Stochastic-Based Computing with Emerging Spin-Based Device Technologies

In this dissertation, analog and emerging device physics is explored to provide a technology platform to design new bio-inspired system and novel architecture. With CMOS approaching the nano-scaling, their physics limits in feature size. Therefore, their physical device characteristics will pose severe challenges to constructing robust digital circuitry. Unlike transistor defects due to fabrication imperfection, quantum-related switching uncertainties will seriously increase their susceptibility to noise, thus rendering the traditional thinking and logic design techniques inadequate. Therefore, the trend of current research objectives is to create a non-Boolean high-level computational model and map it directly to the unique operational properties of new, power efficient, nanoscale devices. The focus of this research is based on two-fold: 1) Investigation of the physical hysteresis switching behaviors of domain wall device. We analyze phenomenon of domain wall device and identify hysteresis behavior with current range. We proposed the Domain-Wall-Motion-based (DWM) NCL circuit that achieves approximately 30x and 8x improvements in energy efficiency and chip layout area, respectively, over its equivalent CMOS design, while maintaining similar delay performance for a one bit full adder. 2) Investigation of the physical stochastic switching behaviors of Mag- netic Tunnel Junction (MTJ) device. With analyzing of stochastic switching behaviors of MTJ, we proposed an innovative stochastic-based architecture for implementing artificial neural network (S-ANN) with both magnetic tunneling junction (MTJ) and domain wall motion (DWM) devices, which enables efficient computing at an ultra-low voltage. For a well-known pattern recognition task, our mixed-model HSPICE simulation results have shown that a 34-neuron S-ANN implementation, when compared with its deterministic-based ANN counterparts implemented with digital and analog CMOS circuits, achieves more than 1.5 ~ 2 orders of magnitude lower energy consumption and 2 ~ 2.5 orders of magnitude less hidden layer chip area

Développement de circuits logiques programmables résistants aux alas logiques en technologie CMOS submicrométrique

The electronics associated to the particle detectors of the Large Hadron Collider (LHC), under construction at CERN, will operate in a very harsh radiation environment. Most of the microelectronics components developed for the first generation of LHC experiments have been designed with very precise experiment-specific goals and are hardly adaptable to other applications. Commercial Off-The-Shelf (COTS) components cannot be used in the vicinity of particle collision due to their poor radiation tolerance. This thesis is a contribution to the effort to cover the need for radiation-tolerant SEU-robust programmable components for application in High Energy Physics (HEP) experiments. Two components are under development: a Programmable Logic Device (PLD) and a Field-Programmable Gate Array (FPGA). The PLD is a fuse-based, 10-input, 8-I/O general architecture device in 0.25 micron CMOS technology. The FPGA under development is instead a 32x32 logic block array, equivalent to ~25k gates, in 0.13 micron CMOS. This work focussed also on the research for an SEU-robust register in both the mentioned technologies. The SEU-robust register is employed as a user data flip-flop in the FPGA and PLD designs and as a configuration cell as well in the FPGA design

Introduction to Logic Circuits & Logic Design with Verilog

The overall goal of this book is to fill a void that has appeared in the instruction of digital circuits over the past decade due to the rapid abstraction of system design. Up until the mid-1980s, digital circuits were designed using classical techniques. Classical techniques relied heavily on manual design practices for the synthesis, minimization, and interfacing of digital systems. Corresponding to this design style, academic textbooks were developed that taught classical digital design techniques. Around 1990, large-scale digital systems began being designed using hardware description languages (HDL) and automated synthesis tools. Broad-scale adoption of this modern design approach spread through the industry during this decade. Around 2000, hardware description languages and the modern digital design approach began to be taught in universities, mainly at the senior and graduate level. There were a variety of reasons that the modern digital design approach did not penetrate the lower levels of academia during this time. First, the design and simulation tools were difficult to use and overwhelmed freshman and sophomore students. Second, the ability to implement the designs in a laboratory setting was infeasible. The modern design tools at the time were targeted at custom integrated circuits, which are cost- and time-prohibitive to implement in a university setting. Between 2000 and 2005, rapid advances in programmable logic and design tools allowed the modern digital design approach to be implemented in a university setting, even in lower-level courses. This allowed students to learn the modern design approach based on HDLs and prototype their designs in real hardware, mainly fieldprogrammable gate arrays (FPGAs). This spurred an abundance of textbooks to be authored, teaching hardware description languages and higher levels of design abstraction. This trend has continued until today. While abstraction is a critical tool for engineering design, the rapid movement toward teaching only the modern digital design techniques has left a void for freshman- and sophomore-level courses in digital circuitry. Legacy textbooks that teach the classical design approach are outdated and do not contain sufficient coverage of HDLs to prepare the students for follow-on classes. Newer textbooks that teach the modern digital design approach move immediately into high-level behavioral modeling with minimal or no coverage of the underlying hardware used to implement the systems. As a result, students are not being provided the resources to understand the fundamental hardware theory that lies beneath the modern abstraction such as interfacing, gate-level implementation, and technology optimization. Students moving too rapidly into high levels of abstraction have little understanding of what is going on when they click the “compile and synthesize” button of their design tool. This leads to graduates who can model a breadth of different systems in an HDL but have no depth into how the system is implemented in hardware. This becomes problematic when an issue arises in a real design and there is no foundational knowledge for the students to fall back on in order to debug the problem

Introduction to Logic Circuits & Logic Design with VHDL

The overall goal of this book is to fill a void that has appeared in the instruction of digital circuits over the past decade due to the rapid abstraction of system design. Up until the mid-1980s, digital circuits were designed using classical techniques. Classical techniques relied heavily on manual design practices for the synthesis, minimization, and interfacing of digital systems. Corresponding to this design style, academic textbooks were developed that taught classical digital design techniques. Around 1990, large-scale digital systems began being designed using hardware description languages (HDL) and automated synthesis tools. Broad-scale adoption of this modern design approach spread through the industry during this decade. Around 2000, hardware description languages and the modern digital design approach began to be taught in universities, mainly at the senior and graduate level. There were a variety of reasons that the modern digital design approach did not penetrate the lower levels of academia during this time. First, the design and simulation tools were difficult to use and overwhelmed freshman and sophomore students. Second, the ability to implement the designs in a laboratory setting was infeasible. The modern design tools at the time were targeted at custom integrated circuits, which are cost- and time-prohibitive to implement in a university setting. Between 2000 and 2005, rapid advances in programmable logic and design tools allowed the modern digital design approach to be implemented in a university setting, even in lower-level courses. This allowed students to learn the modern design approach based on HDLs and prototype their designs in real hardware, mainly field programmable gate arrays (FPGAs). This spurred an abundance of textbooks to be authored teaching hardware description languages and higher levels of design abstraction. This trend has continued until today. While abstraction is a critical tool for engineering design, the rapid movement toward teaching only the modern digital design techniques has left a void for freshman- and sophomore-level courses in digital circuitry. Legacy textbooks that teach the classical design approach are outdated and do not contain sufficient coverage of HDLs to prepare the students for follow-on classes. Newer textbooks that teach the modern digital design approach move immediately into high-level behavioral modeling with minimal or no coverage of the underlying hardware used to implement the systems. As a result, students are not being provided the resources to understand the fundamental hardware theory that lies beneath the modern abstraction such as interfacing, gate-level implementation, and technology optimization. Students moving too rapidly into high levels of abstraction have little understanding of what is going on when they click the “compile and synthesize” button of their design tool. This leads to graduates who can model a breadth of different systems in an HDL but have no depth into how the system is implemented in hardware. This becomes problematic when an issue arises in a real design and there is no foundational knowledge for the students to fall back on in order to debug the problem

Self-healing concepts involving fine-grained redundancy for electronic systems

The start of the digital revolution came through the metal-oxide-semiconductor field-effect transistor (MOSFET) in 1959 followed by massive integration onto a silicon die by means of constant down scaling of individual components. Digital systems for certain applications require fault-tolerance against faults caused by temporary or permanent influence. The most widely used technique is triple module redundancy (TMR) in conjunction with a majority voter, which is regarded as a passive fault mitigation strategy. Design by functional resilience has been applied to circuit structures for increased fault-tolerance and towards self-diagnostic triggered self-healing. The focus of this thesis is therefore to develop new design strategies for fault detection and mitigation within transistor, gate and cell design levels. The research described in this thesis makes three contributions. The first contribution is based on adding fine-grained transistor level redundancy to logic gates in order to accomplish stuck-at fault-tolerance. The objective is to realise maximum fault-masking for a logic gate with minimal added redundant transistors. In the case of non-maskable stuck-at faults, the gate structure generates an intrinsic indication signal that is suitable for autonomous self-healing functions. As a result, logic circuitry utilising this design is now able to differentiate between gate faults and faults occurring in inter-gate connections. This distinction between fault-types can then be used for triggering selective self-healing responses. The second contribution is a logic matrix element which applies the three core redundancy concepts of spatial- temporal- and data-redundancy. This logic structure is composed of quad-modular redundant structures and is capable of selective fault-masking and localisation depending of fault-type at the cell level, which is referred to as a spatiotemporal quadded logic cell (QLC) structure. This QLC structure has the capability of cellular self-healing. Through the combination of fault-tolerant and masking logic features the QLC is designed with a fault-behaviour that is equal to existing quadded logic designs using only 33.3% of the equivalent transistor resources. The inherent self-diagnosing feature of QLC is capable of identifying individual faulty cells and can trigger self-healing features. The final contribution is focused on the conversion of finite state machines (FSM) into memory to achieve better state transition timing, minimal memory utilisation and fault protection compared to common FSM designs. A novel implementation based on content-addressable type memory (CAM) is used to achieve this. The FSM is further enhanced by creating the design out of logic gates of the first contribution by achieving stuck-at fault resilience. Applying cross-data parity checking, the FSM becomes equipped with single bit fault detection and correction

The ATLAS ROBIN – A High-Performance Data-Acquisition Module

This work presents the re-configurable processor ROBIN, which is a key element of the data-acquisition-system of the ATLAS experiment, located at the new LHC at CERN. The ATLAS detector provides data over 1600 channels simultaneously towards the DAQ system. The ATLAS dataflow model follows the “PULL” strategy in contrast to the commonly used “PUSH” strategy. The data volume transported is reduced by a factor of 10, however the data must be temporarily stored at the entry to the DAQ system. The input layer consists of approx. 160 ROS read-out units comprising 1 PC and 4 ROBIN modules. Each ROBIN device acquires detector data via 3 input channels and performs local buffering. Board control is done via a 64-bit PCI interface. Event selection and data transmission runs via PCI in the baseline bus-based ROS. Alternatively, a local GE interface can take over part or all of the data traffic in the switch-based ROS, in order to reduce the load on the host PC. The performance of the ROBIN module stems from the close cooperation of a fast embedded processor with a complex FPGA. The efficient task-distribution lets the processor handle all complex management functionality, programmed in “C” while all movement of data is performed by the FPGA via multiple, concurrently operating DMA engines. The ROBIN-project was carried-out by and international team and comprises the design specification, the development of the ROBIN hardware, firmware (VHDL and C-Code), host-code (C++), prototyping, volume production and installation of 700 boards. The project was led by the author of this thesis. The hardware platform is an evolution of a FPGA processor previously designed by the author. He has contributed elementary concepts of the communication mechanisms and the “C”-coded embedded application software. He also organised and supervised the prototype and series productions including the various design reports and presentations. The results show that the ROBIN-module is able to meet its ambitious requirements of 100kHz incoming fragment rate per channel with a concurrent outgoing fragment rate of 21kHz per channel. At the system level, each ROS unit (12 channels) operates at the same rates, however for a subset of the channels only. The ATLAS DAQ system – with 640 ROBIN modules installed – has performed a successful data-taking phase at the start-up of the LHC in September

Energy-Efficient Digital Circuit Design using Threshold Logic Gates

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

Topical Workshop on Electronics for Particle Physics

The purpose of the workshop was to present results and original concepts for electronics research and development relevant to particle physics experiments as well as accelerator and beam instrumentation at future facilities; to review the status of electronics for the LHC experiments; to identify and encourage common efforts for the development of electronics; and to promote information exchange and collaboration in the relevant engineering and physics communities

Reliable chip design from low powered unreliable components

The pace of technological improvement of the semiconductor market is driven by Moore’s Law, enabling chip transistor density to double every two years. The transistors would continue to decline in cost and size but increase in power. The continuous transistor scaling and extremely lower power constraints in modern Very Large Scale Integrated(VLSI) chips can potentially supersede the benefits of the technology shrinking due to reliability issues. As VLSI technology scales into nanoscale regime, fundamental physical limits are approached, and higher levels of variability, performance degradation, and higher rates of manufacturing defects are experienced. Soft errors, which traditionally affected only the memories, are now also resulting in logic circuit reliability degradation. A solution to these limitations is to integrate reliability assessment techniques into the Integrated Circuit(IC) design flow. This thesis investigates four aspects of reliability driven circuit design: a)Reliability estimation; b) Reliability optimization; c) Fault-tolerant techniques, and d) Delay degradation analysis. To guide the reliability driven synthesis and optimization of combinational circuits, highly accurate probability based reliability estimation methodology christened Conditional Probabilistic Error Propagation(CPEP) algorithm is developed to compute the impact of gate failures on the circuit output. CPEP guides the proposed rewriting based logic optimization algorithm employing local transformations. The main idea behind this methodology is to replace parts of the circuit with functionally equivalent but more reliable counterparts chosen from a precomputed subset of Negation-Permutation-Negation(NPN) classes of 4-variable functions. Cut enumeration and Boolean matching driven by reliability-aware optimization algorithm are used to identify the best possible replacement candidates. Experiments on a set of MCNC benchmark circuits and 8051 functional microcontroller units indicate that the proposed framework can achieve up to 75% reduction of output error probability. On average, about 14% SER reduction is obtained at the expense of very low area overhead of 6.57% that results in 13.52% higher power consumption. The next contribution of the research describes a novel methodology to design fault tolerant circuitry by employing the error correction codes known as Codeword Prediction Encoder(CPE). Traditional fault tolerant techniques analyze the circuit reliability issue from a static point of view neglecting the dynamic errors. In the context of communication and storage, the study of novel methods for reliable data transmission under unreliable hardware is an increasing priority. The idea of CPE is adapted from the field of forward error correction for telecommunications focusing on both encoding aspects and error correction capabilities. The proposed Augmented Encoding solution consists of computing an augmented codeword that contains both the codeword to be transmitted on the channel and extra parity bits. A Computer Aided Development(CAD) framework known as CPE simulator is developed providing a unified platform that comprises a novel encoder and fault tolerant LDPC decoders. Experiments on a set of encoders with different coding rates and different decoders indicate that the proposed framework can correct all errors under specific scenarios. On average, about 1000 times improvement in Soft Error Rate(SER) reduction is achieved. Last part of the research is the Inverse Gaussian Distribution(IGD) based delay model applicable to both combinational and sequential elements for sub-powered circuits. The Probability Density Function(PDF) based delay model accurately captures the delay behavior of all the basic gates in the library database. The IGD model employs these necessary parameters, and the delay estimation accuracy is demonstrated by evaluating multiple circuits. Experiments results indicate that the IGD based approach provides a high matching against HSPICE Monte Carlo simulation results, with an average error less than 1.9% and 1.2% for the 8-bit Ripple Carry Adder(RCA), and 8-bit De-Multiplexer(DEMUX) and Multiplexer(MUX) respectively