Real Time Fault Detection and Diagnostics Using FPGA-Based Architecture

Errors within circuits caused by radiation continue to be an important concern to developers. A new methodology of real time fault detection and diagnostics utilizing FPGA based architectures while under radiation were investigated in this research. The contributions of this research are focused on three areas; a full test platform to evaluate a circuit while under irradiation, an algorithm to detect and diagnose fault locations within a circuit, and finally to characterize Triple Design Triple Modular Redundancy (TDTMR), a new form of TMR. Five different test setups, injected fault test, gamma radiation test, thermal radiation test, optical laser test, and optical flash test, were used to assess the effectiveness of these three research goals. The testing platform was constructed with two FPGA boards, the Device Under Test (DUT) and the controller board, to generate and evaluate specific vector sets sent to the DUT. The testing platform combines a myriad of testing and measuring equipment and work hours onto one small reprogrammable and reusable FPGA. This device was able to be used in multiple test setups. The controlling logic can be interchanged to test multiple circuit designs under various forms of radiation. The detection and diagnostic algorithm was designed to determine fault locations in real time. The algorithm used for diagnosing the fault location uses inverse deductive elimination. By using test generation tools, fault lists were developed. The fault lists were used to narrow \ the possible fault locations within the circuit. The algorithm is able to detect single stuck at faults based on these lists. The algorithm can also detect multiple output errors but not able to diagnose multiple stuck at faults in real time

Radiation Tolerant Electronics, Volume II

Research on radiation tolerant electronics has increased rapidly over the last few years, resulting in many interesting approaches to model radiation effects and design radiation hardened integrated circuits and embedded systems. This research is strongly driven by the growing need for radiation hardened electronics for space applications, high-energy physics experiments such as those on the large hadron collider at CERN, and many terrestrial nuclear applications, including nuclear energy and safety management. With the progressive scaling of integrated circuit technologies and the growing complexity of electronic systems, their ionizing radiation susceptibility has raised many exciting challenges, which are expected to drive research in the coming decade.After the success of the first Special Issue on Radiation Tolerant Electronics, the current Special Issue features thirteen articles highlighting recent breakthroughs in radiation tolerant integrated circuit design, fault tolerance in FPGAs, radiation effects in semiconductor materials and advanced IC technologies and modelling of radiation effects

Autonomous Recovery Of Reconfigurable Logic Devices Using Priority Escalation Of Slack

Field Programmable Gate Array (FPGA) devices offer a suitable platform for survivable hardware architectures in mission-critical systems. In this dissertation, active dynamic redundancy-based fault-handling techniques are proposed which exploit the dynamic partial reconfiguration capability of SRAM-based FPGAs. Self-adaptation is realized by employing reconfiguration in detection, diagnosis, and recovery phases. To extend these concepts to semiconductor aging and process variation in the deep submicron era, resilient adaptable processing systems are sought to maintain quality and throughput requirements despite the vulnerabilities of the underlying computational devices. A new approach to autonomous fault-handling which addresses these goals is developed using only a uniplex hardware arrangement. It operates by observing a health metric to achieve Fault Demotion using Recon- figurable Slack (FaDReS). Here an autonomous fault isolation scheme is employed which neither requires test vectors nor suspends the computational throughput, but instead observes the value of a health metric based on runtime input. The deterministic flow of the fault isolation scheme guarantees success in a bounded number of reconfigurations of the FPGA fabric. FaDReS is then extended to the Priority Using Resource Escalation (PURE) online redundancy scheme which considers fault-isolation latency and throughput trade-offs under a dynamic spare arrangement. While deep-submicron designs introduce new challenges, use of adaptive techniques are seen to provide several promising avenues for improving resilience. The scheme developed is demonstrated by hardware design of various signal processing circuits and their implementation on a Xilinx Virtex-4 FPGA device. These include a Discrete Cosine Transform (DCT) core, Motion Estimation (ME) engine, Finite Impulse Response (FIR) Filter, Support Vector Machine (SVM), and Advanced Encryption Standard (AES) blocks in addition to MCNC benchmark circuits. A iii significant reduction in power consumption is achieved ranging from 83% for low motion-activity scenes to 12.5% for high motion activity video scenes in a novel ME engine configuration. For a typical benchmark video sequence, PURE is shown to maintain a PSNR baseline near 32dB. The diagnosability, reconfiguration latency, and resource overhead of each approach is analyzed. Compared to previous alternatives, PURE maintains a PSNR within a difference of 4.02dB to 6.67dB from the fault-free baseline by escalating healthy resources to higher-priority signal processing functions. The results indicate the benefits of priority-aware resiliency over conventional redundancy approaches in terms of fault-recovery, power consumption, and resource-area requirements. Together, these provide a broad range of strategies to achieve autonomous recovery of reconfigurable logic devices under a variety of constraints, operating conditions, and optimization criteria

Heterogeneous Reconfigurable Fabrics for In-circuit Training and Evaluation of Neuromorphic Architectures

A heterogeneous device technology reconfigurable logic fabric is proposed which leverages the cooperating advantages of distinct magnetic random access memory (MRAM)-based look-up tables (LUTs) to realize sequential logic circuits, along with conventional SRAM-based LUTs to realize combinational logic paths. The resulting Hybrid Spin/Charge FPGA (HSC-FPGA) using magnetic tunnel junction (MTJ) devices within this topology demonstrates commensurate reductions in area and power consumption over fabrics having LUTs constructed with either individual technology alone. Herein, a hierarchical top-down design approach is used to develop the HSCFPGA starting from the configurable logic block (CLB) and slice structures down to LUT circuits and the corresponding device fabrication paradigms. This facilitates a novel architectural approach to reduce leakage energy, minimize communication occurrence and energy cost by eliminating unnecessary data transfer, and support auto-tuning for resilience. Furthermore, HSC-FPGA enables new advantages of technology co-design which trades off alternative mappings between emerging devices and transistors at runtime by allowing dynamic remapping to adaptively leverage the intrinsic computing features of each device technology. HSC-FPGA offers a platform for fine-grained Logic-In-Memory architectures and runtime adaptive hardware. An orthogonal dimension of fabric heterogeneity is also non-determinism enabled by either low-voltage CMOS or probabilistic emerging devices. It can be realized using probabilistic devices within a reconfigurable network to blend deterministic and probabilistic computational models. Herein, consider the probabilistic spin logic p-bit device as a fabric element comprising a crossbar-structured weighted array. The Programmability of the resistive network interconnecting p-bit devices can be achieved by modifying the resistive states of the array\u27s weighted connections. Thus, the programmable weighted array forms a CLB-scale macro co-processing element with bitstream programmability. This allows field programmability for a wide range of classification problems and recognition tasks to allow fluid mappings of probabilistic and deterministic computing approaches. In particular, a Deep Belief Network (DBN) is implemented in the field using recurrent layers of co-processing elements to form an n x m1 x m2 x ::: x mi weighted array as a configurable hardware circuit with an n-input layer followed by i ≥ 1 hidden layers. As neuromorphic architectures using post-CMOS devices increase in capability and network size, the utility and benefits of reconfigurable fabrics of neuromorphic modules can be anticipated to continue to accelerate

Characterisation and mitigation of long-term degradation effects in programmable logic

Reliability has always been an issue in silicon device engineering, but until now it has been managed by the carefully tuned fabrication process. In the future the underlying physical limitations of silicon-based electronics, plus the practical challenges of manufacturing with such complexity at such a small scale, will lead to a crunch point where transistor-level reliability must be forfeited to continue achieving better productivity. Field-programmable gate arrays (FPGAs) are built on state-of-the-art silicon processes, but it has been recognised for some time that their distinctive characteristics put them in a favourable position over application-specific integrated circuits in the face of the reliability challenge. The literature shows how a regular structure, interchangeable resources and an ability to reconfigure can all be exploited to detect, locate, and overcome degradation and keep an FPGA application running. To fully exploit these characteristics, a better understanding is needed of the behavioural changes that are seen in the resources that make up an FPGA under ageing. Modelling is an attractive approach to this and in this thesis the causes and effects are explored of three important degradation mechanisms. All are shown to have an adverse affect on FPGA operation, but their characteristics show novel opportunities for ageing mitigation. Any modelling exercise is built on assumptions and so an empirical method is developed for investigating ageing on hardware with an accelerated-life test. Here, experiments show that timing degradation due to negative-bias temperature instability is the dominant process in the technology considered. Building on simulated and experimental results, this work also demonstrates a variety of methods for increasing the lifetime of FPGA lookup tables. The pre-emptive measure of wear-levelling is investigated in particular detail, and it is shown by experiment how di fferent reconfiguration algorithms can result in a significant reduction to the rate of degradation

Resilience of an embedded architecture using hardware redundancy

In the last decade the dominance of the general computing systems market has being replaced by embedded systems with billions of units manufactured every year. Embedded systems appear in contexts where continuous operation is of utmost importance and failure can be profound. Nowadays, radiation poses a serious threat to the reliable operation of safety-critical systems. Fault avoidance techniques, such as radiation hardening, have been commonly used in space applications. However, these components are expensive, lag behind commercial components with regards to performance and do not provide 100% fault elimination. Without fault tolerant mechanisms, many of these faults can become errors at the application or system level, which in turn, can result in catastrophic failures. In this work we study the concepts of fault tolerance and dependability and extend these concepts providing our own definition of resilience. We analyse the physics of radiation-induced faults, the damage mechanisms of particles and the process that leads to computing failures. We provide extensive taxonomies of 1) existing fault tolerant techniques and of 2) the effects of radiation in state-of-the-art electronics, analysing and comparing their characteristics. We propose a detailed model of faults and provide a classification of the different types of faults at various levels. We introduce an algorithm of fault tolerance and define the system states and actions necessary to implement it. We introduce novel hardware and system software techniques that provide a more efficient combination of reliability, performance and power consumption than existing techniques. We propose a new element of the system called syndrome that is the core of a resilient architecture whose software and hardware can adapt to reliable and unreliable environments. We implement a software simulator and disassembler and introduce a testing framework in combination with ERA’s assembler and commercial hardware simulators

Leveraging the Intrinsic Switching Behaviors of Spintronic Devices for Digital and Neuromorphic Circuits

With semiconductor technology scaling approaching atomic limits, novel approaches utilizing new memory and computation elements are sought in order to realize increased density, enhanced functionality, and new computational paradigms. Spintronic devices offer intriguing avenues to improve digital circuits by leveraging non-volatility to reduce static power dissipation and vertical integration for increased density. Novel hybrid spintronic-CMOS digital circuits are developed herein that illustrate enhanced functionality at reduced static power consumption and area cost. The developed spin-CMOS D Flip-Flop offers improved power-gating strategies by achieving instant store/restore capabilities while using 10 fewer transistors than typical CMOS-only implementations. The spin-CMOS Muller C-Element developed herein improves asynchronous pipelines by reducing the area overhead while adding enhanced functionality such as instant data store/restore and delay-element-free bundled data asynchronous pipelines. Spintronic devices also provide improved scaling for neuromorphic circuits by enabling compact and low power neuron and non-volatile synapse implementations while enabling new neuromorphic paradigms leveraging the stochastic behavior of spintronic devices to realize stochastic spiking neurons, which are more akin to biological neurons and commensurate with theories from computational neuroscience and probabilistic learning rules. Spintronic-based Probabilistic Activation Function circuits are utilized herein to provide a compact and low-power neuron for Binarized Neural Networks. Two implementations of stochastic spiking neurons with alternative speed, power, and area benefits are realized. Finally, a comprehensive neuromorphic architecture comprising stochastic spiking neurons, low-precision synapses with Probabilistic Hebbian Plasticity, and a novel non-volatile homeostasis mechanism is realized for subthreshold ultra-low-power unsupervised learning with robustness to process variations. Along with several case studies, implications for future spintronic digital and neuromorphic circuits are presented

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems