Dual Column, Replica Bitline Delay Technique Using Stochastic Current Processing for a Process Variation Tolerant, Low Power SRAM

SRAM (Static Random Access Memory) design has become the critical and important block in processing ICs with the highest bandwidth power rationed memories taking the business lead. As industry attempts to maintain Moore's law by shrinking the device size, we are facing greater issues with the variability due to random doping fluctuation in devices. This variation compels engineers to design for worst case conditions which leads to inefficient memory model, which make it difficult to stand in the business race. However, a smart design can lead to less variation and “exact” memory parametric prediction to achieve high performance, low power and maximum yield designs. Since, random variation today is more dominant, we consider the application of the central limit theorem to control memory read timing across PVT (Process Voltage Temperature) corners. A statistical read timing is developed for a SRAM memory bank. In the thesis two dummy columns, each at extreme end of the memory bank, are used to implement the statistical memory bank model. By combining Monte-Carlo analysis using cadence virtuoso, and PDK data for the CMOS process (IBM 7RF), an analytically memory timing model is verified. Our major goal is to improve yield across all memory banks in all die across all the wafers; slow-slow (SS), typical-typical (TT) and fast-fast (FF).A smart stochastic/statistical approach is used in the thesis to predict exact parametric yield parameters with less variation to design accurate memory system which gives high performance, low power and maximum yield across all PVT corners to keep you ahead in the memory business. The memory design is compared to the conventional self-timed replica architecture using coefficient of variance of a reference current generated using dummy column. The proposed architecture was able to achieve 62 percent across the process improved accuracy in reference current and sense amplifier firing variation. Proposed architecture looks promising for future node technologies where statistical variability and its impact in subthreshold region is more dominant.Electrical Engineerin

Study of Single-Event Transient Effects on Analog Circuits

Radiation in space is potentially hazardous to microelectronic circuits and systems such as spacecraft electronics. Transient effects on circuits and systems from high energetic particles can interrupt electronics operation or crash the systems. This phenomenon is particularly serious in complementary metal-oxide-semiconductor (CMOS) integrated circuits (ICs) since most of modern ICs are implemented with CMOS technologies. The problem is getting worse with the technology scaling down. Radiation-hardening-by-design (RHBD) is a popular method to build CMOS devices and systems meeting performance criteria in radiation environment. Single-event transient (SET) effects in digital circuits have been studied extensively in the radiation effect community. In recent years analog RHBD has been received increasing attention since analog circuits start showing the vulnerability to the SETs due to the dramatic process scaling. Analog RHBD is still in the research stage. This study is to further study the effects of SET on analog CMOS circuits and introduces cost-effective RHBD approaches to mitigate these effects. The analog circuits concerned in this study include operational amplifiers (op amps), comparators, voltage-controlled oscillators (VCOs), and phase-locked loops (PLLs). Op amp is used to study SET effects on signal amplitude while the comparator, the VCO, and the PLL are used to study SET effects on signal state during transition time. In this work, approaches based on multi-level from transistor, circuit, to system are presented to mitigate the SET effects on the aforementioned circuits. Specifically, RHBD approach based on the circuit level, such as the op amp, adapts the auto-zeroing cancellation technique. The RHBD comparator implemented with dual-well and triple-well is studied and compared at the transistor level. SET effects are mitigated in a LC-tank oscillator by inserting a decoupling resistor. The RHBD PLL is implemented on the system level using triple modular redundancy (TMR) approach. It demonstrates that RHBD at multi-level can be cost-effective to mitigate the SEEs in analog circuits. In addition, SETs detection approaches are provided in this dissertation so that various mitigation approaches can be implemented more effectively. Performances and effectiveness of the proposed RHBD are validated through SPICE simulations on the schematic and pulsed-laser experiments on the fabricated circuits. The proposed and tested RHBD techniques can be applied to other relevant analog circuits in the industry to achieve radiation-tolerance

Low-Power Soft-Error-Robust Embedded SRAM

Soft errors are radiation-induced ionization events (induced by energetic particles like alpha particles, cosmic neutron, etc.) that cause transient errors in integrated circuits. The circuit can always recover from such errors as the underlying semiconductor material is not damaged and hence, they are called soft errors. In nanometer technologies, the reduced node capacitance and supply voltage coupled with high packing density and lack of masking mechanisms are primarily responsible for the increased susceptibility of SRAMs towards soft errors. Coupled with these are the process variations (effective length, width, and threshold voltage), which are prominent in scaled-down technologies. Typically, SRAM constitutes up to 90% of the die in microprocessors and SoCs (System-on-Chip). Hence, the soft errors in SRAMs pose a potential threat to the reliable operation of the system. In this work, a soft-error-robust eight-transistor SRAM cell (8T) is proposed to establish a balance between low power consumption and soft error robustness. Using metrics like access time, leakage power, and sensitivity to single event transients (SET), the proposed approach is evaluated. For the purpose of analysis and comparisons the results of 8T cell are compared with a standard 6T SRAM cell and the state-of-the-art soft-error-robust SRAM cells. Based on simulation results in a 65-nm commercial CMOS process, the 8T cell demonstrates higher immunity to SETs along with smaller area and comparable leakage power. A 32-kb array of 8T cells was fabricated in silicon. After functional verification of the test chip, a radiation test was conducted to evaluate the soft error robustness. As SRAM cells are scaled aggressively to increase the overall packing density, the smaller transistors exhibit higher degrees of process variation and mismatch, leading to larger offset voltages. For SRAM sense amplifiers, higher offset voltages lead to an increased likelihood of an incorrect decision. To address this issue, a sense amplifier capable of cancelling the input offset voltage is presented. The simulated and measured results in 180-nm technology show that the sense amplifier is capable of detecting a 4 mV differential input signal under dc and transient conditions. The proposed sense amplifier, when compared with a conventional sense amplifier, has a similar die area and a greatly reduced offset voltage. Additionally, a dual-input sense amplifier architecture is proposed with corroborating silicon results to show that it requires smaller differential input to evaluate correctly.1 yea

Reliability in the face of variability in nanometer embedded memories

In this thesis, we have investigated the impact of parametric variations on the behaviour of one performance-critical processor structure - embedded memories. As variations manifest as a spread in power and performance, as a first step, we propose a novel modeling methodology that helps evaluate the impact of circuit-level optimizations on architecture-level design choices. Choices made at the design-stage ensure conflicting requirements from higher-levels are decoupled. We then complement such design-time optimizations with a runtime mechanism that takes advantage of adaptive body-biasing to lower power whilst improving performance in the presence of variability. Our proposal uses a novel fully-digital variation tracking hardware using embedded DRAM (eDRAM) cells to monitor run-time changes in cache latency and leakage. A special fine-grain body-bias generator uses the measurements to generate an optimal body-bias that is needed to meet the required yield targets. A novel variation-tolerant and soft-error hardened eDRAM cell is also proposed as an alternate candidate for replacing existing SRAM-based designs in latency critical memory structures. In the ultra low-power domain where reliable operation is limited by the minimum voltage of operation (Vddmin), we analyse the impact of failures on cache functional margin and functional yield. Towards this end, we have developed a fully automated tool (INFORMER) capable of estimating memory-wide metrics such as power, performance and yield accurately and rapidly. Using the developed tool, we then evaluate the #effectiveness of a new class of hybrid techniques in improving cache yield through failure prevention and correction. Having a holistic perspective of memory-wide metrics helps us arrive at design-choices optimized simultaneously for multiple metrics needed for maintaining lifetime requirements

Low-power and high-performance SRAM design in high variability advanced CMOS technology

As process technologies shrink, the size and number of memories on a chip are exponentially increasing. Embedded SRAMs are a critical component in modern digital systems, and they strongly impact the overall power, performance, and area. To promote memory-related research in academia, this dissertation introduces OpenRAM, a flexible, portable and open-source memory compiler and characterization methodology for generating and verifying memory designs across different technologies.In addition, SRAM designs, focusing on improving power consumption, access time and bitcell stability are explored in high variability advanced CMOS technologies. To have a stable read/write operation for SRAM in high variability process nodes, a differential-ended single-port 8T bitcell is proposed that improves the read noise margin, write noise margin and readout bitcell current by 45%, 48% and 21%, respectively, compared to a conventional 6T bitcell. Also, a differential-ended single-port 12T bitcell for subthreshold operation is proposed that solves the half-select disturbance and allows efficient bit-interleaving. 12T bitcell has a leakage control mechanism which helps to reduce the power consumption and provides operation down to 0.3 V. Both 8T and 12T bitcells are analyzed in a 64 kb SRAM array using 32 nm technology. Besides, to further improve the access time and power consumption, two tracking circuits (multi replica bitline delay and reconfigurable replica bitline delay techniques) are proposed to aid the generation of accurate and optimum sense amplifier set time.An error tolerant SRAM architecture suitable for low voltage video application with dynamic power-quality management is also proposed in this dissertation. This memory uses three power supplies to improve the SRAM stability in low voltages. The proposed triple-supply approach achieves 63% improvement in image quality and 69% reduction in power consumption compared to a single-supply 64 kb SRAM array at 0.70 V

Circuit Techniques for Adaptive and Reliable High Performance Computing.

Increasing power density with process scaling has caused stagnation in the clock speed of modern microprocessors. Accordingly, designers have adopted message passing and shared memory based multicore architectures in order to keep up with the rapidly rising demand for computing throughput. At the same time, applications are not entirely parallel and improving single-thread performance continues to remain critical. Additionally, reliability is also worsening with process scaling, and margining for failures due to process and environmental variations in modern technologies consumes an increasingly large portion of the power/performance envelope. In the wake of multicore computing, reliability of signal synchronization between the cores is also becoming increasingly critical. This forces designers to search for alternate efficient methods to improve compute performance while addressing reliability. Accordingly, this dissertation presents innovative circuit and architectural techniques for variation-tolerance, performance and reliability targeted at datapath logic, signal synchronization and memories. Firstly, a domino logic based design style for datapath logic is presented that uses Adaptive Robustness Tuning (ART) in addition to timing speculation to provide up to 71% performance gains over conventional domino logic in 32bx32b multiplier in 65nm CMOS. Margins are reduced until functionality errors are detected, that are used to guide the tuning. Secondly, for signal synchronization across clock domains, a new class of dynamic logic based synchronizers with single-cycle synchronization latency is presented, where pulses, rather than stable intermediate voltages cause metastability. Such pulses are amplified using skewed inverters to improve mean time between failures by ~1e6x over jamb latches and double flip-flops at 2GHz in 65nm CMOS. Thirdly, a reconfigurable sensing scheme for 6T SRAMs is presented that employs auto-zero calibration and pre-amplification to improve sensing reliability (by up to 1.2 standard deviations of NMOS threshold voltage in 28nm CMOS); this increased reliability is in turn traded for ~42% sensing speedup. Finally, a main memory architecture design methodology to address reliability and power in the context of Exascale computing systems is presented. Based on 3D-stacked DRAMs, the methodology co-optimizes DRAM access energy, refresh power and the increased cost of error resilience, to meet stringent power and reliability constraints.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107238/1/bharan_1.pd

Semiconductor Memory Applications in Radiation Environment, Hardware Security and Machine Learning System

abstract: Semiconductor memory is a key component of the computing systems. Beyond the conventional memory and data storage applications, in this dissertation, both mainstream and eNVM memory technologies are explored for radiation environment, hardware security system and machine learning applications. In the radiation environment, e.g. aerospace, the memory devices face different energetic particles. The strike of these energetic particles can generate electron-hole pairs (directly or indirectly) as they pass through the semiconductor device, resulting in photo-induced current, and may change the memory state. First, the trend of radiation effects of the mainstream memory technologies with technology node scaling is reviewed. Then, single event effects of the oxide based resistive switching random memory (RRAM), one of eNVM technologies, is investigated from the circuit-level to the system level. Physical Unclonable Function (PUF) has been widely investigated as a promising hardware security primitive, which employs the inherent randomness in a physical system (e.g. the intrinsic semiconductor manufacturing variability). In the dissertation, two RRAM-based PUF implementations are proposed for cryptographic key generation (weak PUF) and device authentication (strong PUF), respectively. The performance of the RRAM PUFs are evaluated with experiment and simulation. The impact of non-ideal circuit effects on the performance of the PUFs is also investigated and optimization strategies are proposed to solve the non-ideal effects. Besides, the security resistance against modeling and machine learning attacks is analyzed as well. Deep neural networks (DNNs) have shown remarkable improvements in various intelligent applications such as image classification, speech classification and object localization and detection. Increasing efforts have been devoted to develop hardware accelerators. In this dissertation, two types of compute-in-memory (CIM) based hardware accelerator designs with SRAM and eNVM technologies are proposed for two binary neural networks, i.e. hybrid BNN (HBNN) and XNOR-BNN, respectively, which are explored for the hardware resource-limited platforms, e.g. edge devices.. These designs feature with high the throughput, scalability, low latency and high energy efficiency. Finally, we have successfully taped-out and validated the proposed designs with SRAM technology in TSMC 65 nm. Overall, this dissertation paves the paths for memory technologies’ new applications towards the secure and energy-efficient artificial intelligence system.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Design and Implementation of Low Power SRAM Using Highly Effective Lever Shifters

The explosive growth of battery-operated devices has made low-power design a priority in recent years. In high-performance Systems-on-Chip, leakage power consumption has become comparable to the dynamic component, and its relevance increases as technology scales. These trends are even more evident for SRAM memory devices since they are a dominant source of standby power consumption in low-power application processors. The on-die SRAM power consumption is particularly important for increasingly pervasive mobile and handheld applications where battery life is a key design and technology attribute. In the SRAM-memory design, SRAM cells also comprise the most significant portion of the total chip. Moreover, the increasing number of transistors in the SRAM memories and the MOSs\u27 increasing leakage current in the scaled technologies have turned the SRAM unit into a power-hungry block for both dynamic and static viewpoints. Although the scaling of the supply voltage enables low-power consumption, the SRAM cells\u27 data stability becomes a major concern. Thus, the reduction of SRAM leakage power has become a critical research concern. To address the leakage power consumption in high-performance cache memories, a stream of novel integrated circuit and architectural level techniques are proposed by researchers including leakage-current management techniques, cell array leakage reduction techniques, bitline leakage reduction techniques, and leakage current compensation techniques. The main goal of this work was to improve the cell array leakage reduction techniques in order to minimize the leakage power for SRAM memory design in low-power applications. This study performs the body biasing application to reduce leakage current as well. To adjust the NMOSs\u27 threshold voltage and consequently leakage current, a negative DC voltage could be applied to their body terminal as a second gate. As a result, in order to generate a negative DC voltage, this study proposes a negative voltage reference that includes a trimming circuit and a negative level shifter. These enhancements are employed to a 10kb SRAM memory operating at 0.3V in a 65nm CMOS process