Analysis of Radiation-induced Cross Domain Errors in TMR Architectures on SRAM-based FPGAs

SRAM-Based FPGAs represent a low-cost alternative to ASIC device thanks to their high performance and design flexibility. In particular, for aerospace and avionics application fields, SRAM-based FPGAs are increasingly adopted for their configurability features making them a viable solution for long-time applications. However, these fields are characterized by a radiation environment that makes the technology extremely sensitive to radiation-induced Single Event Upsets (SEUs) in the SRAM-based FPGA’s configuration memory. Configuration scrubbing and Triple Modular Redundancy (TMR) have been widely adopted in order to cope with SEU effects. However, modern FPGA devices are characterized by a heterogeneous routing resource distribution and a complex configuration memory mapping causing an increasing sensitivity to Cross Domain Errors affecting the TMR structure. In this paper we developed a new methodology to calculate the reliability of TMR architecture considering the intrinsic characteristics of the new generation of SRAM-based FPGAs. The method includes the analysis of the configuration bit sharing phenomena and of the routing long lines. We experimentally evaluate the method of various benchmark circuits evaluating the Mean Upset To Failure (MUTF). Finally, we used the results of the developed method to implement an improved design achieving 29x improvement of the MUTF

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

Improved Fault Tolerant SRAM Cell Design & Layout in 130nm Technology

Technology scaling of CMOS devices has made the integrated circuits vulnerable to single event radiation effects. Scaling of CMOS Static RAM (SRAM) has led to denser packing architectures by reducing the size and spacing of diffusion nodes. However, this trend has led to the increase in charge collection and sharing effects between devices during an ion strike, making the circuit even more vulnerable to a specific single event effect called the single event multiple-node upset (SEMU). In nanometer technologies, SEMU can easily disrupt the data stored in the memory and can be more hazardous than a single event single-node upset. During the last decade, most of the research efforts were mainly focused on improving the single event single-node upset tolerance of SRAM cells by using novel circuit techniques, but recent studies relating to angular radiation sensitivity has revealed the importance of SEMU and Multi Bit Upset (MBU) tolerance for SRAM cells. The research focuses on improving SEMU tolerance of CMOS SRAM cells by using novel circuit and layout level techniques. A novel SRAM cell circuit & layout technique is proposed to improve the SEMU tolerance of 6T SRAM cells with decreasing feature size, making it an ideal candidate for future technologies. The layout is based on strategically positioning diffusion nodes in such a way as to provide charge cancellation among nodes during SEMU radiation strikes, instead of charge build-up. The new design & layout technique can improve the SEMU tolerance levels by up to 20 times without sacrificing on area overhead and hence is suitable for high density SRAM designs in commercial applications. Finally, laser testing of SRAM based configuration memory of a Xilinx Virtex-5 FPGA is performed to analyze the behavior of SRAM based systems towards radiation strikes

Fault Tolerance Implementation within SRAM Based FPGA Designs based upon Single Event Upset Occurrence Rates

Emerging technology is enabling the design community to consistently expand the amount of functionality that can be implemented within Integrated Circuits (ICs). As the number of gates placed within an FPGA increases, the complexity of the design can grow exponentially. Consequently, the ability to create reliable circuits has become an incredibly difficult task. In order to ease the complexity of design completion, the commercial design community has developed a very rigid (but effective) design methodology based on synchronous circuit techniques. In order to create faster, smaller and lower power circuits, transistor geometries and core voltages have decreased. In environments that contain ionizing energy, such a combination will increase the probability of Single Event Upsets (SEUs) and will consequently affect the state space of a circuit. In order to combat the effects of radiation, the aerospace community has developed several "Hardened by Design" (fault tolerant) design schemes. This paper will address design mitigation schemes targeted for SRAM Based FPGA CMOS devices. Because some mitigation schemes may be over zealous (too much power, area, complexity, etc.. . .), the designer should be conscious that system requirements can ease the amount of mitigation necessary for acceptable operation. Therefore, various degrees of Fault Tolerance will be demonstrated along with an analysis of its effectiveness

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

Semiconductor Memory Applications in Radiation Environment, Hardware Security and Machine Learning System

abstract: Semiconductor memory is a key component of the computing systems. Beyond the conventional memory and data storage applications, in this dissertation, both mainstream and eNVM memory technologies are explored for radiation environment, hardware security system and machine learning applications. In the radiation environment, e.g. aerospace, the memory devices face different energetic particles. The strike of these energetic particles can generate electron-hole pairs (directly or indirectly) as they pass through the semiconductor device, resulting in photo-induced current, and may change the memory state. First, the trend of radiation effects of the mainstream memory technologies with technology node scaling is reviewed. Then, single event effects of the oxide based resistive switching random memory (RRAM), one of eNVM technologies, is investigated from the circuit-level to the system level. Physical Unclonable Function (PUF) has been widely investigated as a promising hardware security primitive, which employs the inherent randomness in a physical system (e.g. the intrinsic semiconductor manufacturing variability). In the dissertation, two RRAM-based PUF implementations are proposed for cryptographic key generation (weak PUF) and device authentication (strong PUF), respectively. The performance of the RRAM PUFs are evaluated with experiment and simulation. The impact of non-ideal circuit effects on the performance of the PUFs is also investigated and optimization strategies are proposed to solve the non-ideal effects. Besides, the security resistance against modeling and machine learning attacks is analyzed as well. Deep neural networks (DNNs) have shown remarkable improvements in various intelligent applications such as image classification, speech classification and object localization and detection. Increasing efforts have been devoted to develop hardware accelerators. In this dissertation, two types of compute-in-memory (CIM) based hardware accelerator designs with SRAM and eNVM technologies are proposed for two binary neural networks, i.e. hybrid BNN (HBNN) and XNOR-BNN, respectively, which are explored for the hardware resource-limited platforms, e.g. edge devices.. These designs feature with high the throughput, scalability, low latency and high energy efficiency. Finally, we have successfully taped-out and validated the proposed designs with SRAM technology in TSMC 65 nm. Overall, this dissertation paves the paths for memory technologies’ new applications towards the secure and energy-efficient artificial intelligence system.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

On the Resilience of RTL NN Accelerators: Fault Characterization and Mitigation

Machine Learning (ML) is making a strong resurgence in tune with the massive generation of unstructured data which in turn requires massive computational resources. Due to the inherently compute- and power-intensive structure of Neural Networks (NNs), hardware accelerators emerge as a promising solution. However, with technology node scaling below 10nm, hardware accelerators become more susceptible to faults, which in turn can impact the NN accuracy. In this paper, we study the resilience aspects of Register-Transfer Level (RTL) model of NN accelerators, in particular, fault characterization and mitigation. By following a High-Level Synthesis (HLS) approach, first, we characterize the vulnerability of various components of RTL NN. We observed that the severity of faults depends on both i) application-level specifications, i.e., NN data (inputs, weights, or intermediate), NN layers, and NN activation functions, and ii) architectural-level specifications, i.e., data representation model and the parallelism degree of the underlying accelerator. Second, motivated by characterization results, we present a low-overhead fault mitigation technique that can efficiently correct bit flips, by 47.3% better than state-of-the-art methods.Comment: 8 pages, 6 figure

Use of Field Programmable Gate Array Technology in Future Space Avionics

Fulfilling NASA's new vision for space exploration requires the development of sustainable, flexible and fault tolerant spacecraft control systems. The traditional development paradigm consists of the purchase or fabrication of hardware boards with fixed processor and/or Digital Signal Processing (DSP) components interconnected via a standardized bus system. This is followed by the purchase and/or development of software. This paradigm has several disadvantages for the development of systems to support NASA's new vision. Building a system to be fault tolerant increases the complexity and decreases the performance of included software. Standard bus design and conventional implementation produces natural bottlenecks. Configuring hardware components in systems containing common processors and DSPs is difficult initially and expensive or impossible to change later. The existence of Hardware Description Languages (HDLs), the recent increase in performance, density and radiation tolerance of Field Programmable Gate Arrays (FPGAs), and Intellectual Property (IP) Cores provides the technology for reprogrammable Systems on a Chip (SOC). This technology supports a paradigm better suited for NASA's vision. Hardware and software production are melded for more effective development; they can both evolve together over time. Designers incorporating this technology into future avionics can benefit from its flexibility. Systems can be designed with improved fault isolation and tolerance using hardware instead of software. Also, these designs can be protected from obsolescence problems where maintenance is compromised via component and vendor availability.To investigate the flexibility of this technology, the core of the Central Processing Unit and Input/Output Processor of the Space Shuttle AP101S Computer were prototyped in Verilog HDL and synthesized into an Altera Stratix FPGA