A 128Kb RAM Design with Capacitor-Based Offset Compensation and Double-Diode based Read Assist Circuits at Low VDD

Low power static random access memory (SRAM) takes significant portion of area on chip in all modern SOCs and emerging Computing-in-memory applications for edge devices in IoT. This work proposes novel readability assist with the double-diode based word line under drive (WLUD) has been effective improving the read-static noise-margin (RSNM) by 26–46%and proposed a capacitor based current controlled sense amplifier offset compensation scheme. This scheme achieves 4X reduction in standard deviation of offset voltage over conventional sense amplifier design with 1.1% and 2.9% of area, power overheads respectively with 90 nm CMOS technology at 0.5–1.0 V supply voltages

A 128Kb RAM Design with Capacitor-Based Offset Compensation and Double-Diode based Read Assist Circuits at Low VDD

788-793Low power static random access memory (SRAM) takes significant portion of area on chip in all modern SOCs and emerging Computing-in-memory applications for edge devices in IoT. This work proposes novel readability assist with the double-diode based word line under drive (WLUD) has been effective improving the read-static noise-margin (RSNM) by 26–46%and proposed a capacitor based current controlled sense amplifier offset compensation scheme. This scheme achieves 4X reduction in standard deviation of offset voltage over conventional sense amplifier design with 1.1% and 2.9% of area, power overheads respectively with 90 nm CMOS technology at 0.5–1.0 V supply voltages

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

Solid State Circuits Technologies

The evolution of solid-state circuit technology has a long history within a relatively short period of time. This technology has lead to the modern information society that connects us and tools, a large market, and many types of products and applications. The solid-state circuit technology continuously evolves via breakthroughs and improvements every year. This book is devoted to review and present novel approaches for some of the main issues involved in this exciting and vigorous technology. The book is composed of 22 chapters, written by authors coming from 30 different institutions located in 12 different countries throughout the Americas, Asia and Europe. Thus, reflecting the wide international contribution to the book. The broad range of subjects presented in the book offers a general overview of the main issues in modern solid-state circuit technology. Furthermore, the book offers an in depth analysis on specific subjects for specialists. We believe the book is of great scientific and educational value for many readers. I am profoundly indebted to the support provided by all of those involved in the work. First and foremost I would like to acknowledge and thank the authors who worked hard and generously agreed to share their results and knowledge. Second I would like to express my gratitude to the Intech team that invited me to edit the book and give me their full support and a fruitful experience while working together to combine this book

Learning-Based Hardware Design for Data Acquisition Systems

This multidisciplinary research work aims to investigate the optimized information extraction from signals or data volumes and to develop tailored hardware implementations that trade-off the complexity of data acquisition with that of data processing, conceptually allowing radically new device designs. The mathematical results in classical Compressive Sampling (CS) support the paradigm of Analog-to-Information Conversion (AIC) as a replacement for conventional ADC technologies. The AICs simultaneously perform data acquisition and compression, seeking to directly sample signals for achieving specific tasks as opposed to acquiring a full signal only at the Nyquist rate to throw most of it away via compression. Our contention is that in order for CS to live up its name, both theory and practice must leverage concepts from learning. This work demonstrates our contention in hardware prototypes, with key trade-offs, for two different fields of application as edge and big-data computing. In the framework of edge-data computing, such as wearable and implantable ecosystems, the power budget is defined by the battery capacity, which generally limits the device performance and usability. This is more evident in very challenging field, such as medical monitoring, where high performance requirements are necessary for the device to process the information with high accuracy. Furthermore, in applications like implantable medical monitoring, the system performances have to merge the small area as well as the low-power requirements, in order to facilitate the implant bio-compatibility, avoiding the rejection from the human body. Based on our new mathematical foundations, we built different prototypes to get a neural signal acquisition chip that not only rigorously trades off its area, energy consumption, and the quality of its signal output, but also significantly outperforms the state-of-the-art in all aspects. In the framework of big-data and high-performance computation, such as in high-end servers application, the RF circuits meant to transmit data from chip-to-chip or chip-to-memory are defined by low power requirements, since the heat generated by the integrated circuits is partially distributed by the chip package. Hence, the overall system power budget is defined by its affordable cooling capacity. For this reason, application specific architectures and innovative techniques are used for low-power implementation. In this work, we have developed a single-ended multi-lane receiver for high speed I/O link in servers application. The receiver operates at 7 Gbps by learning inter-symbol interference and electromagnetic coupling noise in chip-to-chip communication systems. A learning-based approach allows a versatile receiver circuit which not only copes with large channel attenuation but also implements novel crosstalk reduction techniques, to allow single-ended multiple lines transmission, without sacrificing its overall bandwidth for a given area within the interconnect's data-path

Integrated Circuits for Programming Flash Memories in Portable Applications

Smart devices such as smart grids, smart home devices, etc. are infrastructure systems that connect the world around us more than before. These devices can communicate with each other and help us manage our environment. This concept is called the Internet of Things (IoT). Not many smart nodes exist that are both low-power and programmable. Floating-gate (FG) transistors could be used to create adaptive sensor nodes by providing programmable bias currents. FG transistors are mostly used in digital applications like Flash memories. However, FG transistors can be used in analog applications, too. Unfortunately, due to the expensive infrastructure required for programming these transistors, they have not been economical to be used in portable applications. In this work, we present low-power approaches to programming FG transistors which make them a good candidate to be employed in future wireless sensor nodes and portable systems. First, we focus on the design of low-power circuits which can be used in programming the FG transistors such as high-voltage charge pumps, low-drop-out regulators, and voltage reference cells. Then, to achieve the goal of reducing the power consumption in programmable sensor nodes and reducing the programming infrastructure, we present a method to program FG transistors using negative voltages. We also present charge-pump structures to generate the necessary negative voltages for programming in this new configuration

Microarchitectural Low-Power Design Techniques for Embedded Microprocessors

With the omnipresence of embedded processing in all forms of electronics today, there is a strong trend towards wireless, battery-powered, portable embedded systems which have to operate under stringent energy constraints. Consequently, low power consumption and high energy efficiency have emerged as the two key criteria for embedded microprocessor design. In this thesis we present a range of microarchitectural low-power design techniques which enable the increase of performance for embedded microprocessors and/or the reduction of energy consumption, e.g., through voltage scaling. In the context of cryptographic applications, we explore the effectiveness of instruction set extensions (ISEs) for a range of different cryptographic hash functions (SHA-3 candidates) on a 16-bit microcontroller architecture (PIC24). Specifically, we demonstrate the effectiveness of light-weight ISEs based on lookup table integration and microcoded instructions using finite state machines for operand and address generation. On-node processing in autonomous wireless sensor node devices requires deeply embedded cores with extremely low power consumption. To address this need, we present TamaRISC, a custom-designed ISA with a corresponding ultra-low-power microarchitecture implementation. The TamaRISC architecture is employed in conjunction with an ISE and standard cell memories to design a sub-threshold capable processor system targeted at compressed sensing applications. We furthermore employ TamaRISC in a hybrid SIMD/MIMD multi-core architecture targeted at moderate to high processing requirements (> 1 MOPS). A range of different microarchitectural techniques for efficient memory organization are presented. Specifically, we introduce a configurable data memory mapping technique for private and shared access, as well as instruction broadcast together with synchronized code execution based on checkpointing. We then study an inherent suboptimality due to the worst-case design principle in synchronous circuits, and introduce the concept of dynamic timing margins. We show that dynamic timing margins exist in microprocessor circuits, and that these margins are to a large extent state-dependent and that they are correlated to the sequences of instruction types which are executed within the processor pipeline. To perform this analysis we propose a circuit/processor characterization flow and tool called dynamic timing analysis. Moreover, this flow is employed in order to devise a high-level instruction set simulation environment for impact-evaluation of timing errors on application performance. The presented approach improves the state of the art significantly in terms of simulation accuracy through the use of statistical fault injection. The dynamic timing margins in microprocessors are then systematically exploited for throughput improvements or energy reductions via our proposed instruction-based dynamic clock adjustment (DCA) technique. To this end, we introduce a 6-stage 32-bit microprocessor with cycle-by-cycle DCA. Besides a comprehensive design flow and simulation environment for evaluation of the DCA approach, we additionally present a silicon prototype of a DCA-enabled OpenRISC microarchitecture fabricated in 28 nm FD-SOI CMOS. The test chip includes a suitable clock generation unit which allows for cycle-by-cycle DCA over a wide range with fine granularity at frequencies exceeding 1 GHz. Measurement results of speedups and power reductions are provided

Advances in Solid State Circuit Technologies

This book brings together contributions from experts in the fields to describe the current status of important topics in solid-state circuit technologies. It consists of 20 chapters which are grouped under the following categories: general information, circuits and devices, materials, and characterization techniques. These chapters have been written by renowned experts in the respective fields making this book valuable to the integrated circuits and materials science communities. It is intended for a diverse readership including electrical engineers and material scientists in the industry and academic institutions. Readers will be able to familiarize themselves with the latest technologies in the various fields

Product assurance technology for procuring reliable, radiation-hard, custom LSI/VLSI electronics

Advanced measurement methods using microelectronic test chips are described. These chips are intended to be used in acquiring the data needed to qualify Application Specific Integrated Circuits (ASIC's) for space use. Efforts were focused on developing the technology for obtaining custom IC's from CMOS/bulk silicon foundries. A series of test chips were developed: a parametric test strip, a fault chip, a set of reliability chips, and the CRRES (Combined Release and Radiation Effects Satellite) chip, a test circuit for monitoring space radiation effects. The technical accomplishments of the effort include: (1) development of a fault chip that contains a set of test structures used to evaluate the density of various process-induced defects; (2) development of new test structures and testing techniques for measuring gate-oxide capacitance, gate-overlap capacitance, and propagation delay; (3) development of a set of reliability chips that are used to evaluate failure mechanisms in CMOS/bulk: interconnect and contact electromigration and time-dependent dielectric breakdown; (4) development of MOSFET parameter extraction procedures for evaluating subthreshold characteristics; (5) evaluation of test chips and test strips on the second CRRES wafer run; (6) two dedicated fabrication runs for the CRRES chip flight parts; and (7) publication of two papers: one on the split-cross bridge resistor and another on asymmetrical SRAM (static random access memory) cells for single-event upset analysis