A self-adaptive SEU mitigation system for FPGAs with an internal block RAM radiation particle sensor

In this paper, we propose a self-adaptive FPGA- based, partially reconfigurable system for space missions in order to mitigate Single Event Upsets in the FPGA configuration and fabric. Dynamic reconfiguration is used here for an on-demand replication of modules in dependence of current and changing radiation levels. More precisely, the idea is to trigger a redundancy scheme such as Dual Modular Redundancy or Triple Modular Redundancy in response to a continuously monitored Single Event Upset rate measured inside the on-chip memories itself, e.g., any subset (even used) internal Block RAMs. Depending on the current radiation level, the minimal number of replicas is determined at run- time under the constraint that a required Safety Integrity Level for a module is ensured and configured accordingly. For signal processing applications it is shown that this autonomous adaption to the different solar conditions realizes a resource efficient mitigation. In our case study, we show that it is possible to triplicate the data throughput at the Solar Maximum condition (no flares) compared to a Triple Modular Redundancy implementation of a single module. We also show the decreasing Probability of Failures Per Hour by 2 × 104 at flare-enhanced conditions compared with a non-redundant system. Our work is a part of the In-Orbit Verification of the Heinrich Hertz communication satellite

Dynamic Partial Reconfiguration for Dependable Systems

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

A Self-adaptive SEU Mitigation Scheme for Embedded Systems in Extreme Radiation Environments

When electronic systems are working in radiation environments, transient errors, and permanent errors may occur. Static random-access memory (SRAM) has been the one of most significant parts in various semiconductor chips for its high performance and high logic density features. However, because of their dedicated electronic circuits, SRAMs are sensitive to radiation effects. In this article, a portable scheme combined with error correcting code (ECC) and refreshing techniques is proposed to correct errors and mitigate error accumulation in extreme radiation environments. Since the proposed scheme is small and transparent to other modules and no additional latency is introduced, it therefore can be easily applied to the system where the hardware modules are designed with fixed reading and writing latency. We evaluated this design by simulation in a hardware fault injection platform and radiation experiments in the neutron radiation facility. The results obtained in the neutron experiment, where the flux of neutron particles is 5×106 cm2. s−1 , show that the number of bit-flips in 32 kB self-refresh ECC RAM on the Xilinx Artix-7 FPGA remains zero, while the number of bit-flips in unhardened RAM rose to 32 in 1.5 h

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

Area-driven partial reconfiguration for SEU mitigation on SRAM-based FPGAs

This paper presents an area-driven Field-Programmable Gate Array (FPGA) scrubbing technique based on partial reconfiguration for Single Event Upset (SEU) mitigation. The proposed method is compared with existing techniques such as blind and on-demand scrubbing on a novel SEU mitigation framework implemented on the ZYNQ platform, supporting various SEU and scrubbing rates. A design space exploration on the availability versus data transfers from a Double Data Rate Type 3 (DDR3) memory, shows that our approach outperforms blind scrubbing for a range of availability values when a second order polynomial IP is targeted. A comparison to an existing on-demand scrubbing technique based on Dual Modular Redundancy (DMR) shows that our approach saves up to 46% area for the same case study

Analyse und Erweiterung eines fehler-toleranten NoC für SRAM-basierte FPGAs in Weltraumapplikationen

Data Processing Units for scientific space mission need to process ever higher volumes of data and perform ever complex calculations. But the performance of available space-qualified general purpose processors is just in the lower three digit megahertz range, which is already insufficient for some applications. As an alternative, suitable processing steps can be implemented in hardware on a space-qualified SRAM-based FPGA. However, suitable devices are susceptible against space radiation. At the Institute for Communication and Network Engineering a fault-tolerant, network-based communication architecture was developed, which enables the construction of processing chains on the basis of different processing modules within suitable SRAM-based FPGAs and allows the exchange of single processing modules during runtime, too. The communication architecture and its protocol shall isolate non SEU mitigated or just partial SEU mitigated modules affected by radiation-induced faults to prohibit the propagation of errors within the remaining System-on-Chip. In the context of an ESA study, this communication architecture was extended with further components and implemented in a representative hardware platform. Based on the acquired experiences during the study, this work analyses the actual fault-tolerance characteristics as well as weak points of this initial implementation. At appropriate locations, the communication architecture was extended with mechanisms for fault-detection and fault-differentiation as well as with a hardware-based monitoring solution. Both, the former measures and the extension of the employed hardware-platform with selective fault-injection capabilities for the emulation of radiation-induced faults within critical areas of a non SEU mitigated processing module, are used to evaluate the effects of radiation-induced faults within the communication architecture. By means of the gathered results, further measures to increase fast detection and isolation of faulty nodes are developed, selectively implemented and verified. In particular, the ability of the communication architecture to isolate network nodes without SEU mitigation could be significantly improved.Instrumentenrechner für wissenschaftliche Weltraummissionen müssen ein immer höheres Datenvolumen verarbeiten und immer komplexere Berechnungen ausführen. Die Performanz von verfügbaren qualifizierten Universalprozessoren liegt aber lediglich im unteren dreistelligen Megahertz-Bereich, was für einige Anwendungen bereits nicht mehr ausreicht. Als Alternative bietet sich die Implementierung von entsprechend geeigneten Datenverarbeitungsschritten in Hardware auf einem qualifizierten SRAM-basierten FPGA an. Geeignete Bausteine sind jedoch empfindlich gegenüber der Strahlungsumgebung im Weltraum. Am Institut für Datentechnik und Kommunikationsnetze wurde eine fehlertolerante netzwerk-basierte Kommunikationsarchitektur entwickelt, die innerhalb eines geeigneten SRAM-basierten FPGAs Datenverarbeitungsmodule miteinander nach Bedarf zu Verarbeitungsketten verbindet, sowie den Austausch von einzelnen Modulen im Betrieb ermöglicht. Nicht oder nur partiell SEU mitigierte Module sollen bei strahlungsbedingten Fehlern im Modul durch das Protokoll und die Fehlererkennungsmechanismen der Kommunikationsarchitektur isoliert werden, um ein Ausbreiten des Fehlers im restlichen System-on-Chip zu verhindern. Im Kontext einer ESA Studie wurde diese Kommunikationsarchitektur um Komponenten erweitert und auf einer repräsentativen Hardwareplattform umgesetzt. Basierend auf den gesammelten Erfahrungen aus der Studie, wird in dieser Arbeit eine Analyse der tatsächlichen Fehlertoleranz-Eigenschaften sowie der Schwachstellen dieser ursprünglichen Implementierung durchgeführt. Die Kommunikationsarchitektur wurde an geeigneten Stellen um Fehlerdetektierungs- und Fehlerunterscheidungsmöglichkeiten erweitert, sowie um eine hardwarebasierte Überwachung ergänzt. Sowohl diese Maßnahmen, als auch die Erweiterung der Hardwareplattform um gezielte Fehlerinjektions-Möglichkeiten zum Emulieren von strahlungsinduzierten Fehlern in kritischen Komponenten eines nicht SEU mitigierten Prozessierungsmoduls werden genutzt, um die tatsächlichen auftretenden Effekte in der Kommunikationsarchitektur zu evaluieren. Anhand der Ergebnisse werden weitere Verbesserungsmaßnahmen speziell zur schnellen Detektierung und Isolation von fehlerhaften Knoten erarbeitet, selektiv implementiert und verifiziert. Insbesondere die Fähigkeit, fehlerhafte, nicht SEU mitigierte Netzwerkknoten innerhalb der Kommunikationsarchitektur zu isolieren, konnte dabei deutlich verbessert werden

Assessing Scrubbing Techniques for Xilinx SRAM-based FPGAs in Space Applications

SRAM-based FPGAs are becoming increasingly attractive for use in space applications due to their reconfigurability and signal processing capabilities, as well as their increasing speed and capacity. Traditional SRAM-based FPGAs, however, are highly sensitive to the ionizing radiation environment in space, making them prone to radiation-induced memory upsets. In this paper, we evaluate and compare scrubbing techniques for Xilinx SRAM-based FPGAs with respect to radiation-induced single event upsets. A test framework using an exchangeable payload is developed for this purpose and run on a Xilinx Virtex-5 FPGA. We show that recent SRAM-based FPGAs can constitute a cost-efficient alternative to radiation-hardened or antifuse FPGAs for non-critical space application such as satellite instruments

Optimizing Scrubbing by Netlist Analysis for FPGA Configuration Bit Classification and Floorplanning

Existing scrubbing techniques for SEU mitigation on FPGAs do not guarantee an error-free operation after SEU recovering if the affected configuration bits do belong to feedback loops of the implemented circuits. In this paper, we a) provide a netlist-based circuit analysis technique to distinguish so-called critical configuration bits from essential bits in order to identify configuration bits which will need also state-restoring actions after a recovered SEU and which not. Furthermore, b) an alternative classification approach using fault injection is developed in order to compare both classification techniques. Moreover, c) we will propose a floorplanning approach for reducing the effective number of scrubbed frames and d), experimental results will give evidence that our optimization methodology not only allows to detect errors earlier but also to minimize the Mean-Time-To-Repair (MTTR) of a circuit considerably. In particular, we show that by using our approach, the MTTR for datapath-intensive circuits can be reduced by up to 48.5% in comparison to standard approaches