納米級SRAM單粒子翻轉(zhuǎn)效應(yīng)及其誘導(dǎo)的軟錯誤研究
[Abstract]:With the increasing of space science and technology in our country in recent years, the high-reliability demand for application of microprocessor to radiation environment becomes more and more urgent. SRAM, as a core storage component of the microprocessor, occupies a larger chip area and is extremely sensitive to the single particle inversion effect (SEU) initiated by irradiation. It is necessary to carry out SEU and soft error research of SRAM after the SEU induced soft error in SRAM. after the process size enters the nanometer level, the charge sharing between the integrated circuit devices becomes more serious, so that the SEU sensitivity of the nano-scale SRAM cells is changed, and a plurality of reinforcing methods are caused to fail. At the same time, a new single particle inversion recovery effect (SEUR) is also generated in small size SRAM cells, which can reduce the SEU sensitivity of SRAM by enhancing SEUR. The 3D SRAM based on the three-dimensional stacking technology stacks the traditional SRAM in the vertical direction, and the vertical interconnection is performed using the TSVs, so that a plurality of bottlenecks encountered by the conventional SRAM are solved, However, the 3D SRAM in the irradiation environment will still suffer from the SEU hazard. The 3D SRAM stack structure makes SEU generate and propagate more complex, and then increases the difficulty of soft error analysis of 3D SRAM. meanwhile, the TSV used by the three-dimensional stacking technology can collide with the incident single particle, and further influence the soft error characteristics of the 3D SRAM. In view of the new features of SEU and soft error in nanoscale SRAM cells and 3D SRAM, the relevant research has been carried out and the following achievements have been obtained: (1) The effect of charge sharing on the SEU sensitive characteristics of nanoscale SRAM cells is studied by using 3D TCAD system-wide simulation. Based on the 40nm commercial SRAM cell layout, 3D TCAD device model was built for all transistors in the cell. The SEU sensitive area is then simulated under/ without electrical connection and under different LET conditions, respectively. The simulation results show that charge sharing can reduce the SEU sensitive area of PMOS by 37. 5%, and reduce the SEU sensitive area of NMOS by 65.1%. By analyzing the difference of SEU sensitive area under different conditions, it is found that SEUR based on charge sharing can reduce the SEU sensitivity of PMOS, while on-state PMOS reduces the SEU sensitive area of NMOS by helping to absorb the deposited charge and generate compensation current. In addition, the study shows that NMOS is more sensitive to NMOS than PMOS in SRAM cells. (2) the SEUR effect between the off-state PMOS and the ON-state PMOS and the OFF-state PMOS and the ON-state NMOS are researched in the SRAM cell respectively, and the method for enhancing SEUR is also discussed. Based on the TCAD device/ circuit hybrid simulation, it is found that the generation of SEUR between the off-state PMOS and the ON-state PMOS depends not only on charge sharing, but also the charge collection from the stage device is stronger than that of the main-stage device. Two layouts of DSD and DPI are proposed to enhance the SEUR between two PMOS transistors. Compared with the traditional layout in the vertical incident simulation, the DSD and DPI layout can reduce the SEU sensitive area of 4.26% and 31. 56%, respectively. Only DPI layout can greatly increase the generation probability of SEUR in oblique incidence simulation. This paper also studies the new SEUR of delayed charge collection triggered by charge-collection and open-state NMOS of off-state PMOS. This SEUR is affected by the PMOS and is greatly influenced by the NMOS, so that the SEUR can be enhanced by reducing the PMOS and NMOS spacing in the same inverter, and the width saturation value of the induced SET is equal to the sum of the SEU generation time and the SRAM cell feedback delay. (3) Using the SRIM and Geant4 tools based on Monte Carlo method to study the effect of 3D SRAM stack structure on soft error characteristics. Using the SRIM tool to analyze the range of heavy ions in the three-dimensional stacked structure, the simulation results show that the heavy ion energy can pass through the model of the six-layer die stack after the heavy ion energy is greater than 22MeV/ u, thus it can be seen that each layer in the 3D SRAM may produce soft errors. By using Geant4 simulation to obtain the deposition charge in the sensitive layers of each layer die in the complex three-dimensional stacked structure model, the analysis shows that under the condition of low energy heavy ion bombardment, the soft error characteristics of each layer die are greatly different, but under the condition of high energy heavy ion bombardment, the difference can disappear, and the underlying die is more susceptible to a more severe mcu. It is also found that TSVs have a blocking effect on incident heavy ions, and TSV can reduce the inverted cross section of the surrounding sensitive cells. and (4) constructing a 3D SRAM soft error analysis platform, and analyzing the soft error characteristics of the 3D SRAM. Based on the established SET, SEU simulation method and mature tool, the 3D SRAM soft error analysis platform is established, which can quickly and accurately analyze and evaluate the soft error of 3D SRAM. Based on this platform, soft error analysis of 2D SRAM, word line division 3D SRAM and bit line division 3D SRAM were carried out. The results show that the flip section of the three SRAM is almost the same in the vertical bombardment static test, but the inverted cross section of the 3D SRAM is larger than 2D SRAM in the random incident angle simulation; the word line division 3D SRAM in the static test will produce more serious MBU, Therefore, the bit line division 3D SRAM is more suitable for application in the irradiation environment; the combinational logic circuits of the three SRAM in the dynamic test cause serious MBU; due to the small number of sensitive units around the TSV, the TSV can only reduce the inverted cross section of about 3%.
【學(xué)位授予單位】:國防科學(xué)技術(shù)大學(xué)
【學(xué)位級別】:博士
【學(xué)位授予年份】:2016
【分類號】:TP333
【相似文獻(xiàn)】
相關(guān)期刊論文 前10條
1 吳珍妮;梁華國;黃正峰;陳秀美;曹源;;一種針對軟錯誤的流水線電路加固方案[J];武漢大學(xué)學(xué)報(理學(xué)版);2010年02期
2 朱丹;李暾;李思昆;;形式化等價性檢查指導(dǎo)的軟錯誤敏感點(diǎn)篩選[J];計算機(jī)輔助設(shè)計與圖形學(xué)學(xué)報;2011年03期
3 徐建軍;譚慶平;熊磊;葉俊;;一種針對軟錯誤的程序可靠性定量分析方法[J];電子學(xué)報;2011年03期
4 熊磊;譚慶平;;基于軟錯誤的動態(tài)程序可靠性分析和評估[J];小型微型計算機(jī)系統(tǒng);2011年11期
5 梁華國;黃正峰;王偉;詹文法;;一種雙;ユi的容軟錯誤靜態(tài)鎖存器[J];宇航學(xué)報;2009年05期
6 龔銳;戴葵;王志英;;片上多核處理器容軟錯誤執(zhí)行模型[J];計算機(jī)學(xué)報;2008年11期
7 孫巖;王永文;張民選;;微處理器體系結(jié)構(gòu)級軟錯誤易感性評估[J];計算機(jī)工程與科學(xué);2010年11期
8 成玉;馬安國;張承義;張民選;;微體系結(jié)構(gòu)軟錯誤易感性階段特性研究[J];電子科技大學(xué)學(xué)報;2012年02期
9 張民選;孫巖;宋超;;納米級集成電路的軟錯誤問題及其對策[J];上海交通大學(xué)學(xué)報;2013年01期
10 龔銳;戴葵;王志英;;基于現(xiàn)場保存與恢復(fù)的雙核冗余執(zhí)行模型[J];計算機(jī)工程與科學(xué);2009年08期
相關(guān)會議論文 前7條
1 吳珍妮;梁華國;黃正峰;王俊;陳秀美;曹源;;容軟錯誤的電路選擇性加固技術(shù)[A];第六屆中國測試學(xué)術(shù)會議論文集[C];2010年
2 熊蔭喬;譚慶平;徐建軍;;基于軟件標(biāo)簽的軟錯誤校驗(yàn)和恢復(fù)技術(shù)[A];中國通信學(xué)會第六屆學(xué)術(shù)年會論文集(上)[C];2009年
3 成玉;張承義;張民選;;微體系結(jié)構(gòu)的軟錯誤易感性評估及其階段特性研究[A];第十五屆計算機(jī)工程與工藝年會暨第一屆微處理器技術(shù)論壇論文集(B輯)[C];2011年
4 金作霖;張民選;孫巖;石文強(qiáng);;柵氧退化效應(yīng)下納米級SRAM單元臨界電荷分析[A];第十五屆計算機(jī)工程與工藝年會暨第一屆微處理器技術(shù)論壇論文集(B輯)[C];2011年
5 郭御風(fēng);郭誦忻;龔銳;鄧宇;張明;;一種面向多核處理器I/O系統(tǒng)軟錯誤容錯方法[A];第十五屆計算機(jī)工程與工藝年會暨第一屆微處理器技術(shù)論壇論文集(B輯)[C];2011年
6 周彬;霍明學(xué);肖立伊;;單粒子多脈沖的軟錯誤敏感性分析方法[A];第十六屆全國核電子學(xué)與核探測技術(shù)學(xué)術(shù)年會論文集(上冊)[C];2012年
7 梁麗波;梁華國;黃正峰;;基于功能復(fù)用的增強(qiáng)型掃描結(jié)構(gòu)ESFF-SEAD[A];2011中國儀器儀表與測控技術(shù)大會論文集[C];2011年
相關(guān)博士學(xué)位論文 前10條
1 焦佳佳;處理器中分析模型驅(qū)動的高效軟錯誤量化方法研究[D];上海交通大學(xué);2014年
2 周婉婷;輻照環(huán)境中通信數(shù)字集成電路軟錯誤預(yù)測建模研究[D];電子科技大學(xué);2014年
3 閆愛斌;納米集成電路軟錯誤評估方法研究[D];合肥工業(yè)大學(xué);2015年
4 唐柳;微處理器軟錯誤脆弱性建模及緩解技術(shù)研究[D];北京工業(yè)大學(xué);2016年
5 杜延康;納米CMOS組合電路單粒子誘導(dǎo)的軟錯誤研究[D];國防科學(xué)技術(shù)大學(xué);2015年
6 李鵬;納米級SRAM單粒子翻轉(zhuǎn)效應(yīng)及其誘導(dǎo)的軟錯誤研究[D];國防科學(xué)技術(shù)大學(xué);2016年
7 成玉;高性能微處理器動態(tài)容軟錯誤設(shè)計關(guān)鍵技術(shù)研究[D];國防科學(xué)技術(shù)大學(xué);2012年
8 丁潛;集成電路軟錯誤問題研究[D];清華大學(xué);2009年
9 繩偉光;數(shù)字集成電路軟錯誤敏感性分析與可靠性優(yōu)化技術(shù)研究[D];哈爾濱工業(yè)大學(xué);2009年
10 黃正峰;數(shù)字電路軟錯誤防護(hù)方法研究[D];合肥工業(yè)大學(xué);2009年
相關(guān)碩士學(xué)位論文 前10條
1 徐東超;面向SystemC的軟錯誤敏感度分析方法[D];上海交通大學(xué);2015年
2 靳麗娜;基于SET傳播特性的軟錯誤率研究[D];電子科技大學(xué);2015年
3 潘阿成;一種低功耗抗輻射的TCAM系統(tǒng)設(shè)計[D];大連理工大學(xué);2015年
4 彭小飛;納米工藝下集成電路的容軟錯誤技術(shù)研究[D];合肥工業(yè)大學(xué);2015年
5 張麗娜;集成電路的容軟錯誤技術(shù)研究[D];合肥工業(yè)大學(xué);2014年
6 陳凡;數(shù)字集成電路容忍軟錯誤加固技術(shù)研究[D];合肥工業(yè)大學(xué);2014年
7 蘭風(fēng)宇;Xilinx Virtex-7 FPGA軟錯誤減緩技術(shù)研究[D];哈爾濱工業(yè)大學(xué);2016年
8 袁德冉;納米數(shù)字電路軟錯誤率分析關(guān)鍵技術(shù)研究[D];合肥工業(yè)大學(xué);2016年
9 劉思愷;單粒子軟錯誤在電路中的傳播過程研究[D];國防科學(xué)技術(shù)大學(xué);2014年
10 徐毅;面向軟錯誤的源代碼級故障恢復(fù)技術(shù)研究[D];國防科學(xué)技術(shù)大學(xué);2015年
,本文編號:2254298
本文鏈接:http://sikaile.net/shoufeilunwen/xxkjbs/2254298.html