Ultra low-power fault-tolerant SRAM design in 90nm CMOS technology

With the increment of mobile, biomedical and space applications, digital systems with low-power consumption are required. As a main part in digital systems, low-power memories are especially desired. Reducing the power supply voltages to sub-threshold region is one of the effective approaches for ultra low-power applications. However, the reduced Static Noise Margin (SNM) of Static Random Access Memory (SRAM) imposes great challenges to the subthreshold SRAM design. The conventional 6-transistor SRAM cell does not function properly at sub-threshold supply voltage range because it has no enough noise margin for reliable operation. In order to achieve ultra low-power at sub-threshold operation, previous research work has demonstrated that the read and write decoupled scheme is a good solution to the reduced SNM problem. A Dual Interlocked Storage Cell (DICE) based SRAM cell was proposed to eliminate the drawback of conventional DICE cell during read operation. This cell can mitigate the singleevent effects, improve the stability and also maintain the low-power characteristic of subthreshold SRAM, In order to make the proposed SRAM cell work under different power supply voltages from 0.3 V to 0.6 V, an improved replica sense scheme was applied to produce a reference control signal, with which the optimal read time could be achieved. In this thesis, a 2K ~8 bits SRAM test chip was designed, simulated and fabricated in 90nm CMOS technology provided by ST Microelectronics. Simulation results suggest that the operating frequency at VDD = 0.3 V is up to 4.7 MHz with power dissipation 6.0 ƒÊW, while it is 45.5 MHz at VDD = 0.6 V dissipating 140 ƒÊW. However, the area occupied by a single cell is larger than that by conventional SRAM due to additional transistors used. The main contribution of this thesis project is that we proposed a new design that could simultaneously solve the ultra low-power and radiation-tolerance problem in large capacity memory design

Ultra-Low Power Circuit Design for Cubic-Millimeter Wireless Sensor Platform.

Modern daily life is surrounded by smaller and smaller computing devices. As Bell’s Law predicts, the research community is now looking at tiny computing platforms and mm3-scale sensor systems are drawing an increasing amount of attention since they can create a whole new computing environment. Designing mm3-scale sensor nodes raises various circuit and system level challenges and we have addressed and proposed novel solutions for many of these challenges to create the first complete 1.0mm3 sensor system including a commercial microprocessor. We demonstrate a 1.0mm3 form factor sensor whose modular die-stacked structure allows maximum volume utilization. Low power I2C communication enables inter-layer serial communication without losing compatibility to standard I2C communication protocol. A dual microprocessor enables concurrent computation for the sensor node control and measurement data processing. A multi-modal power management unit allowed energy harvesting from various harvesting sources. An optical communication scheme is provided for initial programming, synchronization and re-programming after recovery from battery discharge. Standby power reduction techniques are investigated and a super cut-off power gating scheme with an ultra-low power charge pump reduces the standby power of logic circuits by 2-19× and memory by 30%. Different approaches for designing low-power memory for mm3-scale sensor nodes are also presented in this work. A dual threshold voltage gain cell eDRAM design achieves the lowest eDRAM retention power and a 7T SRAM design based on hetero-junction tunneling transistors reduces the standby power of SRAM by 9-19× with only 15% area overhead. We have paid special attention to the timer for the mm3-scale sensor systems and propose a multi-stage gate-leakage-based timer to limit the standard deviation of the error in hourly measurement to 196ms and a temperature compensation scheme reduces temperature dependency to 31ppm/°C. These techniques for designing ultra-low power circuits for a mm3-scale sensor enable implementation of a 1.0mm3 sensor node, which can be used as a skeleton for future micro-sensor systems in variety of applications. These microsystems imply the continuation of the Bell’s Law, which also predicts the massive deployment of mm3-scale computing systems and emergence of even smaller and more powerful computing systems in the near future.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91438/1/sori_1.pd

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

Ultra-Low-Power Embedded SRAM Design for Battery- Operated and Energy-Harvested IoT Applications

Internet of Things (IoT) devices such as wearable health monitors, augmented reality goggles, home automation, smart appliances, etc. are a trending topic of research. Various IoT products are thriving in the current electronics market. The IoT application needs such as portability, form factor, weight, etc. dictate the features of such devices. Small, portable, and lightweight IoT devices limit the usage of the primary energy source to a smaller rechargeable or non-rechargeable battery. As battery life and replacement time are critical issues in battery-operated or partially energy-harvested IoT devices, ultra-low-power (ULP) system on chips (SoC) are becoming a widespread solution of chip makers’ choice. Such ULP SoC requires both logic and the embedded static random access memory (SRAM) in the processor to operate at very low supply voltages. With technology scaling for bulk and FinFET devices, logic has demonstrated to operate at low minimum operating voltages (VMIN). However, due to process and temperature variation, SRAMs have higher VMIN in scaled processes that become a huge problem in designing ULP SoC cores. This chapter discusses the latest published circuits and architecture techniques to minimize the SRAM VMIN for scaled bulk and FinFET technologies and improve battery life for ULP IoT applications

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

MFPA: Mixed-Signal Field Programmable Array for Energy-Aware Compressive Signal Processing

Compressive Sensing (CS) is a signal processing technique which reduces the number of samples taken per frame to decrease energy, storage, and data transmission overheads, as well as reducing time taken for data acquisition in time-critical applications. The tradeoff in such an approach is increased complexity of signal reconstruction. While several algorithms have been developed for CS signal reconstruction, hardware implementation of these algorithms is still an area of active research. Prior work has sought to utilize parallelism available in reconstruction algorithms to minimize hardware overheads; however, such approaches are limited by the underlying limitations in CMOS technology. Herein, the MFPA (Mixed-signal Field Programmable Array) approach is presented as a hybrid spin-CMOS reconfigurable fabric specifically designed for implementation of CS data sampling and signal reconstruction. The resulting fabric consists of 1) slice-organized analog blocks providing amplifiers, transistors, capacitors, and Magnetic Tunnel Junctions (MTJs) which are configurable to achieving square/square root operations required for calculating vector norms, 2) digital functional blocks which feature 6-input clockless lookup tables for computation of matrix inverse, and 3) an MRAM-based nonvolatile crossbar array for carrying out low-energy matrix-vector multiplication operations. The various functional blocks are connected via a global interconnect and spin-based analog-to-digital converters. Simulation results demonstrate significant energy and area benefits compared to equivalent CMOS digital implementations for each of the functional blocks used: this includes an 80% reduction in energy and 97% reduction in transistor count for the nonvolatile crossbar array, 80% standby power reduction and 25% reduced area footprint for the clockless lookup tables, and roughly 97% reduction in transistor count for a multiplier built using components from the analog blocks. Moreover, the proposed fabric yields 77% energy reduction compared to CMOS when used to implement CS reconstruction, in addition to latency improvements

Design of Low-Voltage Digital Building Blocks and ADCs for Energy-Efficient Systems

Increasing number of energy-limited applications continue to drive the demand for designing systems with high energy efficiency. This tutorial covers the main building blocks of a system implementation including digital logic, embedded memories, and analog-to-digital converters and describes the challenges and solutions to designing these blocks for low-voltage operation

Near-Threshold Computing

Valmistustekniikoiden kehittyessä IC-piireille saadaan mahtumaan yhä enemmän transistoreja. Monimutkaisemmat piirit mahdollistavat suurempien laskutoimitusmäärien suorittamisen aikayksikössä. Piirien aktiivisuuden lisääntyessä myös niiden energiankulutus lisääntyy, ja tämä puolestaan lisää piirin lämmöntuotantoa. Liiallinen lämpö rajoittaa piirien toimintaa. Tämän takia tarvitaan tekniikoita, joilla piirien energiankulutusta saadaan pienennettyä. Uudeksi tutkimuskohteeksi ovat tulleet pienet laitteet, jotka seuraavat esimerkiksi ihmiskehon toimintaa, rakennuksia tai siltoja. Tällaisten laitteiden on oltava energiankulutukseltaan pieniä, jotta ne voivat toimia pitkiä aikoja ilman akkujen lataamista. Near-Threshold Computing on tekniikka, jolla pyritään pienentämään integroitujen piirien energiankulutusta. Periaatteena on käyttää piireillä pienempää käyttöjännitettä kuin piirivalmistaja on niille alunperin suunnitellut. Tämä hidastaa ja haittaa piirin toimintaa. Jos kuitenkin laitteen toiminnassa pystyään hyväksymään huonompi laskentateho ja pienentynyt toimintavarmuus, voidaan saavuttaa säästöä energiankulutuksessa. Tässä diplomityössä tarkastellaan Near-Threshold Computing -tekniikkaa eri näkökulmista: aluksi perustuen kirjallisuudesta löytyviin aikaisempiin tutkimuksiin, ja myöhemmin tutkimalla Near-Threshold Computing -tekniikan soveltamista kahden tapaustutkimuksen kautta. Tapaustutkimuksissa tarkastellaan FO4-invertteriä sekä 6T SRAM -solua piirisimulaatioiden avulla. Näiden komponenttien käyttäytymisen Near-Threshold Computing –jännitteillä voidaan tulkita antavan kattavan kuvan suuresta osasta tavanomaisen IC-piirin pinta-alaa ja energiankulusta. Tapaustutkimuksissa käytetään 130 nm teknologiaa, ja niissä mallinnetaan todellisia piirivalmistusprosessin tuotteita ajamalla useita Monte Carlo -simulaatioita. Tämä valmistuskustannuksiltaan huokea teknologia yhdistettynä Near-Threshold Computing -tekniikkaan mahdollistaa matalan energiankulutuksen piirien valmistaminen järkevään hintaan. Tämän diplomityön tulokset näyttävät, että Near-Threshold Computing pienentää piirien energiankulutusta merkittävästi. Toisaalta, piirien nopeus heikkenee, ja yleisesti käytetty 6T SRAM -muistisolu muuttuu epäluotettavaksi. Pidemmät polut logiikkapiireissä sekä transistorien kasvattaminen muistisoluissa osoitetaan tehokkaiksi vastatoimiksi Near- Threshold Computing -tekniikan huonoja puolia vastaan. Tulokset antavat perusteita matalan energiankulutuksen IC-piirien suunnittelussa sille, kannattaako käyttää normaalia käyttöjännitettä, vai laskea sitä, jolloin piirin hidastuminen ja epävarmempi käyttäytyminen pitää ottaa huomioon.Siirretty Doriast