三维集成电路中内存的经时击穿分析与检测

doi:10.19665/j.issn1001-2400.2019.04.025

Abstract

Abstract:

3D multicore systems with stacked DRAM are capable of boosting system performance significantly, but accompanied with the key problem of the effect of heat density and heat dissipation on circuit reliability. Aiming to study the TDDB (Time Dependent Dielectric Breakdown) effect in DRAM of 3D-ICs, we adopt a physical-based SPICE model and analyze the statistical TDDB degradation induced by the gate leakage current in peripheral circuits of DRAM. Meanwhile, a TDDB detection design is proposed based on the 45nm process, which is suitable for large scale integration of the memory circuit. And the operation of the detection circuit is analyzed based on the BTI (Bias Temperature Instability) effect. Experimental results show that sense amplifiers are more susceptible to time dependent dielectric breakdown than word-line drivers in DRAM. The proposed TDDB detection design can completely meet the maximum fault coverage rate with good robustness to BTI, and it will send out an alarm signal when TDDB happens in the sense amplifier.

Key words: reliability, time dependent dielectric breakdown, three dimensional integrated circuit, dynamic random access memory, detection

CLC Number:

TN47

JIA Dingcheng,WANG Leilei,GAO Wei. Analysis and detection of TDDB degradation for DRAM in 3D-ICs[J].Journal of Xidian University, 2019, 46(4): 182-189.

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References 19

[1]	JIA D C, ZHOU P Q. Effective Activating Compensation Logic for DRAMs in 3D-ICs [C]//Proceedings of the 2019 China Semiconductor Technology International Conference. Piscataway: IEEE, 2019: 8755615.
[2]	AHMED F, MILOR L . Analysis and On-chip Monitoring of Gate Oxide Breakdown in SRAM Cells[J]. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2012,20(5):855-864.
[3]	HO C H, KIM S Y, PANAGOPOULOS G D , et al. Statistical TDDB Degradation in Memory Circuits: Bit-cells to Arrays[J]. IEEE Transactions on Electron Devices, 2016,63(6):2384-2390.
[4]	潘少俊 . 集成电路栅介质TDDB失效预警电路设计[D]. 广州: 暨南大学, 2014.
[5]	李新瑞 . 基于TDDB效应的年龄传感器技术研究[D]. 成都: 电子科技大学, 2017.
[6]	LI S, AHN J H, STRONG R D. et al. McPAT: an Integrated Power, Area, and Timing Modeling Framework for Multicore and Manycore Architectures [C]//Proceedings of the 2009 Annual International Symposium on Microarchitecture. Washington: IEEE Computer Society, 2009: 469-480.
[7]	SKADRON K, STAN M R, SANKARANARAYANAN K , et al. Temperature-aware Microarchitecture: Modeling and Implementation[J]. ACM Transactions on Architecture and Code Optimization, 2004,1(1):94-125.
[8]	WU E, SUÑÉ J, LAROW C. et al. Temperature Dependence of TDDB Voltage Acceleration in High-κ/SiO₂ Bilayers and SiO₂ Gate Dielectrics [C]//Proceedings of the 2012 IEEE International Electron Devices Meeting. Piscataway: IEEE, 2012: 653-656.
[9]	SUÑÉ J, WU E Y, LAI W L . Statistics of Competing Post-breakdown Failure Modes in Ultrathin MOS Devices[J]. IEEE Transactions on Electron Devices, 2006,53(2):224-234.
[10]	马仲发, 庄奕琪, 杜磊 , 等. 栅氧化层击穿的统一逾渗模型[J]. 西安电子科技大学学报, 2004,31(1):54-58.
	MA Zhongfa, ZHUANG Yiqi, DU Lei , et al. Unified Percolation Model for Gate Oxide Breakdown[J]. Journal of Xidian University, 2004,31(1):54-58.
[11]	MIRANDA E, SUÑÉ J . Electron Transport through Broken Down Ultra-thin SiO₂ Layers in MOS Devices[J]. Microelectronics Reliability, 2004,44(1):1-23.
[12]	KIM S Y, HO C H, ROY K . Statistical SBD Modeling and Characterization and Its Impact on SRAM Cells[J]. IEEE Transactions on Electron Devices, 2014,61(1):54-59.
[13]	KIM S Y, PANAGOPOULOS G, HO C H. et al. A Compact SPICE Model for Statistical Post-breakdown Gate Current Increase Due to TDDB [C]//2013 IEEE International Reliability Physics Symposium Proceedings. Piscataway: IEEE, 2013: 6531942.
[14]	JACOB B, NG S, WANG D . Memory Systems: Cache, DRAM, Disk[M]. Boston: Elsevier Academic, 2010: 353-375.
[15]	VOGELSANG T. Understanding the Energy Consumption of Dynamic Random Access Memories [C]//Proceedings of the 2010 Annual International Symposium on Microarchitecture. Washington: IEEE Computer Society, 2010: 363-374.
[16]	LEE D, KHAN S, SUBRAMANIAN L , et al. Design-induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms[J]. Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2017,1(1):a26.
[17]	CHANG K K, YAGLIKÇI A G, GHOSE S, et al . Understanding Reduced-voltage Operation in Modern Dram Devices: Experimental Characterization, Analysis, and Mechanisms[J]. Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2017,1(1):a9.
[18]	LIU J, JAIYEN B, KIM Y. et al. An Experimental Study of Data Retention Behavior in Modern DRAM Devices: Implications for Retention Time Profiling Mechanisms [C]//Proceedings of the 2013 International Symposium on Computer Architecture. Piscataway: IEEE, 2013: 60-71.
[19]	SUTARIA K, RAMKUMAR A, ZHU R G. et al. BTI-induced Aging under Random Stress Waveforms: Modeling, Simulation and Silicon Validation [C]//Proceedings of the 51st Design Automation Conference. Piscataway: IEEE, 2014: 2593101.

Analysis and detection of TDDB degradation for DRAM in 3D-ICs

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