520 research outputs found

    DeSyRe: on-Demand System Reliability

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    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

    Trading-off reliability and performance in FPGA-based reconfigurable heterogeneous systems

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    Recent years have witnessed the rapid growth of heterogeneous systems, composed of CPUs and hardware accelerators, to face up the constant increase of computational performance demand of digital systems. In this scenario, FPGAs offer the possibility to implement high performance reconfigurable accelerators, able to speed up the intrinsically parallel portions of applications. The study of reconfigurable heterogeneous systems is still maturing and, while some contributions about performance and power consumption are available, in literature there are few works addressing reliability. This paper analyzes reconfigurable heterogeneous systems in presence of permanent faults occurring in the FPGA. In this context, a reconfigurable heterogeneous architecture, including a Run Time Manager responsible for the communication of software tasks and the FPGA, the scheduling and the placement of hardware tasks, is presented. In addition, the paper introduces a reconfigurable heterogeneous system simulator for the proposed architecture. This simulator is able to evaluate during the design phase the degradation of the system performance due to permanent faults and allows to explore the design space dimensions efficiently

    Autonomous Recovery Of Reconfigurable Logic Devices Using Priority Escalation Of Slack

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    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

    OLT(RE)2: an On-Line on-demand Testing approach for permanent Radiation Effects in REconfigurable systems

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    Reconfigurable systems gained great interest in a wide range of application fields, including aerospace, where electronic devices are exposed to a very harsh working environment. Commercial SRAM-based FPGA devices represent an extremely interesting hardware platform for this kind of systems since they combine low cost with the possibility to utilize state-of-the-art processing power as well as the flexibility of reconfigurable hardware. In this paper we present OLT(RE)2: an on-line on-demand approach to test permanent faults induced by radiation in reconfigurable systems used in space missions. The proposed approach relies on a test circuit and on custom place-and-route algorithms. OLT(RE)2 exploits partial dynamic reconfigurability offered by today’s SRAM-based FPGAs to place the test circuits at run-time. The goal of OLT(RE)2 is to test unprogrammed areas of the FPGA before using them, thus preventing functional modules of the reconfigurable system to be placed on areas with faulty resources. Experimental results have shown that (i) it is possible to generate, place and route the test circuits needed to detect on average more than 99 % of the physical wires and on average about 97 % of the programmable interconnection points of an arbitrary large region of the FPGA in a reasonable time and that (ii) it is possible to download and run the whole test suite on the target device without interfering with the normal functioning of the system

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

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    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

    Sustainable Fault-handling Of Reconfigurable Logic Using Throughput-driven Assessment

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    A sustainable Evolvable Hardware (EH) system is developed for SRAM-based reconfigurable Field Programmable Gate Arrays (FPGAs) using outlier detection and group testing-based assessment principles. The fault diagnosis methods presented herein leverage throughput-driven, relative fitness assessment to maintain resource viability autonomously. Group testing-based techniques are developed for adaptive input-driven fault isolation in FPGAs, without the need for exhaustive testing or coding-based evaluation. The techniques maintain the device operational, and when possible generate validated outputs throughout the repair process. Adaptive fault isolation methods based on discrepancy-enabled pair-wise comparisons are developed. By observing the discrepancy characteristics of multiple Concurrent Error Detection (CED) configurations, a method for robust detection of faults is developed based on pairwise parallel evaluation using Discrepancy Mirror logic. The results from the analytical FPGA model are demonstrated via a self-healing, self-organizing evolvable hardware system. Reconfigurability of the SRAM-based FPGA is leveraged to identify logic resource faults which are successively excluded by group testing using alternate device configurations. This simplifies the system architect\u27s role to definition of functionality using a high-level Hardware Description Language (HDL) and system-level performance versus availability operating point. System availability, throughput, and mean time to isolate faults are monitored and maintained using an Observer-Controller model. Results are demonstrated using a Data Encryption Standard (DES) core that occupies approximately 305 FPGA slices on a Xilinx Virtex-II Pro FPGA. With a single simulated stuck-at-fault, the system identifies a completely validated replacement configuration within three to five positive tests. The approach demonstrates a readily-implemented yet robust organic hardware application framework featuring a high degree of autonomous self-control

    Design and implementation of a routing algorithm to maximize test coverage of permanent faults in FPGAs

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    Nowadays electronic devices are used in a huge number of applications, from entertainment market to military equipment, from mobile phones to satellites. Each application has its own requirements and constraints depending on its purpose. One particular kind of applications is the one called mission critical that is characterized by a large amount of money that could be lost if something goes wrong. As an example this is the case of satellites that cannot be repaired or returned for maintenance if some parts stop working. When electronic device, and in particular FPGAs, are used in mission critical applications their reliability requires a special attention, therefore a key aspect of them is the capability to tolerate faults. When FPGAs operate in harsh environment, like in space, both temporary and permanent faults can occur due to radiation. The on-line testing technique involves a testing circuit that is capable to test its own used resources. In this work a design and implementation of a routing algorithm to maximize fault coverage of permanent faults is presented

    An Adaptive Modular Redundancy Technique to Self-regulate Availability, Area, and Energy Consumption in Mission-critical Applications

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    As reconfigurable devices\u27 capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing environments that require high degree of adaptation. The hardware layer is implemented on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA) to provide self-repair using a novel approach called a Reconfigurable Adaptive Redundancy System (RARS). The software layer supervises the organic activities within the FPGA and extends the self-healing capabilities through application-independent, intrinsic, evolutionary repair techniques to leverage the benefits of dynamic Partial Reconfiguration (PR). A SMART prototype is evaluated using a Sobel edge detection application. This prototype is shown to provide sustainability for stressful occurrences of transient and permanent fault injection procedures while still reducing energy consumption and area requirements. An Organic Genetic Algorithm (OGA) technique is shown capable of consistently repairing hard faults while maintaining correct edge detector outputs, by exploiting spatial redundancy in the reconfigurable hardware. A Monte Carlo driven Continuous Markov Time Chains (CTMC) simulation is conducted to compare SMART\u27s availability to industry-standard Triple Modular Technique (TMR) techniques. Based on nine use cases, parameterized with realistic fault and repair rates acquired from publically available sources, the results indicate that availability is significantly enhanced by the adoption of fast repair techniques targeting aging-related hard-faults. Under harsh environments, SMART is shown to improve system availability from 36.02% with lengthy repair techniques to 98.84% with fast ones. This value increases to five nines (99.9998%) under relatively more favorable conditions. Lastly, SMART is compared to twenty eight standard TMR benchmarks that are generated by the widely-accepted BL-TMR tools. Results show that in seven out of nine use cases, SMART is the recommended technique, with power savings ranging from 22% to 29%, and area savings ranging from 17% to 24%, while still maintaining the same level of availability

    Dynamic Partial Reconfiguration for Dependable Systems

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    Moore’s law has served as goal and motivation for consumer electronics manufacturers in the last decades. The results in terms of processing power increase in the consumer electronics devices have been mainly achieved due to cost reduction and technology shrinking. However, reducing physical geometries mainly affects the electronic devices’ dependability, making them more sensitive to soft-errors like Single Event Transient (SET) of Single Event Upset (SEU) and hard (permanent) faults, e.g. due to aging effects. Accordingly, safety critical systems often rely on the adoption of old technology nodes, even if they introduce longer design time w.r.t. consumer electronics. In fact, functional safety requirements are increasingly pushing industry in developing innovative methodologies to design high-dependable systems with the required diagnostic coverage. On the other hand commercial off-the-shelf (COTS) devices adoption began to be considered for safety-related systems due to real-time requirements, the need for the implementation of computationally hungry algorithms and lower design costs. In this field FPGA market share is constantly increased, thanks to their flexibility and low non-recurrent engineering costs, making them suitable for a set of safety critical applications with low production volumes. The works presented in this thesis tries to face new dependability issues in modern reconfigurable systems, exploiting their special features to take proper counteractions with low impacton performances, namely Dynamic Partial Reconfiguration

    Run-time reconfigurable, fault-tolerant FPGA systems for space applications

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    Cozzi D. Run-time reconfigurable, fault-tolerant FPGA systems for space applications. Bielefeld: Universität Bielefeld; 2016.The aim of this thesis is to investigate the use of Dynamic Partial Reconfiguration (DPR) on Commercial Off-the-Shelf (COTS) FPGAs in space applications. Reconfigurable systems gained interest in a wide range of application fields, including aerospace, where electronic devices are exposed to a harsh working environment. COTS SRAM-based FPGA devices represent an interesting hardware platform for this kind of systems since they combine low cost with the possibility to utilize state-of-the-art processing power as well as the flexibility of reconfigurable hardware. FPGA architectures have high computational power and thanks to their ability to be reconfigured at run-time, they became interesting candidates for payload processing in space applications. The presented Dynamic Reconfigurable Processing Module (DRPM) has been developed to investigate the use of the DPR approach for satellite payload processing. This scalable platform combines dynamically reconfigurable FPGAs with the required avionic interfaces (e.g., SpaceWire, MIL-STD-1553B, and SpaceFibre). In particular, a novel communication interface has been developed, the Heterogeneous Multi Processor Communication Interface (HMPCI), which allows inter-process communication with small latency and low memory footprint. Current synthesis tools do not support fully the DPR capabilities of FPGAs. Therefore, this thesis introduces INDRA 2.0: an INtegrated Design flow for Reconfigurable Architectures. The key part of INDRA 2.0 is DHHarMa: a Design flow for Homogeneous Hard Macros, which generates homogeneous hard macros for Xilinx FPGAs starting from a high-level description (e.g., VHDL). In particular, the homogeneous DHHarMa router is explained in detail, providing novel terminologies and algorithms, which have enabled the generation of homogeneous routed designs. Results have been shown that Design flow for Homogeneous Hard Macros (DHHarMa) can route homogeneously a communication infrastructure utilizing just between 1% and 31% more resources than the Xilinx router, which cannot provide a homogeneous solution. Furthermore, the permanent faults that can occur on FPGAs have been investigated. This thesis presents OLT(RE)2: an on-line on-demand approach to testing permanent faults induced by radiation in reconfigurable systems used in space missions. The proposed approach relies on a test circuit and custom placer and router. OLT(RE)2 exploits DPR to place the test circuits at run-time. Its goal is to test unprogrammed areas of the FPGA before using them. Experimental results of OLT(RE)2 have shown that is possible to generate, place, and route the test circuits needed to detect on average more than 99 % of the physical wires and on average about 97 % of the programmable interconnection points of a large arbitrary region of the FPGA in a reasonable time. Moreover, the test can be run on the target device without interfering the functional behavior of the system
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