Interconnect yield analysis and fault tolerance for field programmable gate arrays

Imperial Users onl

Microprocessor fault-tolerance via on-the-fly partial reconfiguration

This paper presents a novel approach to exploit FPGA dynamic partial reconfiguration to improve the fault tolerance of complex microprocessor-based systems, with no need to statically reserve area to host redundant components. The proposed method not only improves the survivability of the system by allowing the online replacement of defective key parts of the processor, but also provides performance graceful degradation by executing in software the tasks that were executed in hardware before a fault and the subsequent reconfiguration happened. The advantage of the proposed approach is that thanks to a hardware hypervisor, the CPU is totally unaware of the reconfiguration happening in real-time, and there's no dependency on the CPU to perform it. As proof of concept a design using this idea has been developed, using the LEON3 open-source processor, synthesized on a Virtex 4 FPG

Fault and Defect Tolerant Computer Architectures: Reliable Computing With Unreliable Devices

This research addresses design of a reliable computer from unreliable device technologies. A system architecture is developed for a fault and defect tolerant (FDT) computer. Trade-offs between different techniques are studied and yield and hardware cost models are developed. Fault and defect tolerant designs are created for the processor and the cache memory. Simulation results for the content-addressable memory (CAM)-based cache show 90% yield with device failure probabilities of 3 x 10(-6), three orders of magnitude better than non fault tolerant caches of the same size. The entire processor achieves 70% yield with device failure probabilities exceeding 10(-6). The required hardware redundancy is approximately 15 times that of a non-fault tolerant design. While larger than current FT designs, this architecture allows the use of devices much more likely to fail than silicon CMOS. As part of model development, an improved model is derived for NAND Multiplexing. The model is the first accurate model for small and medium amounts of redundancy. Previous models are extended to account for dependence between the inputs and produce more accurate results

Développement des techniques de test et de diagnostic pour les FPGA hiérarchique de type mesh

The evolution trend of shrinking feature size and increasing complexity in modern electronics is being slowed down due to physical limits that generate numerous imperfections and defects during fabrication steps or projected life time of the chip. Field Programmable Gate Arrays (FPGAs) are used in complex digital systems mainly due to their reconfigurability and shorter time-to-market. To maintain a high reliability of such systems, FPGAs should be tested thoroughly for defects. FPGA architecture optimization for area saving and better signal routability is an ongoing process which directly impacts the overall FPGA testability, hence the reliability. This thesis presents a complete strategy for test and diagnosis of manufacturing defects in mesh-based FPGAs containing a novel multilevel interconnects topology which promises to provide better area and routability. Efficiency of the proposed test schemes is analyzed in terms of test cost, respective fault coverage and diagnostic resolution.L’évolution tendant à réduire la taille et augmenter la complexité des circuits électroniques modernes, est en train de ralentir du fait des limitations technologiques, qui génèrent beaucoup de d’imperfections et de defaults durant la fabrication ou la durée de vie de la puce. Les FPGAs sont utilisés dans les systèmes numériques complexes, essentiellement parce qu’ils sont reconfigurables et rapide à commercialiser. Pour garder une grande fiabilité de tels systèmes, les FPGAs doivent être testés minutieusement pour les defaults. L’optimisation de l’architecture des FPGAs pour l’économie de surface et une meilleure routabilité est un processus continue qui impacte directement la testabilité globale et de ce fait, la fiabilité. Cette thèse présente une stratégie complète pour le test et le diagnostique des defaults de fabrication des “mesh-based FPGA” contenant une nouvelle topologie d’interconnections à plusieurs niveaux, ce qui promet d’apporter une meilleure routabilité. Efficacité des schémas proposes est analysée en termes de temps de test, couverture de faute et résolution de diagnostique

Robust configurable system design with built-in self-healing

The new generations of SRAM-based FPGA (Field Programmable Gate Array) devices, built on nanometre technology, are the preferred choice for the implementation of reconfigurable computing platforms. However, their vulnerability to hard and soft errors is a major weakness to robust system design based on FPGAs. In this paper, a novel Built-In Self-Healing (BISH) methodology, based on modular redundancy and on selfreconfiguration, is proposed. A soft microprocessor core implemented in the FPGA is responsible for the management and execution of all the BISH procedures. Fault detection and diagnosis is followed by repairing actions, taking advantage of the self-configuration features. Meanwhile, modular redundancy assures that the system still works correctly. This approach leads to a robust system design able to assure high reliability, availability and data integrity

Using Fine Grain Approaches for highly reliable Design of FPGA-based Systems in Space

Nowadays using SRAM based FPGAs in space missions is increasingly considered due to their flexibility and reprogrammability. A challenge is the devices sensitivity to radiation effects that increased with modern architectures due to smaller CMOS structures. This work proposes fault tolerance methodologies, that are based on a fine grain view to modern reconfigurable architectures. The focus is on SEU mitigation challenges in SRAM based FPGAs which can result in crucial situations

Toward Fault-Tolerant Applications on Reconfigurable Systems-on-Chip

L'abstract è presente nell'allegato / the abstract is in the attachmen

Enhancing Real-time Embedded Image Processing Robustness on Reconfigurable Devices for Critical Applications

Nowadays, image processing is increasingly used in several application fields, such as biomedical, aerospace, or automotive. Within these fields, image processing is used to serve both non-critical and critical tasks. As example, in automotive, cameras are becoming key sensors in increasing car safety, driving assistance and driving comfort. They have been employed for infotainment (non-critical), as well as for some driver assistance tasks (critical), such as Forward Collision Avoidance, Intelligent Speed Control, or Pedestrian Detection. The complexity of these algorithms brings a challenge in real-time image processing systems, requiring high computing capacity, usually not available in processors for embedded systems. Hardware acceleration is therefore crucial, and devices such as Field Programmable Gate Arrays (FPGAs) best fit the growing demand of computational capabilities. These devices can assist embedded processors by significantly speeding-up computationally intensive software algorithms. Moreover, critical applications introduce strict requirements not only from the real-time constraints, but also from the device reliability and algorithm robustness points of view. Technology scaling is highlighting reliability problems related to aging phenomena, and to the increasing sensitivity of digital devices to external radiation events that can cause transient or even permanent faults. These faults can lead to wrong information processed or, in the worst case, to a dangerous system failure. In this context, the reconfigurable nature of FPGA devices can be exploited to increase the system reliability and robustness by leveraging Dynamic Partial Reconfiguration features. The research work presented in this thesis focuses on the development of techniques for implementing efficient and robust real-time embedded image processing hardware accelerators and systems for mission-critical applications. Three main challenges have been faced and will be discussed, along with proposed solutions, throughout the thesis: (i) achieving real-time performances, (ii) enhancing algorithm robustness, and (iii) increasing overall system's dependability. In order to ensure real-time performances, efficient FPGA-based hardware accelerators implementing selected image processing algorithms have been developed. Functionalities offered by the target technology, and algorithm's characteristics have been constantly taken into account while designing such accelerators, in order to efficiently tailor algorithm's operations to available hardware resources. On the other hand, the key idea for increasing image processing algorithms' robustness is to introduce self-adaptivity features at algorithm level, in order to maintain constant, or improve, the quality of results for a wide range of input conditions, that are not always fully predictable at design-time (e.g., noise level variations). This has been accomplished by measuring at run-time some characteristics of the input images, and then tuning the algorithm parameters based on such estimations. Dynamic reconfiguration features of modern reconfigurable FPGA have been extensively exploited in order to integrate run-time adaptivity into the designed hardware accelerators. Tools and methodologies have been also developed in order to increase the overall system dependability during reconfiguration processes, thus providing safe run-time adaptation mechanisms. In addition, taking into account the target technology and the environments in which the developed hardware accelerators and systems may be employed, dependability issues have been analyzed, leading to the development of a platform for quickly assessing the reliability and characterizing the behavior of hardware accelerators implemented on reconfigurable FPGAs when they are affected by such faults

Design techniques for xilinx virtex FPGA configuration memory scrubbers

SRAM-based FPGAs are in-field reconfigurable an unlimited number of times. This characteristic, together with their high performance and high logic density, proves to be very convenient for a number of ground and space level applications. One drawback of this technology is that it is susceptible to ionizing radiation, and this sensitivity increases with technology scaling. This is a first order concern for applications in harsh radiation environments, and starts to be a concern for high reliability ground applications. Several techniques exist for coping with radiation effects at user application. In order to be effective they need to be complemented with configuration memory scrubbing, which allows error mitigation and prevents failures due to error accumulation. Depending on the radiation environment and on the system dependability requirements, the configuration scrubber design can become more or less complex. This paper classifies and presents current and novel design methodologies and architectures for SRAM-based FPGAs, and in particular for Xilinx Virtex-4QV/5QV, configuration memory scrubbers

Fault Tolerant Electronic System Design

Due to technology scaling, which means reduced transistor size, higher density, lower voltage and more aggressive clock frequency, VLSI devices may become more sensitive against soft errors. Especially for those devices used in safety- and mission-critical applications, dependability and reliability are becoming increasingly important constraints during the development of system on/around them. Other phenomena (e.g., aging and wear-out effects) also have negative impacts on reliability of modern circuits. Recent researches show that even at sea level, radiation particles can still induce soft errors in electronic systems. On one hand, processor-based system are commonly used in a wide variety of applications, including safety-critical and high availability missions, e.g., in the automotive, biomedical and aerospace domains. In these fields, an error may produce catastrophic consequences. Thus, dependability is a primary target that must be achieved taking into account tight constraints in terms of cost, performance, power and time to market. With standards and regulations (e.g., ISO-26262, DO-254, IEC-61508) clearly specify the targets to be achieved and the methods to prove their achievement, techniques working at system level are particularly attracting. On the other hand, Field Programmable Gate Array (FPGA) devices are becoming more and more attractive, also in safety- and mission-critical applications due to the high performance, low power consumption and the flexibility for reconfiguration they provide. Two types of FPGAs are commonly used, based on their configuration memory cell technology, i.e., SRAM-based and Flash-based FPGA. For SRAM-based FPGAs, the SRAM cells of the configuration memory highly susceptible to radiation induced effects which can leads to system failure; and for Flash-based FPGAs, even though their non-volatile configuration memory cells are almost immune to Single Event Upsets induced by energetic particles, the floating gate switches and the logic cells in the configuration tiles can still suffer from Single Event Effects when hit by an highly charged particle. So analysis and mitigation techniques for Single Event Effects on FPGAs are becoming increasingly important in the design flow especially when reliability is one of the main requirements