Low Leakage and Robust Sub-threshold SRAM Cell using Memristor

This work aims to improve the total power dissipation, leakage currents and stability without disturbing the logic state of SRAM cell with concept called sub-threshold operation. Though, sub-threshold SRAM proves to be advantageous but fails with basic 6T SRAM cell during readability and writability. In this paper we have investigated a non-volatile 6T2M (6 Transistors & 2 Memristors) sub-threshold SRAM cell working at lower supply voltage of VDD=0.3V, where Memristor is used to store the information even at power failures and restores previous data with successful read and write operation overcomes the challenge faced. This paper also proposes a new configuration of non-volatile 6T2M (6 Transistors & 2 Memristors) sub-threshold SRAM cell resulting in improved behaviour in terms of power, stability and leakage current where read and write power has improved by 40% and 90% respectively when compared to 6T2M (conventional) SRAM cell. The proposed 6T2M SRAM cell offers good stability of RSNM=65mV and WSNM=93mV which is much improved at low voltage when compared to conventional basic 6T SRAM cell, and improved leakage current of 4.92nA is achieved as compared

Addressing the RRAM Reliability and Radiation Soft-Errors in the Memory Systems

With the continuous and aggressive technology scaling, the design of memory systems becomes very challenging. The desire to have high-capacity, reliable, and energy efficient memory arrays is rising rapidly. However, from the technology side, the increasing leakage power and the restrictions resulting from the manufacturing limitations complicate the design of memory systems. In addition to this, with the new machine learning applications, which require tremendous amount of mathematical operations to be completed in a timely manner, the interest in neuromorphic systems has increased in recent years. Emerging Non- Volatile Memory (NVM) devices have been suggested to be incorporated in the design of memory arrays due to their small size and their ability to reduce leakage power since they can retain their data even in the absence of power supply. Compared to other novel NVM devices, the Resistive Random Access Memory (RRAM) device has many advantages including its low-programming requirements, the large ratio between its high and low resistive states, and its compatibility with the Complementary Metal Oxide Semiconductor (CMOS) fabrication process. RRAM device suffers from other disadvantages including the instability in its switching dynamics and its sensitivity to process variations. Yet, one of the popular issues hindering the deployment of RRAM arrays in products are the RRAM reliability and radiation soft-errors. The RRAM reliability soft-errors result from the diffusion of oxygen vacations out of the conductive channels within the oxide material of the device. On the other hand, the radiation soft-errors are caused by the highly energetic cosmic rays incident on the junction of the MOS device used as a selector for the RRAM cell. Both of those soft-errors cause the unintentional change of the resistive state of the RRAM device. While there is research work in literature to address some of the RRAM disadvantages such as the switching dynamic instability, there is no dedicated work discussing the impact of RRAM soft-errors on the various designs to which the RRAM device is integrated and how the soft-errors can be automatically detected and fixed. In this thesis, we bring the attention to the need of considering the RRAM soft-errors to avoid the degradation in design performance. In addition to this, using previously reported SPICE models, which were experimentally verified, and widely adapted system level simulators and test benches, various solutions are provided to automatically detect and fix the degradation in design performance due to the RRAM soft-errors. The main focus in this work is to propose methodologies which solve or improve the robustness of memory systems to the RRAM soft-errors. These memories are expected to be incorporated in the current and futuristic platforms running the advanced machine learning applications. In more details, the main contributions of this thesis can be summarized as: - Provide in depth analysis of the impact of RRAM soft-errors on the performance of RRAM-based designs. - Provide a new SRAM cell which uses the RRAM device to reduce the SRAM leakage power with minimal impact on its read and write operations. This new SRAM cell can be incorporated in the Graphical Processing Unit (GPU) design used currently in the implementation of the machine learning platforms. - Provide a circuit and system solutions to resolve the reliability and radiation soft-errors in the RRAM arrays. These solution can automatically detect and fix the soft-errors with minimum impact on the delay and energy consumption of the memory array. - A framework is developed to estimate the effect of RRAM soft-errors on the performance of RRAM-based neuromorphic systems. This actually provides, for the first time, a very generic methodology through which the device level RRAM soft-errors are mapped to the overall performance of the neuromorphic systems. Our analysis show that the accuracy of the RRAM-based neuromorphic system can degrade by more than 48% due to RRAM soft-errors. - Two algorithms are provided to automatically detect and restore the degradation in RRAM-based neuromorphic systems due to RRAM soft-errors. The system and circuit level techniques to implement these algorithms are also explained in this work. In conclusion, this work offers initial steps for enabling the usage of RRAM devices in products by tackling one of its most known challenges: RRAM reliability and radiation soft-errors. Despite using experimentally verified SPICE models and widely popular system simulators and test benches, the provided solutions in this thesis need to be verified in the future work through fabrication to study the impact of other RRAM technology shortcomings including: a) the instability in its switching dynamics due to the stochastic nature of oxygen vacancies movement, and b) its sensitivity to process variations

Switching event detection and self-termination programming circuit for energy efficient ReRAM memory arrays

Energy efficiency remains a challenge for the design of non-volatile resistive memories (ReRAMs) arrays. This memory technology suffers from intrinsic variability in switching speed, programming voltages and resistance levels. The programming conditions of memory elements (e.g. pulse widths and amplitudes) must cover the tail bits to avoid programming failures. Switching time of ReRAMs shows wide distributions. Therefore, fast cells are subjects for electrical stress after their switching and energy waste since programming currents are typically large for this technology (tens of µA). In this paper, we present a Write Termination (WT) circuit to stop the programming operation when the switching event occurs in the selected memory element. The proposed design is sensitive to current variations that take place when the memory element switches between two different resistance states (LRS and HRS). This WT scheme reduces the power consumption by 97+%, 93+% and 65+% during Forming, RESET and SET operations respectively. Our estimations show that area efficiency of 70% for a memory array is achievable when the presented WT circuit is integrated in near-memory peripheries. The demonstrated WT circuit is suitable for different ReRAM technologies with small overhead penalty and shows robustness against CMOS and ReRAM variabilities

Energy/Reliability Trade-Offs in Low-Voltage ReRAM-Based Non-Volatile Flip-Flop Design

The total power budget of Ultra-Low Power (ULP) VLSI Systems-on-Chip (SoCs) is often dominated by the leakage power of embedded memories as well as status registers. On the one hand, supply voltage scaling down to the near-threshold (near-VT) or even to the subthreshold (sub-VT) domain is a commonly used, efficient technique to reduce both leakage power and active energy dissipation. On the other hand, emerging CMOS-compatible device technologies such as Resistive Memories (ReRAMs) enable non-volatile, on-chip data storage and zero-leakage sleep periods. For the first time, we present and compare ReRAM-based Non-Volatile Flip-Flop (NVFF) topologies which are optimized for low-voltage operation (including near-VT and sub-VT operation). Three low-voltage NVFF circuit topologies are proposed and evaluated in terms of energy dissipation and reliability. Using topologies with two complementary programmed ReRAM devices, Monte Carlo simulations accounting for parametric variations confirm reliable data restore operation from the ReRAM devices at a sub- voltage as low as 400 mV. A topology using a single ReRAM device exhibits lower write energy, but requires a near- voltage for robust read. Energy characterization is performed at nominal, near-VT , and sub-VT supply voltages. The minimum energy point is reached for near-VT read operation with a total read+write energy of 735 fJ

Designing energy-efficient sub-threshold logic circuits using equalization and non-volatile memory circuits using memristors

The very large scale integration (VLSI) community has utilized aggressive complementary metal-oxide semiconductor (CMOS) technology scaling to meet the ever-increasing performance requirements of computing systems. However, as we enter the nanoscale regime, the prevalent process variation effects degrade the CMOS device reliability. Hence, it is increasingly essential to explore emerging technologies which are compatible with the conventional CMOS process for designing highly-dense memory/logic circuits. Memristor technology is being explored as a potential candidate in designing non-volatile memory arrays and logic circuits with high density, low latency and small energy consumption. In this thesis, we present the detailed functionality of multi-bit 1-Transistor 1-memRistor (1T1R) cell-based memory arrays. We present the performance and energy models for an individual 1T1R memory cell and the memory array as a whole. We have considered TiO2- and HfOx-based memristors, and for these technologies there is a sub-10% difference between energy and performance computed using our models and HSPICE simulations. Using a performance-driven design approach, the energy-optimized TiO2-based RRAM array consumes the least write energy (4.06 pJ/bit) and read energy (188 fJ/bit) when storing 3 bits/cell for 100 nsec write and 1 nsec read access times. Similarly, HfOx-based RRAM array consumes the least write energy (365 fJ/bit) and read energy (173 fJ/bit) when storing 3 bits/cell for 1 nsec write and 200 nsec read access times. On the logic side, we investigate the use of equalization techniques to improve the energy efficiency of digital sequential logic circuits in sub-threshold regime. We first propose the use of a variable threshold feedback equalizer circuit with combinational logic blocks to mitigate the timing errors in digital logic designed in sub-threshold regime. This mitigation of timing errors can be leveraged to reduce the dominant leakage energy by scaling supply voltage or decreasing the propagation delay. At the fixed supply voltage, we can decrease the propagation delay of the critical path in a combinational logic block using equalizer circuits and, correspondingly decrease the leakage energy consumption. For a 8-bit carry lookahead adder designed in UMC 130 nm process, the operating frequency can be increased by 22.87% (on average), while reducing the leakage energy by 22.6% (on average) in the sub-threshold regime. Overall, the feedback equalization technique provides up to 35.4% lower energy-delay product compared to the conventional non-equalized logic. We also propose a tunable adaptive feedback equalizer circuit that can be used with sequential digital logic to mitigate the process variation effects and reduce the dominant leakage energy component in sub-threshold digital logic circuits. For a 64-bit adder designed in 130 nm our proposed approach can reduce the normalized delay variation of the critical path delay from 16.1% to 11.4% while reducing the energy-delay product by 25.83% at minimum energy supply voltage. In addition, we present detailed energy-performance models of the adaptive feedback equalizer circuit. This work serves as a foundation for the design of robust, energy-efficient digital logic circuits in sub-threshold regime

Nouvelles Architectures Hybrides (Logique / Mémoires Non-Volatiles et technologies associées.)

Les nouvelles approches de technologies mémoires permettront une intégration dite back-end, où les cellules élémentaires de stockage seront fabriquées lors des dernières étapes de réalisation à grande échelle du circuit. Ces approches innovantes sont souvent basées sur l'utilisation de matériaux actifs présentant deux états de résistance distincts. Le passage d'un état à l'autre est contrôlé en courant ou en tension donnant lieu à une caractéristique I-V hystérétique. Nos mémoires résistives sont composées d'argent en métal électrochimiquement actif et de sulfure amorphe agissant comme électrolyte. Leur fonctionnement repose sur la formation réversible et la dissolution d'un filament conducteur. Le potentiel d'application de ces nouveaux dispositifs n'est pas limité aux mémoires ultra-haute densité mais aussi aux circuits embarqués. En empilant ces mémoires dans la troisième dimension au niveau des interconnections des circuits logiques CMOS, de nouvelles architectures hybrides et innovantes deviennent possibles. Il serait alors envisageable d'exploiter un fonctionnement à basse énergie, à haute vitesse d'écriture/lecture et de haute performance telles que l'endurance et la rétention. Dans cette thèse, en se concentrant sur les aspects de la technologie de mémoire en vue de développer de nouvelles architectures, l'introduction d'une fonctionnalité non-volatile au niveau logique est démontrée par trois circuits hybrides: commutateurs de routage non volatiles dans un Field Programmable Gate Arrays, un 6T-SRAM non volatile, et les neurones stochastiques pour un réseau neuronal. Pour améliorer les solutions existantes, les limitations de la performances des dispositifs mémoires sont identifiés et résolus avec des nouveaux empilements ou en fournissant des défauts de circuits tolérants.Novel approaches in the field of memory technology should enable backend integration, where individual storage nodes will be fabricated during the last fabrication steps of the VLSI circuit. In this case, memory operation is often based upon the use of active materials with resistive switching properties. A topology of resistive memory consists of silver as electrochemically active metal and amorphous sulfide acting as electrolyte and relies on the reversible formation and dissolution of a conductive filament. The application potential of these new memories is not limited to stand-alone (ultra-high density), but is also suitable for embedded applications. By stacking these memories in the third dimension at the interconnection level of CMOS logic, new ultra-scalable hybrid architectures becomes possible which exploit low energy operation, fast write/read access and high performance with respect to endurance and retention. In this thesis, focusing on memory technology aspects in view of developing new architectures, the introduction of non-volatile functionality at the logic level is demonstrated through three hybrid (CMOS logic ReRAM devices) circuits: nonvolatile routing switches in a Field Programmable Gate Array, nonvolatile 6T-SRAMs, and stochastic neurons of an hardware neural network. To be competitive or even improve existing solutions, limitations on the memory devices performances are identified and solved by stack engineering of CBRAM devices or providing faults tolerant circuits.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Non-volatile FPGA architecture using resistive switching devices

This dissertation reports the research work that was conducted to propose a non-volatile architecture for FPGA using resistive switching devices. This is achieved by designing a Configurable Memristive Logic Block (CMLB). The CMLB comprises of memristive logic cells (MLC) interconnected to each other using memristive switch matrices. In the MLC, novel memristive D flip-flop (MDFF), 6-bit non-volatile look-up table (NVLUT), and CMOS-based multiplexers are used. Other than the MDFF, a non-volatile D-latch (NVDL) was also designed. The MDFF and the NVDL are proposed to replace CMOS-based D flip-flops and D-latches to improve energy consumption. The CMLB shows a reduction of 8.6% of device area and 1.094 times lesser critical path delay against the SRAM-based FPGA architecture. Against similar CMOS-based circuits, the MDFF provides switching speed of 1.08 times faster; the NVLUT reduces power consumption by 6.25nW and improves device area by 128 transistors; while the memristive logic cells reduce overall device area by 60.416μm2. The NVLUT is constructed using novel 2TG1M memory cells, which has the fastest switching times of 12.14ns, compared to other similar memristive memory cells. This is due to the usage of transmission gates which improves voltage transfer from input to the memristor. The novel 2TG1M memory cell also has lower energy consumption than the CMOS-based 6T SRAM cell. The memristive-based switch matrices that interconnects the MLCs together comprises of novel 7T1M SRAM cells, which has the lowest energy-delay-area-product value of 1.61 among other memristive SRAM cells. Two memristive logic gates (MLG) were also designed (OR and AND), that introduces non-volatility into conventional logic gates. All the above circuits and design simulations were performed on an enhanced SPICE memristor model, which was improved from a previously published memristor model. The previously published memristor model was fault to not be in good agreement with memristor theory and the physical model of memristors. Therefore, the enhanced SPICE memristor model provides a memristor model which is in good agreement with the memristor theory and the physical model of memristors, which is used throughout this research work

Bipolar resistive switching and memristive properties of hydrothermally synthesized TiO2 nanorod array: Effect of growth temperature

The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.matdes.2018.04.046 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/In the present work, the hydrothermal approach is employed to develop 1D-TiO2 nanorod array memristive devices and the effect of hydrothermal growth temperature on TiO2 memristive devices is studied. X-ray diffraction (XRD) analysis suggested that the rutile phase is dominant in the developed TiO2 nanorod array. Field emission scanning electron microscopy (FESEM) images show well adherent and pinhole free one dimensional (1D) TiO2 nanorods. The presence of titanium and oxygen in all the samples was confirmed by energy dispersive X-ray spectroscopy (EDS). Furthermore, growth of the 1D TiO2 nanorods depends on the growth temperature and uniform growth is observed at the higher growth temperatures. The well-known memristive hysteresis loop is observed in the TiO2 nanorod thin films. Furthermore, resistive switching voltages, the shape of I-V loops and (non)rectifying behavior changed as the growth temperature varied from 140 °C to 170 °C. The biological synapse properties such as paired-pulse facilitation and short-term depression are observed in some devices. The detailed electrical characterizations suggested that the developed devices show doubled valued charge-magnetic flux characteristic and charge transportation is due to the Ohmic and space charge limited current.Funding from School of Nanoscience and Biotechnology, Shivaji University, Kolhapu

Non-volatile FPGA architecture using resistive switching devices

This dissertation reports the research work that was conducted to propose a non-volatile architecture for FPGA using resistive switching devices. This is achieved by designing a Configurable Memristive Logic Block (CMLB). The CMLB comprises of memristive logic cells (MLC) interconnected to each other using memristive switch matrices. In the MLC, novel memristive D flip-flop (MDFF), 6-bit non-volatile look-up table (NVLUT), and CMOS-based multiplexers are used. Other than the MDFF, a non-volatile D-latch (NVDL) was also designed. The MDFF and the NVDL are proposed to replace CMOS-based D flip-flops and D-latches to improve energy consumption. The CMLB shows a reduction of 8.6% of device area and 1.094 times lesser critical path delay against the SRAM-based FPGA architecture. Against similar CMOS-based circuits, the MDFF provides switching speed of 1.08 times faster; the NVLUT reduces power consumption by 6.25nW and improves device area by 128 transistors; while the memristive logic cells reduce overall device area by 60.416μm2. The NVLUT is constructed using novel 2TG1M memory cells, which has the fastest switching times of 12.14ns, compared to other similar memristive memory cells. This is due to the usage of transmission gates which improves voltage transfer from input to the memristor. The novel 2TG1M memory cell also has lower energy consumption than the CMOS-based 6T SRAM cell. The memristive-based switch matrices that interconnects the MLCs together comprises of novel 7T1M SRAM cells, which has the lowest energy-delay-area-product value of 1.61 among other memristive SRAM cells. Two memristive logic gates (MLG) were also designed (OR and AND), that introduces non-volatility into conventional logic gates. All the above circuits and design simulations were performed on an enhanced SPICE memristor model, which was improved from a previously published memristor model. The previously published memristor model was fault to not be in good agreement with memristor theory and the physical model of memristors. Therefore, the enhanced SPICE memristor model provides a memristor model which is in good agreement with the memristor theory and the physical model of memristors, which is used throughout this research work