7 research outputs found

    Imperfection-Aware Design of CNFET Digital VLSI Circuits

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    Carbon nanotube field-effect transistor (CNFET) is one of the promising candidates as extensions to silicon CMOS devices. The CNFET, which is a 1-D structure with a near-ballistic transport capability, can potentially offer excellent device characteristics and order-of-magnitude better energy-delay product over standard CMOS devices. Significant challenges in CNT synthesis prevent CNFETs today from achieving such ideal benefits. CNT density variation and metallic CNTs are the dominant type of CNT variations/imperfections that cause performance variation, large static power consumption, and yield degradation. We present an imperfection-aware design technique for CNFET digital VLSI circuits by: 1) Analytical models that are developed to analyze and quantify the effects of CNT density variation on device characteristics, gate and system levels delays. The analytical models, which were validated by comparison to real experimental/simulation data, enables us to examine the space of CNFET combinational, sequential and memory cells circuits to minimize delay variations. Using these model, we drive CNFET processing and circuit design guidelines to manage/overcome CNT density variation. 2) Analytical models that are developed to analyze the effects of metallic CNTs on device characteristics, gate and system levels delay and power consumption. Using our presented analytical models, which are again validated by comparison with simulation data, it is shown that the static power dissipation is a more critical issue than the delay and the dynamic power of CNFET circuits in the presence of m-CNTs. 3) CNT density variation and metallic CNTs can result in functional failure of CNFET circuits. The complete and compact model for CNFET probability of failure that consider CNT density variation and m-CNTs is presented. This analytical model is applied to analyze the logical functional failures. The presented model is extended to predict opportunities and limitations of CNFET technology at todays Gigascale integration and beyond.\u2

    Building Efficient and Reliable Emerging Technology Systems

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    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

    A Holistic Solution for Reliability of 3D Parallel Systems

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    As device scaling slows down, emerging technologies such as 3D integration and carbon nanotube field-effect transistors are among the most promising solutions to increase device density and performance. These emerging technologies offer shorter interconnects, higher performance, and lower power. However, higher levels of operating temperatures and current densities project significantly higher failure rates. Moreover, due to the infancy of the manufacturing process, high variation, and defect densities, chip designers are not encouraged to consider these emerging technologies as a stand-alone replacement for Silicon-based transistors. The goal of this dissertation is to introduce new architectural and circuit techniques that can work around high-fault rates in the emerging 3D technologies, improving performance and reliability comparable to Silicon. We propose a new holistic approach to the reliability problem that addresses the necessary aspects of an effective solution such as detection, diagnosis, repair, and prevention synergically for a practical solution. By leveraging 3D fabric layouts, it proposes the underlying architecture to efficiently repair the system in the presence of faults. This thesis presents a fault detection scheme by re-executing instructions on idle identical units that distinguishes between transient and permanent faults while localizing it to the granularity of a pipeline stage. Furthermore, with the use of a dynamic and adaptive reconfiguration policy based on activity factors and temperature variation, we propose a framework that delivers a significant improvement in lifetime management to prevent faults due to aging. Finally, a design framework that can be used for large-scale chip production while mitigating yield and variation failures to bring up Carbon Nano Tube-based technology is presented. The proposed framework is capable of efficiently supporting high-variation technologies by providing protection against manufacturing defects at different granularities: module and pipeline-stage levels.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168118/1/javadb_1.pd

    Reliability-aware memory design using advanced reconfiguration mechanisms

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    Fast and Complex Data Memory systems has become a necessity in modern computational units in today's integrated circuits. These memory systems are integrated in form of large embedded memory for data manipulation and storage. This goal has been achieved by the aggressive scaling of transistor dimensions to few nanometer (nm) sizes, though; such a progress comes with a drawback, making it critical to obtain high yields of the chips. Process variability, due to manufacturing imperfections, along with temporal aging, mainly induced by higher electric fields and temperature, are two of the more significant threats that can no longer be ignored in nano-scale embedded memory circuits, and can have high impact on their robustness. Static Random Access Memory (SRAM) is one of the most used embedded memories; generally implemented with the smallest device dimensions and therefore its robustness can be highly important in nanometer domain design paradigm. Their reliable operation needs to be considered and achieved both in cell and also in architectural SRAM array design. Recently, and with the approach to near/below 10nm design generations, novel non-FET devices such as Memristors are attracting high attention as a possible candidate to replace the conventional memory technologies. In spite of their favorable characteristics such as being low power and highly scalable, they also suffer with reliability challenges, such as process variability and endurance degradation, which needs to be mitigated at device and architectural level. This thesis work tackles such problem of reliability concerns in memories by utilizing advanced reconfiguration techniques. In both SRAM arrays and Memristive crossbar memories novel reconfiguration strategies are considered and analyzed, which can extend the memory lifetime. These techniques include monitoring circuits to check the reliability status of the memory units, and architectural implementations in order to reconfigure the memory system to a more reliable configuration before a fail happens.Actualmente, el diseño de sistemas de memoria en circuitos integrados busca continuamente que sean más rápidos y complejos, lo cual se ha vuelto de gran necesidad para las unidades de computación modernas. Estos sistemas de memoria están integrados en forma de memoria embebida para una mejor manipulación de los datos y de su almacenamiento. Dicho objetivo ha sido conseguido gracias al agresivo escalado de las dimensiones del transistor, el cual está llegando a las dimensiones nanométricas. Ahora bien, tal progreso ha conllevado el inconveniente de una menor fiabilidad, dado que ha sido altamente difícil obtener elevados rendimientos de los chips. La variabilidad de proceso - debido a las imperfecciones de fabricación - junto con la degradación de los dispositivos - principalmente inducido por el elevado campo eléctrico y altas temperaturas - son dos de las más relevantes amenazas que no pueden ni deben ser ignoradas por más tiempo en los circuitos embebidos de memoria, echo que puede tener un elevado impacto en su robusteza final. Static Random Access Memory (SRAM) es una de las celdas de memoria más utilizadas en la actualidad. Generalmente, estas celdas son implementadas con las menores dimensiones de dispositivos, lo que conlleva que el estudio de su robusteza es de gran relevancia en el actual paradigma de diseño en el rango nanométrico. La fiabilidad de sus operaciones necesita ser considerada y conseguida tanto a nivel de celda de memoria como en el diseño de arquitecturas complejas basadas en celdas de memoria SRAM. Actualmente, con el diseño de sistemas basados en dispositivos de 10nm, dispositivos nuevos no-FET tales como los memristores están atrayendo una elevada atención como posibles candidatos para reemplazar las actuales tecnologías de memorias convencionales. A pesar de sus características favorables, tales como el bajo consumo como la alta escabilidad, ellos también padecen de relevantes retos de fiabilidad, como son la variabilidad de proceso y la degradación de la resistencia, la cual necesita ser mitigada tanto a nivel de dispositivo como a nivel arquitectural. Con todo esto, esta tesis doctoral afronta tales problemas de fiabilidad en memorias mediante la utilización de técnicas de reconfiguración avanzada. La consideración de nuevas estrategias de reconfiguración han resultado ser validas tanto para las memorias basadas en celdas SRAM como en `memristive crossbar¿, donde se ha observado una mejora significativa del tiempo de vida en ambos casos. Estas técnicas incluyen circuitos de monitorización para comprobar la fiabilidad de las unidades de memoria, y la implementación arquitectural con el objetivo de reconfigurar los sistemas de memoria hacia una configuración mucho más fiables antes de que el fallo suced

    Energy-Efficient Digital Circuit Design using Threshold Logic Gates

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    abstract: Improving energy efficiency has always been the prime objective of the custom and automated digital circuit design techniques. As a result, a multitude of methods to reduce power without sacrificing performance have been proposed. However, as the field of design automation has matured over the last few decades, there have been no new automated design techniques, that can provide considerable improvements in circuit power, leakage and area. Although emerging nano-devices are expected to replace the existing MOSFET devices, they are far from being as mature as semiconductor devices and their full potential and promises are many years away from being practical. The research described in this dissertation consists of four main parts. First is a new circuit architecture of a differential threshold logic flipflop called PNAND. The PNAND gate is an edge-triggered multi-input sequential cell whose next state function is a threshold function of its inputs. Second a new approach, called hybridization, that replaces flipflops and parts of their logic cones with PNAND cells is described. The resulting \hybrid circuit, which consists of conventional logic cells and PNANDs, is shown to have significantly less power consumption, smaller area, less standby power and less power variation. Third, a new architecture of a field programmable array, called field programmable threshold logic array (FPTLA), in which the standard lookup table (LUT) is replaced by a PNAND is described. The FPTLA is shown to have as much as 50% lower energy-delay product compared to conventional FPGA using well known FPGA modeling tool called VPR. Fourth, a novel clock skewing technique that makes use of the completion detection feature of the differential mode flipflops is described. This clock skewing method improves the area and power of the ASIC circuits by increasing slack on timing paths. An additional advantage of this method is the elimination of hold time violation on given short paths. Several circuit design methodologies such as retiming and asynchronous circuit design can use the proposed threshold logic gate effectively. Therefore, the use of threshold logic flipflops in conventional design methodologies opens new avenues of research towards more energy-efficient circuits.Dissertation/ThesisDoctoral Dissertation Computer Science 201

    Cost-Efficient Soft-Error Resiliency for ASIP-based Embedded Systems

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    Recent decades have witnessed the rapid growth of embedded systems. At present, embedded systems are widely applied in a broad range of critical applications including automotive electronics, telecommunication, healthcare, industrial electronics, consumer electronics military and aerospace. Human society will continue to be greatly transformed by the pervasive deployment of embedded systems. Consequently, substantial amount of efforts from both industry and academic communities have contributed to the research and development of embedded systems. Application-specific instruction-set processor (ASIP) is one of the key advances in embedded processor technology, and a crucial component in some embedded systems. Soft errors have been directly observed since the 1970s. As devices scale, the exponential increase in the integration of computing systems occurs, which leads to correspondingly decrease in the reliability of computing systems. Today, major research forums state that soft errors are one of the major design technology challenges at and beyond the 22 nm technology node. Therefore, a large number of soft-error solutions, including error detection and recovery, have been proposed from differing perspectives. Nonetheless, most of the existing solutions are designed for general or high-performance systems which are different to embedded systems. For embedded systems, the soft-error solutions must be cost-efficient, which requires the tailoring of the processor architecture with respect to the feature of the target application. This thesis embodies a series of explorations for cost-efficient soft-error solutions for ASIP-based embedded systems. In this exploration, five major solutions are proposed. The first proposed solution realizes checkpoint recovery in ASIPs. By generating customized instructions, ASIP-implemented checkpoint recovery can perform at a finer granularity than what was previously possible. The fault-free performance overhead of this solution is only 1.45% on average. The recovery delay is only 62 cycles at the worst case. The area and leakage power overheads are 44.4% and 45.6% on average. The second solution explores utilizing two primitive error recovery techniques jointly. This solution includes three application-specific optimization methodologies. This solution generates the optimized error-resilient ASIPs, based on the characteristics of primitive error recovery techniques, static reliability analysis and design constraints. The resultant ASIP can be configured to perform at runtime according to the optimized recovery scheme. This solution can strategically enhance cost-efficiency for error recovery. In order to guarantee cost-efficiency in unpredictable runtime situations, the third solution explores runtime adaptation for error recovery. This solution aims to budget and adapt the error recovery operations, so as to spend the resources intelligently and to tolerate adverse influences of runtime variations. The resultant ASIP can make runtime decisions to determine the activation of spatial and temporal redundancies, according to the runtime situations. At the best case, this solution can achieve almost 50x reliability gain over the state of the art solutions. Given the increasing demand for multi-core computing systems, the last two proposed solutions target error recovery in multi-core ASIPs. The first solution of these two explores ASIP-implemented fine-grained process migration. This solution is a key infrastructure, which allows cost-efficient task management, for realizing cost-efficient soft-error recovery in multi-core ASIPs. The average time cost is only 289 machine cycles to perform process migration. The last solution explores using dynamic and adaptive mapping to assign heterogeneous recovery operations to the tasks in the multi-core context. This solution allows each individual ASIP-based processing core to dynamically adapt its specific error recovery functionality according to the corresponding task's characteristics, in terms of soft error vulnerability and execution time deadline. This solution can significantly improve the reliability of the system by almost two times, with graceful constraint penalty, in comparison to the state-of-the-art counterparts

    Circuit-level modelling and simulation of carbon nanotube devices

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    The growing academic interest in carbon nanotubes (CNTs) as a promising novel class of electronic materials has led to significant progress in the understanding of CNT physics including ballistic and non-ballistic electron transport characteristics. Together with the increasing amount of theoretical analysis and experimental studies into the properties of CNT transistors, the need for corresponding modelling techniques has also grown rapidly. This research is focused on the electron transport characteristics of CNT transistors, with the aim to develop efficient techniquesto model and simulate CNT devices for logic circuit analysis.The contributions of this research can be summarised as follows. Firstly, to accelerate the evaluation of the equations that model a CNT transistor, while maintaining high modelling accuracy, three efficient numerical techniques based on piece-wise linear, quadratic polynomial and cubic spline approximation have been developed. The numerical approximation simplifies the solution of the CNT transistor’s self-consistent voltage such that the calculation of the drain-source current is accelerated by at least two orders of magnitude. The numerical approach eliminates complicated calculations in the modelling process and facilitates the development of fast and efficient CNT transistor models for circuit simulation.Secondly, non-ballistic CNT transistors have been considered, and extended circuit-level models which can capture both ballistic and non-ballistic electron transport phenomena, including elastic scattering, phonon scattering, strain and tunnelling effects, have been developed. A salient feature of the developed models is their ability to incorporate both ballistic and non-ballistic transport mechanisms without a significant computational cost. The developed models have been extensively validated against reported transport theories of CNT transistors and experimental results.Thirdly, the proposed carbon nanotube transistor models have been implemented on several platforms. The underlying algorithms have been developed and tested in MATLAB, behaviourallevel models in VHDL-AMS, and improved circuit-level models have been implemented in two versions of the SPICE simulator. As the final contribution of this work, parameter variation analysis has been carried out in SPICE3 to study the performance of the proposed circuit-level CNT transistor models in logic circuit analysis. Typical circuits, including inverters and adders, have been analysed to determine the dependence of the circuit’s correct operation on CNT parameter variation
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