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-tolerant sub-lithographic design with rollback recovery

Shrinking feature sizes and energy levels coupled with high clock rates and decreasing node capacitance lead us into a regime where transient errors in logic cannot be ignored. Consequently, several recent studies have focused on feed-forward spatial redundancy techniques to combat these high transient fault rates. To complement these studies, we analyze fine-grained rollback techniques and show that they can offer lower spatial redundancy factors with no significant impact on system performance for fault rates up to one fault per device per ten million cycles of operation (Pf = 10^-7) in systems with 10^12 susceptible devices. Further, we concretely demonstrate these claims on nanowire-based programmable logic arrays. Despite expensive rollback buffers and general-purpose, conservative analysis, we show the area overhead factor of our technique is roughly an order of magnitude lower than a gate level feed-forward redundancy scheme

Reliable and Fault-Resilient Schemes for Efficient Radix-4 Complex Division

Complex division is commonly used in various applications in signal processing and control theory including astronomy and nonlinear RF measurements. Nevertheless, unless reliability and assurance are embedded into the architectures of such structures, the suboptimal (and thus erroneous) results could undermine the objectives of such applications. As such, in this thesis, we present schemes to provide complex number division architectures based on (Sweeney, Robertson, and Tocher) SRT-division with fault diagnosis mechanisms. Different fault resilient architectures are proposed in this thesis which can be tailored based on the eventual objectives of the designs in terms of area and time requirements, among which we pinpoint carefully the schemes based on recomputing with shifted operands (RESO) to be able to detect both natural and malicious faults and with proper modification achieve high throughputs. The design also implements a minimized look up table approach which favors in error detection based designs and provides high fault coverage with relatively-low overhead. Additionally, to benchmark the effectiveness of the proposed schemes, extensive fault diagnosis assessments are performed for the proposed designs through fault simulations and FPGA implementations; the design is implemented on Xilinx Spartan-VI and Xilinx Virtex-VI FPGA families

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

Measurements, Models, Systems and Design

531 s.

Fault-Resilient Lightweight Cryptographic Block Ciphers for Secure Embedded Systems

The development of extremely-constrained environments having sensitive nodes such as RFID tags and nano-sensors necessitates the use of lightweight block ciphers. Indeed, lightweight block ciphers are essential for providing low-cost confidentiality to such applications. Nevertheless, providing the required security properties does not guarantee their reliability and hardware assurance when the architectures are prone to natural and malicious faults. In this thesis, considering false-alarm resistivity, error detection schemes for the lightweight block ciphers are proposed with the case study of XTEA (eXtended TEA). We note that lightweight block ciphers might be better suited for low-resource environments compared to the Advanced Encryption Standard, providing low complexity and power consumption. To the best of the author\u27s knowledge, there has been no error detection scheme presented in the literature for the XTEA to date. Three different error detection approaches are presented and according to our fault-injection simulations for benchmarking the effectiveness of the proposed schemes, high error coverage is derived. Finally, field-programmable gate array (FPGA) implementations of these proposed error detection structures are presented to assess their efficiency and overhead. The proposed error detection architectures are capable of increasing the reliability of the implementations of this lightweight block cipher. The schemes presented can also be applied to lightweight hash functions with similar structures, making the presented schemes suitable for providing reliability to their lightweight security-constrained hardware implementations

DeSyRe: on-Demand System Reliability

The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints

Using embedded hardware monitor cores in critical computer systems

The integration of FPGA devices in many different architectures and services makes monitoring and real time detection of errors an important concern in FPGA system design. A monitor is a tool, or a set of tools, that facilitate analytic measurements in observing a given system. The goal of these observations is usually the performance analysis and optimisation, or the surveillance of the system. However, System-on-Chip (SoC) based designs leave few points to attach external tools such as logic analysers. Thus, an embedded error detection core that allows observation of critical system nodes (such as processor cores and buses) should enforce the operation of the FPGA-based system, in order to prevent system failures. The core should not interfere with system performance and must ensure timely detection of errors. This thesis is an investigation onto how a robust hardware-monitoring module can be efficiently integrated in a target PCI board (with FPGA-based application processing features) which is part of a critical computing system. [Continues.

CMOS Vision Sensors: Embedding Computer Vision at Imaging Front-Ends

CMOS Image Sensors (CIS) are key for imaging technol-ogies. These chips are conceived for capturing opticalscenes focused on their surface, and for delivering elec-trical images, commonly in digital format. CISs may incor-porate intelligence; however, their smartness basicallyconcerns calibration, error correction and other similartasks. The term CVISs (CMOS VIsion Sensors) definesother class of sensor front-ends which are aimed at per-forming vision tasks right at the focal plane. They havebeen running under names such as computational imagesensors, vision sensors and silicon retinas, among others. CVIS and CISs are similar regarding physical imple-mentation. However, while inputs of both CIS and CVISare images captured by photo-sensors placed at thefocal-plane, CVISs primary outputs may not be imagesbut either image features or even decisions based on thespatial-temporal analysis of the scenes. We may hencestate that CVISs are more “intelligent” than CISs as theyfocus on information instead of on raw data. Actually,CVIS architectures capable of extracting and interpretingthe information contained in images, and prompting reac-tion commands thereof, have been explored for years inacademia, and industrial applications are recently ramp-ing up.One of the challenges of CVISs architects is incorporat-ing computer vision concepts into the design flow. Theendeavor is ambitious because imaging and computervision communities are rather disjoint groups talking dif-ferent languages. The Cellular Nonlinear Network Univer-sal Machine (CNNUM) paradigm, proposed by Profs.Chua and Roska, defined an adequate framework forsuch conciliation as it is particularly well suited for hard-ware-software co-design [1]-[4]. This paper overviewsCVISs chips that were conceived and prototyped at IMSEVision Lab over the past twenty years. Some of them fitthe CNNUM paradigm while others are tangential to it. Allthem employ per-pixel mixed-signal processing circuitryto achieve sensor-processing concurrency in the quest offast operation with reduced energy budget.Junta de Andalucía TIC 2012-2338Ministerio de Economía y Competitividad TEC 2015-66878-C3-1-R y TEC 2015-66878-C3-3-