L. Chiang et al., "Cold CMOS as a Power-Performance-Reliability Booster for Advanced FinFETs," 2020 IEEE Symposium on VLSI Technology, 2020, pp. 1-2. [35] Lawrence T. Clark, Vinay Vashishtha, Lucian Shifren, Aditya Gujja, Saurabh Sinha, Brian Cline, Chandarasekaran Ramamurthy, Greg Yeric,” A 7-nm finFET predictive process design kit,” Microelectronics Journal, Volume 53, July 2016, Pages 105-115. [36] S. M. Salahuddin et al., "SRAM With Buried Power Distribution to Improve Write Margin and Performance in Advanced Technology Nodes," in IEEE Electron Device Letters, vol. 40, no. 8, pp. 1261-1264, Aug. 2019. [37] W. Chakraborty et al., "Cryogenic RF CMOS on 22nm FDSOI Platform with Record fT=495GHz and fMAX=497GHz," 2021 Symposium on VLSI Technology, 2021, pp. 1-2. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91253 | - |
| dc.description.abstract | 隨著製程技術的發展,同時降低供應電壓與臨界電壓會導致整體電路的靜態功率嚴重增加以及穩定性下降,使得互補式金氧半場效電晶體(complementary metal-oxide semiconductor, CMOS)元件的微縮碰到一定的困難,此外,隨著摩爾定律持續的演進,後段製程金屬導線電阻值會快速的增加,進而降低電路的效能。低溫CMOS是一個極有潛力解決效能下降問題的技術,透過將元件操作在低溫的環境下,在提高電路性能的同時也能降低功率消耗。然而,將低溫CMOS操作在低供應電壓與低臨界電壓的條件下,依然面臨穩定性不足的挑戰,因此,需要利用設計技術協同優化(design technology co-optimization, DTCO)來同時改善性能和穩定度。本論文考慮低溫矽鰭式場效電晶體(Si FinFET)之電流電壓實驗數據,並與TCAD模型進行校正,分析6T和8T靜態隨機存取記憶體(static random-access memory, SRAM)在低溫下的性能表現,分析讀寫穩定度和速度等特性,最後提出在77K下6T與8T SRAM的優化設計。
本論文分析並比較經過優化後的6T opt2、Opt 6N2P 8T與Opt-LVR 4N4P 8T三種SRAM,研究結果顯示Opt-LVR 4N4P 8T SRAM在各方面的性能上都優於其他的記憶體設計,與77K 6T LVT相比,Opt-LVR 4N4P 8T SRAM提升讀取穩定度達540%、寫入穩定度達78%,在讀取時間(-40%)與能量消耗(-61%)上,相較於300K 6T Baseline SRAM皆有更好的表現,儘管77K Opt-LVR 4N4P 8T SRAM有著面積較大的劣勢,仍能利用積層型三維(Monolithic 3D, M3D)堆疊技術來克服此問題,其4顆N型與4顆P型元件所組成SRAM電路,在積層型三維堆疊技術中,可以利用一層N型元件及一層P型元件的堆疊方式,使整體面積達到40%的下降,解決面積過大的問題。 此外與300K 6T Baseline的SRAM相比,Opt-LVR 4N4P 8T SRAM在相同功率下具有顯著的速度增益(+45%),在相同速度下也表現較低的功率消耗(-73%)。Opt-LVR 4N4P 8T SRAM在供應電壓降到0.45V時,仍有不錯的速度表現及並降低73%的功率消耗,具備高潛力應用於高效能運算應用。 | zh_TW |
| dc.description.abstract | As the process technology advances, simultaneous reduction of supply voltage and threshold voltage results in a significant increase in overall circuit static power and a decline in stability. This poses challenges for scaling Complementary Metal-Oxide-Semiconductor (CMOS) devices. Furthermore, with the continued evolution of Moore's Law, the metal wire resistance in the Back-End-of-Line(BEOL) process increases rapidly, leading to decreased circuit performance. Low-temperature CMOS is a promising technique to address this performance degradation issue, achieved by operating components in a low-temperature environment, which enhances circuit performance while reducing power consumption.
However, operating low-temperature CMOS under conditions of low supply voltage and low threshold voltage still faces challenges in terms of stability. Therefore, Design Technology Co-Optimization (DTCO) is needed to simultaneously enhance performance and stability. This thesis considers experimental current-voltage data of low-temperature silicon FinFET, calibrated against TCAD models. It analyzes the performance of 6T and 8T Static Random-Access Memory (SRAM) under low-temperature conditions, examining characteristics such as read and write stability and speed. Finally, it presents optimized designs for 6T and 8T SRAM at 77K. The thesis analyzes and compares three optimized SRAM designs: 6T opt2, Opt 6N2P 8T, and Opt-LVR 4N4P 8T. Results demonstrate that Opt-LVR 4N4P 8T SRAM outperforms other memory designs in various aspects. Compared to 77K 6T LVT, Opt-LVR 4N4P 8T SRAM achieves a 540% improvement in read stability and a 78% improvement in write stability. In terms of read time (-40%) and energy consumption (-61%), it outperforms the 300K 6T Baseline SRAM. Despite the larger area of 77K Opt-LVR 4N4P 8T SRAM, this issue can be addressed using Monolithic 3D (M3D) stacking technology. In M3D stacking, the SRAM circuit composed of 4 N-type and 4 P-type components can achieve a 40% overall area reduction by stacking one layer of N-type components and one layer of P-type components, overcoming the problem of excessive area. Additionally, compared to the 300K 6T Baseline SRAM, Opt-LVR 4N4P 8T SRAM demonstrates significant speed gains (+45%) at the same power, and lower power consumption (-73%) at the same speed. Even at a reduced supply voltage of 0.45V, Opt-LVR 4N4P 8T SRAM maintains good speed performance and reduces power consumption by 73%, making it highly suitable for high-performance computing applications. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-12-20T16:09:16Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2023-12-20T16:09:16Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 口試委員審定書 I
致謝 II 摘要 III ABSTRACT V 目錄 VII 圖目錄 X 目錄 XIII 第一章 導論 1 1.1 背景與相關研究 1 1.1.1 低溫金氧半場效電晶體 (Cryo-CMOS) 3 1.1.2 靜態隨機存取記憶體 7 1.1.3 靜態隨機存取記憶體周邊電路 9 1.2 研究動機 10 1.3 論文架構 11 第二章 6T與8T靜態隨機存取記憶體之操作 12 2.1 前言 12 2.2 6T和8T靜態隨機存取記憶體讀取電路介紹 13 2.3 8T 靜態隨機存取記憶體介紹 17 2.4 靜態雜訊邊界介紹 20 2.5 靜態隨機存取記憶體性能分析 23 2.5.1 讀取時間(Cell read access time) 23 2.5.2 寫入時間(Time to write) 25 2.6 靜態與動態功率 27 2.7 能量延遲積 30 2.8 感測延遲(Sensing delay) 31 第三章 分析與優化低溫6T靜態隨機存取記憶體 33 3.1 前言 33 3.2 元件ID-VG參數校正與低溫元件特性 34 3.3 元件結構及模擬參數 36 3.4 77K的6T靜態隨機存取記憶體 37 3.5 77K下優化臨界電壓的6T SRAM單元設計及其性能分析 40 3.5.1 佈局設計(Layout design) 40 3.5.2 靜態雜訊邊界分析 42 3.5.3 金屬線電阻電容計算 48 3.5.4 速度-功率分析 49 3.6 結論 50 第四章 分析與優化低溫8T靜態隨機存取記憶體 51 4.1 前言 51 4.2 6T和8T靜態隨機存取記憶體讀取電路介紹 53 4.2.1 6T靜態隨機存取記憶體讀取電路介紹 54 4.2.2 8T靜態隨機存取記憶體讀取電路介紹 57 4.3 77K下6N2P 8T靜態隨機存取記憶體的設計技術協同優化 60 4.3.1 佈局設計(Layout design) 60 4.3.2 77K下6N2P 8T靜態隨機存取記憶體的設計技術協同優化(DTCO)介紹 61 4.3.3 Opt 6N2P 8T SRAM靜態雜訊邊界分析 63 4.3.4 Opt 6N2P 8T SRAM讀取時間分析 65 4.3.5 Opt 6N2P 8T SRAM能量消耗分析 66 4.4 77K下4N4P 8T靜態隨機存取記憶體的設計技術協同優化 67 4.4.1 佈局設計(Layout design) 67 4.4.2 77K下4N4P 8T靜態隨機存取記憶體的設計技術協同優化(DTCO)介紹 68 4.4.3 Opt 4N4P 8T SRAM靜態雜訊邊界分析 73 4.4.4 Opt-LVR 4N4P 8T SRAM讀取時間分析 75 4.4.5 Opt-LVR 4N4P 8T SRAM能量消耗分析 76 4.5 77K下不同6T和8T靜態隨機存取記憶體單元的基準比較 77 4.5.1 靜態雜訊邊界分析 78 4.5.2 讀取時間分析 80 4.5.3 能量消耗分析 81 4.5.4 速度-功率分析 82 4.6 結論 83 第五章 總結與未來展望 84 5.1 總結 85 5.2 未來展望 86 參考文獻 87 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 能量效率 | zh_TW |
| dc.subject | 靜態隨機存取記憶體 | zh_TW |
| dc.subject | 能量效率 | zh_TW |
| dc.subject | 低溫金氧半場效電晶體 | zh_TW |
| dc.subject | 設計技術協同優化 | zh_TW |
| dc.subject | 設計技術協同優化 | zh_TW |
| dc.subject | 低溫金氧半場效電晶體 | zh_TW |
| dc.subject | 靜態隨機存取記憶體 | zh_TW |
| dc.subject | Design Technology Co-Optimization (DTCO) | en |
| dc.subject | Design Technology Co-Optimization (DTCO) | en |
| dc.subject | SRAM | en |
| dc.subject | SRAM | en |
| dc.subject | energy efficiency | en |
| dc.subject | Cryo-CMOS | en |
| dc.subject | energy efficiency | en |
| dc.subject | Cryo-CMOS | en |
| dc.title | 低溫靜態隨機存取記憶體應用於高效能運算之優化 | zh_TW |
| dc.title | Optimization of Cryogenic SRAM Cells for High-Performance Computing Applications | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 胡振國;李進福 | zh_TW |
| dc.contributor.oralexamcommittee | Jenn-Gwo Hwu;Jin-Fu Li | en |
| dc.subject.keyword | 設計技術協同優化,低溫金氧半場效電晶體,能量效率,靜態隨機存取記憶體, | zh_TW |
| dc.subject.keyword | Design Technology Co-Optimization (DTCO),Cryo-CMOS,energy efficiency,SRAM, | en |
| dc.relation.page | 90 | - |
| dc.identifier.doi | 10.6342/NTU202304298 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2023-10-11 | - |
| dc.contributor.author-college | 電機資訊學院 | - |
| dc.contributor.author-dept | 電子工程學研究所 | - |
| 顯示於系所單位: | 電子工程學研究所 | |
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