High-Performance Ternary (4:2) Compressor Based on Capacitive Threshold Logic

This paper presents a ternary (4:2) compressor, which is an important component in multiplication. However, the structure differs from the binary counterpart since the ternary model does not require carry signals. The method of capacitive threshold logic (CTL) is used to achieve the output signals directly. Unlike the previously presented similar structure, the entire capacitor network is divided into two parts. This segregation results in higher reliability and robustness against unwanted process, voltage, and temperature (PVT) variations. Simulations are performed by HSPICE and 32nm CNFET technology. Simulation results demonstrate about 94% higher performance in terms of power-delay product (PDP) for the new design over the previous one

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”

Characterization and mitigation of process variation in digital circuits and systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 155-166).Process variation threatens to negate a whole generation of scaling in advanced process technologies due to performance and power spreads of greater than 30-50%. Mitigating this impact requires a thorough understanding of the variation sources, magnitudes and spatial components at the device, circuit and architectural levels. This thesis explores the impacts of variation at each of these levels and evaluates techniques to alleviate them in the context of digital circuits and systems. At the device level, we propose isolation and measurement of variation in the intrinsic threshold voltage of a MOSFET using sub-threshold leakage currents. Analysis of the measured data, from a test-chip implemented on a 0. 18[mu]m CMOS process, indicates that variation in MOSFET threshold voltage is a truly random process dependent only on device dimensions. Further decomposition of the observed variation reveals no systematic within-die variation components nor any spatial correlation. A second test-chip capable of characterizing spatial variation in digital circuits is developed and implemented in a 90nm triple-well CMOS process. Measured variation results show that the within-die component of variation is small at high voltages but is an increasing fraction of the total variation as power-supply voltage decreases. Once again, the data shows no evidence of within-die spatial correlation and only weak systematic components. Evaluation of adaptive body-biasing and voltage scaling as variation mitigation techniques proves voltage scaling is more effective in performance modification with reduced impact to idle power compared to body-biasing.(cont.) Finally, the addition of power-supply voltages in a massively parallel multicore processor is explored to reduce the energy required to cope with process variation. An analytic optimization framework is developed and analyzed; using a custom simulation methodology, total energy of a hypothetical 1K-core processor based on the RAW core is reduced by 6-16% with the addition of only a single voltage. Analysis of yield versus required energy demonstrates that a combination of disabling poor-performing cores and additional power-supply voltages results in an optimal trade-off between performance and energy.by Nigel Anthony Drego.Ph.D

A Novel Ultra Low-Power 10T CNFET-Based Full Adder Cell Design in 32nm Technology

Nowadays, energy consumption is the main concern in portable electronic systems such as laptops, smart mobile phones, personal digital assistances (PDAs) and so forth. Considering that the 1-bit Full adder cell has been the determinant circuit due to its wide usage in these systems, it affects the entire performance of the electronic system. In this paper, a novel low-power and low-energy 10 transistor (10T) Full Adder cell using NAND/NOR functions based on carbon nanotube field effect transistors (CNFETs) is presented. The proposed cell showed superiority in terms of power-delay product (PDP) compared to the other cells under different simulation condition, such as power supply, temperature, load and operating frequency variations. Moreover, a Monte Carlo (MC) simulation was conducted to study the reliability of the proposed cell against manufacturing process variations (i.e. the variations of diameters of carbon nanotubes). Simulations confirmed the robustness of the proposed cell

Low power predictable memory and processing architectures

Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

Energy efficient hybrid computing systems using spin devices

Emerging spin-devices like magnetic tunnel junctions (MTJ\u27s), spin-valves and domain wall magnets (DWM) have opened new avenues for spin-based logic design. This work explored potential computing applications which can exploit such devices for higher energy-efficiency and performance. The proposed applications involve hybrid design schemes, where charge-based devices supplement the spin-devices, to gain large benefits at the system level. As an example, lateral spin valves (LSV) involve switching of nanomagnets using spin-polarized current injection through a metallic channel such as Cu. Such spin-torque based devices possess several interesting properties that can be exploited for ultra-low power computation. Analog characteristic of spin current facilitate non-Boolean computation like majority evaluation that can be used to model a neuron. The magneto-metallic neurons can operate at ultra-low terminal voltage of ∼20mV, thereby resulting in small computation power. Moreover, since nano-magnets inherently act as memory elements, these devices can facilitate integration of logic and memory in interesting ways. The spin based neurons can be integrated with CMOS and other emerging devices leading to different classes of neuromorphic/non-Von-Neumann architectures. The spin-based designs involve `mixed-mode\u27 processing and hence can provide very compact and ultra-low energy solutions for complex computation blocks, both digital as well as analog. Such low-power, hybrid designs can be suitable for various data processing applications like cognitive computing, associative memory, and currentmode on-chip global interconnects. Simulation results for these applications based on device-circuit co-simulation framework predict more than ∼100x improvement in computation energy as compared to state of the art CMOS design, for optimal spin-device parameters

An Ultra-Low-Power 75mV 64-Bit Current-Mode Majority-Function Adder

Ultra-low-power circuits are becoming more desirable due to growing portable device markets and they are also becoming more interesting and applicable today in biomedical, pharmacy and sensor networking applications because of the nano-metric scaling and CMOS reliability improvements. In this thesis, three main achievements are presented in ultra-low-power adders. First, a new majority function algorithm for carry and the sum generation is presented. Then with this algorithm and implied new architecture, we achieved a circuit with 75mV supply voltage operation. Last but not least, a 64 bit current-mode majority-function adder based on the new architecture and algorithm is successfully tested at 75mV supply voltage. The circuit consumed 4.5nW or 3.8pJ in one of the worst conditions

Building Efficient and Reliable Emerging Technology Systems

The semiconductor industry has been reaping the benefits of Moore’s law powered by Dennard’s voltage scaling for the past fifty years. However, with the end of Dennard scaling, silicon chip manufacturers are facing a widespread plateau in performance improvements. While the architecture community has focused its effort on exploring parallelism, such as with multi-core, many-core and accelerator-based systems, chip manufacturers have been forced to explore beyond-Moore technologies to improve performance while maintaining power density. Examples of such technologies include monolithic 3D integration, carbon nanotube transistors, tunneling-based transistors, spintronics and quantum computing. However, the infancy of the manufacturing process of these new technologies impedes their usage in commercial products. The goal of this dissertation is to combine both architectural and device-level efforts to provide solutions across the computing stack that can overcome the reliability concerns of emerging technologies. This allows for beyond-Moore systems to compete with highly optimized silicon-based processors, thus, enabling faster commercialization of such systems. This dissertation proposes the following key steps: (i) Multifaceted understanding and modeling of variation and yield issues that occur in emerging technologies, such as carbon nanotube transistors (CNFETs). (ii) Design of systems using suitable logic families such as pass transistor logic that provide high performance. (iii) Design of a multi-granular fault-tolerant reconfigurable architecture that enhances yield and performance. (iv) Design of a multi-technology, multi-accelerator heterogeneous system (v) Development of real-time constrained efficient workload scheduling mechanism for heterogeneous systems. This dissertation first presents the use of pass transistor logic family as an alternate to the CMOS logic family for CNFETs to improve performance. It explores various architectural design choices for CNFETs using pass transistor logic (PTL) to create an energy-efficient RISC-V processor. Our results show that while a CNFET RISC-V processor using CMOS logic achieves a 2.9x energy-delay product (EDP) improvement over a silicon design, using PTL along the critical path components of the processor can boost EDP improvement by 5x as well as reduce area by 17% over 16 nm silicon CMOS. This document further builds on providing fault-tolerant and yield enhancing solutions for emerging 3D integration compatible technologies in the context of CNFETs. The proposed framework can efficiently support high-variation technologies by providing protection against manufacturing defects at multiple granularities: module and pipeline-stage levels. Based on the variation observed in a synthesized design, a reliable CNFET-based 3D multi-granular reconfigurable architecture, 3DTUBE, is presented to overcome the manufacturing difficulties. For 0.4-0.7 V, 3DTUBE provides up to 6.0x higher throughput and 3.1x lower EDP compared to a silicon-based multi-core design evaluated at 1 part per billion transistor failure rate, which is 10,000x lower in comparison to CNFET’s failure rate. This dissertation then ventures into building multi-accelerator heterogeneous systems and real-time schedulers that cater to the requirements of the applications while taking advantage of the underlying heterogeneous system. We introduce optimizations like task pruning, hierarchical hetero-ranking and rank update built upon two scheduler policies (MS-static and MS-dynamic), that result in a performance improvement of 3.5x (average) for real-world autonomous vehicle applications, when compared against state-of-the-art schedulers. Adopting insights from the above work, this thesis presents a multi-accelerator, multi-technology heterogeneous system powered by a multi-constrained scheduler that optimizes for varying task requirements to achieve up to 6.1x better energy over a baseline silicon-based system.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169699/1/aporvaa_1.pd