Design Of 1K Asynchronous Static Random Access Memory Using 0.35 Micron Complementary Metal Oxide Semiconductor Technology

Static Random Access Memory (SRAM) is a high speed semiconductor memory which is widely used as cache memory in microprocessors and microcontrollers, telecommunication and networking devices. The SRAM operations are categorized into two main groups: asynchronous and synchronous. A synchronous SRAM has external clock input signal to control all the memory operation synchronously at either positive or negative edge of the clock signal. While, in asynchronous SRAM, the memory events are not referred or controlled by the external clock. In this study, we have proposed an asynchronous SRAM which configured with a self-holding system in the control unit. The self-holding SRAM control system can produce appropriate signals internally to operate the SRAM system automatically, eliminating hold and wait time, and eliminating Sense Enable and Output Enable signals which usually used in SRAM control system. All input signals are synchronized by the internal control unit. The overall SRAM operations however do not depend on the rising of falling edge of the global (external) clock signal, and thus, the design is still categorized under asynchronous SRAM. The proposed self-holding control system has been developed for a 1 kilobit SRAM using MIMOS 0.35 micron 3.3V CMOS technology Due to limited computer resources such as speed and space, the design had been limited to 1 kilobit memory size. The design covers both schematic and layout designs using Hspice and Cadence Layout Editor, respectively. Meanwhile analysis covers Hspice, Timernill and LVS (Layout versus Schematic). The simulation results have shown the self-holding SRAM control system was working successfully. The design operation speed was 7.0% faster as compared to the SRAM system without the self-holding circuit. An operation speed of 66Mhz with access time of 2.85ns was achieved

VERY LARGE SCALE INTEGRATION TINY CHIP WITH NANOPOWER SENSOR APPLICATIONS

Semiconductor devices have rapidly advanced over the past years increasing switching(on and off) speed and density of the device, causing an increase in power consumption and power dissipation; accordingly, the issues have been considered and improved . In CMOS 0.5μm process, the designed VLSI mirror-amplifier had power dissipation of 8.41 milliwatts. This technique is changed in this paper. The biasing is done in two steps proved to be correct procedure to improve overall power consumption. Source voltage was considered as 3V for the MOSIS process technology. Layout ,simulation and electrical characterization of the design were carried out by MENTOR GRAPHICS tool and CAD tools were used for the design Holding the scaling and process unchanged at 0.5μm as the previous design, the new VLSI design had power dissipation of 4.39 nanowatts in second step by reducing the dynamic loss. Multi-die chip placement is done for fabrication. More advanced 0.35um CMOS process is used for low threshold voltage and enhanced supply voltage range. This paper presents details of the key research works, results, completed chip layout and applications of the chip

A Process Variation Tolerant Self-Compensation Sense Amplifier Design

As we move under the aegis of the Moore\u27s law, we have to deal with its darker side with problems like leakage and short channel effects. Once we go beyond 45nm regime process variations also have emerged as a significant design concern.Embedded memories uses sense amplifier for fast sensing and typically, sense amplifiers uses pair of matched transistors in a positive feedback environment. A small difference in voltage level of applied input signals to these matched transistors is amplified and the resulting logic signals are latched. Intra die variation causes mismatch between the sense transistors that should ideally be identical structures. Yield loss due to device and process variations has never been so critical to cause failure in circuits. Due to growth in size of embedded SRAMs as well as usage of sense amplifier based signaling techniques, process variations in sense amplifiers leads to significant loss of yield for that we need to come up with process variation tolerant circuit styles and new devices. In this work impact of transistor mismatch due to process variations on sense amplifier is evaluated and this problem is stated. For the solution of the problem a novel self compensation scheme on sense amplifiers is presented on different technology nodes up to 32nm on conventional bulk MOSFET technology. Our results show that the self compensation technique in the conventional bulk MOSFET latch type sense amplifier not just gives improvement in the yield but also leads to improvement in performance for latch type sense amplifiers. Lithography related CD variations, fluctuations in dopant density, oxide thickness and parametric variations of devices are identified as a major challenge to the classical bulk type MOSFET. With the emerging nanoscale devices, SIA roadmap identifies FinFETs as a candidate for post-planar end-of-roadmap CMOS device. With current technology scaling issues and with conventional bulk type MOSFET on 32nm node our technique can easily be applied to Double Gate devices. In this work, we also develop the model of Double Gate MOSFET through 3D Device Simulator Damocles and TCAD simulator. We propose a FinFET based process variation tolerant sense amplifier design that exploits the back gate of FinFET devices for dynamic compensation against process variations. Results from statistical simulation show that the proposed dynamic compensation is highly effective in restoring yield at a level comparable to that of sense amplifiers without process variations. We created the 32nm double gate models generated from Damocles 3-D device simulations [25] and Taurus Device Simulator available commercially from Synopsys [47] and use them in the nominal latch type sense amplifier design and on the Independent Gate Self Compensation Sense Amplifier Design (IGSSA) to compare the yield and performance benefits of sense amplifier design on FinFET technology over the conventional bulk type CMOS based sense amplifier on 32nm technology node effective in restoring yield at a level comparable to that of sense amplifiers without process variations. We created the 32nm double gate models generated from Damocles 3-D device simulations [25] and Taurus Device Simulator available commercially from Synopsys [47] and use them in the nominal latch type sense amplifier design and on the Independent Gate Self Compensation Sense Amplifier Design (IGSSA) to compare the yield and performance benefits of sense amplifier design on FinFET technology over the conventional bulk type CMOS based sense amplifier on 32nm technology node

Study of Radiation-Tolerant SRAM Design

Static Random Access Memories (SRAMs) are important storage components and widely used in digital systems. Meanwhile, with the continuous development and progress of aerospace technologies, SRAMs are increasingly used in electronic systems for spacecraft and satellites. Energetic particles in space environments can cause single event upsets normally referred as soft errors in the memories, which can lead to the failure of systems. Nowadays electronics at the ground level also experience this kind of upset mainly due to cosmic neutrons and alpha particles from packaging materials, and the failure rate can be 10 to 100 times higher than the errors from hardware failures. Therefore, it is important to study the single event effects in SRAMs and develop cost-effective techniques to mitigate these errors. The objectives of this thesis are to evaluate the current mitigation techniques of single event effects in SRAMs and develop a radiation-tolerant SRAM based on the developed techniques. Various radiation sources and the mechanism of their respective effects in Complementary Metal-Oxide Semiconductors(CMOS) devices are reviewed first in the thesis. The radiation effects in the SRAMs, specifically single event effects are studied, and various mitigation techniques are evaluated. Error-correcting codes (ECC) are studied in the thesis since they can detect and correct single bit errors in the cell array, and it is a effective method with low overhead in terms of area, speed, and power. Hamming codes are selected and implemented in the design of the SRAM, to protect the cells from single event upsets in the SRAM. The simulation results show they can prevent the single bit errors in the cell arrays with low area and speed overhead. Another important and vulnerable part of SRAMs in radiation environments is the sense amplifier. It may not generate the correct output during the reading operation if it is hit by an energetic particle. A novel fault-tolerant sense amplifier is introduced and validated with simulations. The results showed that the performance of the new design can be more than ten times better than that of the reference design. When combining the SRAM cell arrays protected with ECC and the radiation-tolerant hardened sense amplifiers, the SRAM can achieve high reliability with low speed and area overhead

Design of ALU and Cache Memory for an 8 bit ALU

The design of an ALU and a Cache memory for use in a high performance processor was examined in this thesis. Advanced architectures employing increased parallelism were analyzed to minimize the number of execution cycles needed for 8 bit integer arithmetic operations. In addition to the arithmetic unit, an optimized SRAM memory cell was designed to be used as cache memory and as fast Look Up Table. The ALU consists of stand alone units for bit parallel computation of basic integer arithmetic operations. Addition and subtraction were performed using Kogge Stone parallel prefix hardware operating at 330MHz. A high performance multiplier was built using Radix 4 Modified Booth Encoder (MBE) and a Wallace Tree summation array. The multiplier requires single clock cycle for 8 bit integer multiplication and operates at a maximum frequency of 100MHz. Multiplicative division hardware was built for executing both integer division and square root. The division hardware computes 8-bit division and square root in 4 clock cycles. Multiplier forms the basic building block of all these functional units, making high level of resource sharing feasible with this architecture. The optimal operating frequency for the arithmetic unit is 70MHz. A 6T CMOS SRAM cell measuring 90 µm2 was designed using minimum size transistors. The layout allows for horizontal overlap resulting in effective area of 76 µm2 for an 8x8 array. By substituting equivalent bit line capacitance of P4 L1 Cache, the memory was simulated to have a read time of 3.27ns. An optimized set of test vectors were identified to enable high fault coverage without the need for any additional test circuitry. Sixteen test cases were identified that would toggle all the nodes and provide all possible inputs to the sub units of the multiplier. A correlation based semi automatic method was investigated to facilitate test case identification for large multipliers. This method of testability eliminates performance and area overhead associated with conventional testability hardware. Bottom up design methodology was employed for the design. The performance and area metrics are presented along with estimated power consumption. A set of Monte Carlo analysis was carried out to ensure the dependability of the design under process variations as well as fluctuations in operating conditions. The arithmetic unit was found to require a total die area of 2mm2 (approx.) in 0.35 micron process

An ultra-low power in-memory computing cell for binarized neural networks

Deep Neural Networks (DNN’s) are widely used in many artificial intelligence applications such as image classification and image recognition. Data movement in DNN’s results in increased power consumption. The primary reason behind the energy-expensive data movement in DNN’s is due to the conventional Von Neuman architecture in which computing unit and memory are physically separated. To address the issue of energy-expensive data movement in DNN’s in-memory computing schemes are proposed in the literature. The fundamental principle behind in-memory computing is to enable the vector computations closer to the memory. In-memory computing schemes based on CMOS technologies are of great importance nowadays due to the ease of massive production and commercialization. However, many of the proposed in-memory computing schemes suffer from power and performance degradation. Besides, some of them are capable of reducing power consumption only to a small extent and this requires sacrificing the overall signal to noise ratio (SNR). This thesis discusses an efficient In-Memory Computing (IMC) cell for Binarized Neural Networks (BNNs). Moreover, IMC cell was modelled using the simplest current computing method. In this thesis, the developed IMC cell is a practical solution to the energy-expensive data movement within the BNNs. A 4-bit Digital to Analog Converter (DAC) is designed and simulated using 130nm CMOS process. Using the 4-bit DAC the functionality of IMC scheme for BNNs is demonstrated. The optimised 4-bit DAC shows that it is a powerful IMC method for BNNs. The results presented in this thesis show this approach of IMC is capable of accurately performing dot operation between the input activations and the weights. Furthermore, 4-bit DAC provides a 4-bit weight precision, which provides an effective means to improve the overall accuracy

Digital and analog TFET circuits: Design and benchmark

In this work, we investigate by means of simulations the performance of basic digital, analog, and mixed-signal circuits employing tunnel-FETs (TFETs). The analysis reviews and complements our previous papers on these topics. By considering the same devices for all the analysis, we are able to draw consistent conclusions for a wide variety of circuits. A virtual complementary TFET technology consisting of III-V heterojunction nanowires is considered. Technology Computer Aided Design (TCAD) models are calibrated against the results of advanced full-quantum simulation tools and then used to generate look-up-tables suited for circuit simulations. The virtual complementary TFET technology is benchmarked against predictive technology models (PTM) of complementary silicon FinFETs for the 10 nm node over a wide range of supply voltages (VDD) in the sub-threshold voltage domain considering the same footprint between the vertical TFETs and the lateral FinFETs and the same static power. In spite of the asymmetry between p- and n-type transistors, the results show clear advantages of TFET technology over FinFET for VDDlower than 0.4 V. Moreover, we highlight how differences in the I-V characteristics of FinFETs and TFETs suggest to adapt the circuit topologies used to implement basic digital and analog blocks with respect to the most common CMOS solutions

Digital and analog TFET circuits: Design and benchmark

In this work, we investigate by means of simulations the performance of basic digital, analog, and mixed-signal circuits employing tunnel-FETs (TFETs). The analysis reviews and complements our previous papers on these topics. By considering the same devices for all the analysis, we are able to draw consistent conclusions for a wide variety of circuits. A virtual complementary TFET technology consisting of III-V heterojunction nanowires is considered. Technology Computer Aided Design (TCAD) models are calibrated against the results of advanced full-quantum simulation tools and then used to generate look-up-tables suited for circuit simulations. The virtual complementary TFET technology is benchmarked against predictive technology models (PTM) of complementary silicon FinFETs for the 10 nm node over a wide range of supply voltages (VDD) in the sub-threshold voltage domain considering the same footprint between the vertical TFETs and the lateral FinFETs and the same static power. In spite of the asymmetry between p- and n-type transistors, the results show clear advantages of TFET technology over FinFET for VDDlower than 0.4 V. Moreover, we highlight how differences in the I-V characteristics of FinFETs and TFETs suggest to adapt the circuit topologies used to implement basic digital and analog blocks with respect to the most common CMOS solutions