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

High Peformance and Low Power On-Die Interconnect Fabrics.

Increasing power density with technology scaling has caused stagnation in operating frequency of modern day microprocessors. This has led designers to prefer multicore architectures over complex monolithic processors to keep up with the demand for rising computing throughput. Although processing units are getting smaller and simpler, the dramatic rise of their count on a single die has made the fabric that connects these processing units increasingly complex. These interconnect fabrics have become a bottleneck in improving overall system effciency. As a result, the design paradigm for multi-core chips is gradually shifting from a core-centric architecture towards an interconnect-centric architecture, where system efficiency is limited by the fabric rather than the processing ability of any individual core. This dissertation introduces three novel and synergistic circuit techniques to improve scalability of switch fabrics to make on-die integration of hundreds to thousands of cores feasible. 1) A matrix topology is proposed for designing a fully connected switch fabric that re-uses output buses for programming, and stores shue congurations at cross points. This significantly reduces routing congestion, lowers area/power, and improves per- formance. Silicon measurements demonstrate 47% energy savings in a 64-lane SIMD processor fabricated in 65nm CMOS over a conventional implementation. 2) A novel approach to handle high radix arbitration along with data routing is proposed. It optimally uses existing cross-bar interconnect resources without requiring any additional overhead. Bandwidth exceeding 2Tb/s is recorded in a test prototype fabricated in 65nm. 3) Building on the later, a new circuit topology to manage and update priority adaptively within the switch fabric without incurring additional delay or area is then proposed. Several assist circuit techniques, such as a thyristor based sense amplifier and self regenerating bi-directional repeaters are proposed for high speed energy efficient signaling to and from the switch fabric to improve overall routing efficiency. Using these techniques a 64 x 64 switch fabric with 128b data bus fabricated in 45nm achieves a throughput of 4.5Tb/s at single cycle latency while operating at 559MHz.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91506/1/sudhirks_1.pd

X-SRAM: Enabling In-Memory Boolean Computations in CMOS Static Random Access Memories

Silicon-based Static Random Access Memories (SRAM) and digital Boolean logic have been the workhorse of the state-of-art computing platforms. Despite tremendous strides in scaling the ubiquitous metal-oxide-semiconductor transistor, the underlying \textit{von-Neumann} computing architecture has remained unchanged. The limited throughput and energy-efficiency of the state-of-art computing systems, to a large extent, results from the well-known \textit{von-Neumann bottleneck}. The energy and throughput inefficiency of the von-Neumann machines have been accentuated in recent times due to the present emphasis on data-intensive applications like artificial intelligence, machine learning \textit{etc}. A possible approach towards mitigating the overhead associated with the von-Neumann bottleneck is to enable \textit{in-memory} Boolean computations. In this manuscript, we present an augmented version of the conventional SRAM bit-cells, called \textit{the X-SRAM}, with the ability to perform in-memory, vector Boolean computations, in addition to the usual memory storage operations. We propose at least six different schemes for enabling in-memory vector computations including NAND, NOR, IMP (implication), XOR logic gates with respect to different bit-cell topologies $-$ the 8T cell and the 8$^+$T Differential cell. In addition, we also present a novel \textit{`read-compute-store'} scheme, wherein the computed Boolean function can be directly stored in the memory without the need of latching the data and carrying out a subsequent write operation. The feasibility of the proposed schemes has been verified using predictive transistor models and Monte-Carlo variation analysis.Comment: This article has been accepted in a future issue of IEEE Transactions on Circuits and Systems-I: Regular Paper

Robust low-power digital circuit design in nano-CMOS technologies

Device scaling has resulted in large scale integrated, high performance, low-power, and low cost systems. However the move towards sub-100 nm technology nodes has increased variability in device characteristics due to large process variations. Variability has severe implications on digital circuit design by causing timing uncertainties in combinational circuits, degrading yield and reliability of memory elements, and increasing power density due to slow scaling of supply voltage. Conventional design methods add large pessimistic safety margins to mitigate increased variability, however, they incur large power and performance loss as the combination of worst cases occurs very rarely. In-situ monitoring of timing failures provides an opportunity to dynamically tune safety margins in proportion to on-chip variability that can significantly minimize power and performance losses. We demonstrated by simulations two delay sensor designs to detect timing failures in advance that can be coupled with different compensation techniques such as voltage scaling, body biasing, or frequency scaling to avoid actual timing failures. Our simulation results using 45 nm and 32 nm technology BSIM4 models indicate significant reduction in total power consumption under temperature and statistical variations. Future work involves using dual sensing to avoid useless voltage scaling that incurs a speed loss. SRAM cache is the first victim of increased process variations that requires handcrafted design to meet area, power, and performance requirements. We have proposed novel 6 transistors (6T), 7 transistors (7T), and 8 transistors (8T)-SRAM cells that enable variability tolerant and low-power SRAM cache designs. Increased sense-amplifier offset voltage due to device mismatch arising from high variability increases delay and power consumption of SRAM design. We have proposed two novel design techniques to reduce offset voltage dependent delays providing a high speed low-power SRAM design. Increasing leakage currents in nano-CMOS technologies pose a major challenge to a low-power reliable design. We have investigated novel segmented supply voltage architecture to reduce leakage power of the SRAM caches since they occupy bulk of the total chip area and power. Future work involves developing leakage reduction methods for the combination logic designs including SRAM peripherals

Temperature Variation Operation of Mixed-VT 3T GC-eDRAM for Low Power Applications in 2Kbit Memory Array

Embedded memories were once utilized to transfer information between the CPU and the main memory. The cache storage in most traditional computers was static-random-access-memory (SRAM). Other memory technologies, such as embedded dynamic random-access memory (eDRAM) and spin-transfer-torque random-access memory (STT-RAM), have also been used to store cache data. The SRAM, on the other hand, has a low density and severe leakage issues, and the STT-RAM has high latency and energy consumption when writing. The gain-cell eDRAM (GC-eDRAM), which has a higher density, lower leakage, logic compatibility, and is appropriate for two-port operations, is an attractive option. To speed up data retrieval from the main memory, future processors will require larger and faster-embedded memories. Area overhead, power overhead, and speed performance are all issues with the existing architecture. A unique mixed-V_T 3T GC-eDRAM architecture is suggested in this paper to improve data retention times (DRT) and performance for better energy efficiency in embedded memories. The GC-eDRAM is simulated using a standard complementary-metal-oxide-semiconductor (CMOS) with a 130nm technology node transistor. The performance of a 2kbit mixed-V_T 3T GC-eDRAM array were evaluated through corner process simulations. Each memory block is designed and simulated using Mentor Graphics Software. The array, which is based on the suggested bit-cell, has been successfully operated at 400Mhz under a 1V supply and takes up almost 60-75% less space than 6T SRAM using the same technology. When compared to the existing 6T and 4T ULP SRAMs (others' work), the retention power of the proposed GC-eDRAM is around 80-90% lower

Ultra Low Power Digital Circuit Design for Wireless Sensor Network Applications

Ny forskning innenfor feltet trådløse sensornettverk åpner for nye og innovative produkter og løsninger. Biomedisinske anvendelser er blant områdene med størst potensial og det investeres i dag betydelige beløp for å bruke denne teknologien for å gjøre medisinsk diagnostikk mer effektiv samtidig som man åpner for fjerndiagnostikk basert på trådløse sensornoder integrert i et ”helsenett”. Målet er å forbedre tjenestekvalitet og redusere kostnader samtidig som brukerne skal oppleve forbedret livskvalitet som følge av økt trygghet og mulighet for å tilbringe mest mulig tid i eget hjem og unngå unødvendige sykehusbesøk og innleggelser. For å gjøre dette til en realitet er man avhengige av sensorelektronikk som bruker minst mulig energi slik at man oppnår tilstrekkelig batterilevetid selv med veldig små batterier. I sin avhandling ” Ultra Low power Digital Circuit Design for Wireless Sensor Network Applications” har PhD-kandidat Farshad Moradi fokusert på nye løsninger innenfor konstruksjon av energigjerrig digital kretselektronikk. Avhandlingen presenterer nye løsninger både innenfor aritmetiske og kombinatoriske kretser, samtidig som den studerer nye statiske minneelementer (SRAM) og alternative minnearkitekturer. Den ser også på utfordringene som oppstår når silisiumteknologien nedskaleres i takt med mikroprosessorutviklingen og foreslår løsninger som bidrar til å gjøre kretsløsninger mer robuste og skalerbare i forhold til denne utviklingen. De viktigste konklusjonene av arbeidet er at man ved å introdusere nye konstruksjonsteknikker både er i stand til å redusere energiforbruket samtidig som robusthet og teknologiskalerbarhet øker. Forskningen har vært utført i samarbeid med Purdue University og vært finansiert av Norges Forskningsråd gjennom FRINATprosjektet ”Micropower Sensor Interface in Nanometer CMOS Technology”

SRAM Compiler For Automated Memory Layout Supporting Multiple Transistor Process Technologies

This research details the design of an SRAM compiler for quickly creating SRAM blocks for Cal Poly integrated circuit (IC) designs. The compiler generates memory for two process technologies (IBM 180nm cmrf7sf and ON Semiconductor 600nm SCMOS) and requires a minimum number of specifications from the user for ease of use, while still offering the option to customize the performance for speed or area of the generated SRAM cell. By automatically creating SRAM arrays, the compiler saves the user time from having to layout and test memory and allows for quick updates and changes to a design. Memory compilers with various features already exist, but they have several disadvantages. Most memory compilers are expensive, usually only generate memory for one process technology, and don’t allow for user-defined custom SRAM cell optimizations. This free design makes it available for students and institutions that would not be able to afford an industry-made compiler. A compiler that offers multiple process technologies allows for more freedom to design in other processes if needed or desired. An attempt was made for this design to be modular for different process technologies so new processes could be added with ease; however, different process technologies have different DRC rules, making that option very difficult to attain. A customizable SRAM cell based on transistor sizing ratios allows for optimized designs in speed, area, or power, and for academic research. Even for an experienced designer, the layout of a single SRAM cell (1 bit) can take an hour. This command-line-based tool can draw a 1Kb SRAM block in seconds and a 1Mb SRAM block in about 15 minutes. In addition, this compiler also adds a manually laid out precharge circuit to each of the SRAM columns for an enhanced read operation by ensuring the bit lines have valid logic output values. Finally, an analysis on SRAM cell stability is done for creating a robust cell as the default design for the compiler. The default cell design is verified for stability during read and write operations, and has an area of 14.067 µm2 for the cmrf7sf process and 246.42 µm2 for the SCMOS process. All factors considered, this SRAM compiler design overcomes several of the drawbacks of other existing memory compilers

A PUF based Lightweight Hardware Security Architecture for IoT

With an increasing number of hand-held electronics, gadgets, and other smart devices, data is present in a large number of platforms, thereby increasing the risk of security, privacy, and safety breach than ever before. Due to the extreme lightweight nature of these devices, commonly referred to as IoT or `Internet of Things\u27, providing any kind of security is prohibitive due to high overhead associated with any traditional and mathematically robust cryptographic techniques. Therefore, researchers have searched for alternative intuitive solutions for such devices. Hardware security, unlike traditional cryptography, can provide unique device-specific security solutions with little overhead, address vulnerability in hardware and, therefore, are attractive in this domain. As Moore\u27s law is almost at its end, different emerging devices are being explored more by researchers as they present opportunities to build better application-specific devices along with their challenges compared to CMOS technology. In this work, we have proposed emerging nanotechnology-based hardware security as a security solution for resource constrained IoT domain. Specifically, we have built two hardware security primitives i.e. physical unclonable function (PUF) and true random number generator (TRNG) and used these components as part of a security protocol proposed in this work as well. Both PUF and TRNG are built from metal-oxide memristors, an emerging nanoscale device and are generally lightweight compared to their CMOS counterparts in terms of area, power, and delay. Design challenges associated with designing these hardware security primitives and with memristive devices are properly addressed. Finally, a complete security protocol is proposed where all of these different pieces come together to provide a practical, robust, and device-specific security for resource-limited IoT systems