Online Timing Slack Measurement and its Application in Field-Programmable Gate Arrays

Reliability, power consumption and timing performance are key concerns for today's integrated circuits. Measurement techniques capable of quantifying the timing characteristics of a circuit, while it is operating, facilitate a range of benefits. Delay variation due to environmental and operational conditions, and degradation can be monitored by tracking changes in timing performance. Using the measurements in a closed-loop to control power supply voltage or clock frequency allows for the reduction of timing safety margins, leading to improvements in power consumption or throughput performance through the exploitation of better-than worst-case operation. This thesis describes a novel online timing slack measurement method which can directly measure the timing performance of a circuit, accurately and with minimal overhead. Enhancements allow for the improvement of absolute accuracy and resolution. A compilation flow is reported that can automatically instrument arbitrary circuits on FPGAs with the measurement circuitry. On its own this measurement method is able to track the "health" of an integrated circuit, from commissioning through its lifetime, warning of impending failure or instigating pre-emptive degradation mitigation techniques. The use of the measurement method in a closed-loop dynamic voltage and frequency scaling scheme has been demonstrated, achieving significant improvements in power consumption and throughput performance.Open Acces

Characterization of Interconnection Delays in FPGAS Due to Single Event Upsets and Mitigation

RÉSUMÉ L’utilisation incessante de composants électroniques à géométrie toujours plus faible a engendré de nouveaux défis au fil des ans. Par exemple, des semi-conducteurs à mémoire et à microprocesseur plus avancés sont utilisés dans les systèmes avioniques qui présentent une susceptibilité importante aux phénomènes de rayonnement cosmique. L'une des principales implications des rayons cosmiques, observée principalement dans les satellites en orbite, est l'effet d'événements singuliers (SEE). Le rayonnement atmosphérique suscite plusieurs préoccupations concernant la sécurité et la fiabilité de l'équipement avionique, en particulier pour les systèmes qui impliquent des réseaux de portes programmables (FPGA). Les FPGA à base de cellules de mémoire statique (SRAM) présentent une solution attrayante pour mettre en oeuvre des systèmes complexes dans le domaine de l’avionique. Les expériences de rayonnement réalisées sur les FPGA ont dévoilé la vulnérabilité de ces dispositifs contre un type particulier de SEE, à savoir, les événements singuliers de changement d’état (SEU). Un SEU est considérée comme le changement de l'état d'un élément bistable (c'est-à-dire, un bit-flip) dû à l'effet d'un ion, d'un proton ou d’un neutron énergétique. Cet effet est non destructif et peut être corrigé en réécrivant la partie de la SRAM affectée. Les changements de délai (DC) potentiels dus aux SEU affectant la mémoire de configuration de routage ont été récemment confirmés. Un des objectifs de cette thèse consiste à caractériser plus précisément les DC dans les FPGA causés par les SEU. Les DC observés expérimentalement sont présentés et la modélisation au niveau circuit de ces DC est proposée. Les circuits impliqués dans la propagation du délai sont validés en effectuant une modélisation précise des blocs internes à l'intérieur du FPGA et en exécutant des simulations. Les résultats montrent l’origine des DC qui sont en accord avec les mesures expérimentales de délais. Les modèles proposés au niveau circuit sont, aux meilleures de notre connaissance, le premier travail qui confirme et explique les délais combinatoires dans les FPGA. La conception d'un circuit moniteur de délai pour la détection des DC a été faite dans la deuxième partie de cette thèse. Ce moniteur permet de détecter un changement de délai sur les sections critiques du circuit et de prévenir les pannes de synchronisation engendrées par les SEU sans utiliser la redondance modulaire triple (TMR).----------ABSTRACT The unrelenting demand for electronic components with ever diminishing feature size have emerged new challenges over the years. Among them, more advanced memory and microprocessor semiconductors are being used in avionic systems that exhibit a substantial susceptibility to cosmic radiation phenomena. One of the main implications of cosmic rays, which was primarily observed in orbiting satellites, is single-event effect (SEE). Atmospheric radiation causes several concerns regarding the safety and reliability of avionics equipment, particularly for systems that involve field programmable gate arrays (FPGA). SRAM-based FPGAs, as an attractive solution to implement systems in aeronautic sector, are very susceptible to SEEs in particular Single Event Upset (SEU). An SEU is considered as the change of the state of a bistable element (i.e., bit-flip) due to the effect of an energetic ion or proton. This effect is non-destructive and may be fixed by rewriting the affected part. Sensitivity evaluation of SRAM-based FPGAs to a physical impact such as potential delay changes (DC) has not been addressed thus far in the literature. DCs induced by SEU can affect the functionality of the logic circuits by disturbing the race condition on critical paths. The objective of this thesis is toward the characterization of DCs in SRAM-based FPGAs due to transient ionizing radiation. The DCs observed experimentally are presented and the circuit-level modeling of those DCs is proposed. Circuits involved in delay propagation are reverse-engineered by performing precise modeling of internal blocks inside the FPGA and executing simulations. The results show the root cause of DCs that are in good agreement with experimental delay measurements. The proposed circuit level models are, to the best of our knowledge, the first work on modeling of combinational delays in FPGAs.In addition, the design of a delay monitor circuit for DC detection is investigated in the second part of this thesis. This monitor allowed to show experimentally cumulative DCs on interconnects in FPGA. To this end, by avoiding the use of triple modular redundancy (TMR), a mitigation technique for DCs is proposed and the system downtime is minimized. A method is also proposed to decrease the clock frequency after DC detection without interrupting the process

Asynchronous techniques for new generation variation-tolerant FPGA

PhD ThesisThis thesis presents a practical scenario for asynchronous logic implementation that would benefit the modern Field-Programmable Gate Arrays (FPGAs) technology in improving reliability. A method based on Asynchronously-Assisted Logic (AAL) blocks is proposed here in order to provide the right degree of variation tolerance, preserve as much of the traditional FPGAs structure as possible, and make use of asynchrony only when necessary or beneficial for functionality. The newly proposed AAL introduces extra underlying hard-blocks that support asynchronous interaction only when needed and at minimum overhead. This has the potential to avoid the obstacles to the progress of asynchronous designs, particularly in terms of area and power overheads. The proposed approach provides a solution that is complementary to existing variation tolerance techniques such as the late-binding technique, but improves the reliability of the system as well as reducing the design’s margin headroom when implemented on programmable logic devices (PLDs) or FPGAs. The proposed method suggests the deployment of configurable AAL blocks to reinforce only the variation-critical paths (VCPs) with the help of variation maps, rather than re-mapping and re-routing. The layout level results for this method's worst case increase in the CLB’s overall size only of 6.3%. The proposed strategy retains the structure of the global interconnect resources that occupy the lion’s share of the modern FPGA’s soft fabric, and yet permits the dual-rail iv completion-detection (DR-CD) protocol without the need to globally double the interconnect resources. Simulation results of global and interconnect voltage variations demonstrate the robustness of the method

Design and Evaluation of a Hardware System for Online Signal Processing within Mobile Brain-Computer Interfaces

Brain-Computer Interfaces (BCIs) sind innovative Systeme, die eine direkte Kommunikation zwischen dem Gehirn und externen Geräten ermöglichen. Diese Schnittstellen haben sich zu einer transformativen Lösung nicht nur für Menschen mit neurologischen Verletzungen entwickelt, sondern auch für ein breiteres Spektrum von Menschen, das sowohl medizinische als auch nicht-medizinische Anwendungen umfasst. In der Vergangenheit hat die Herausforderung, dass neurologische Verletzungen nach einer anfänglichen Erholungsphase statisch bleiben, die Forscher dazu veranlasst, innovative Wege zu beschreiten. Seit den 1970er Jahren stehen BCIs an vorderster Front dieser Bemühungen. Mit den Fortschritten in der Forschung haben sich die BCI-Anwendungen erweitert und zeigen ein großes Potenzial für eine Vielzahl von Anwendungen, auch für weniger stark eingeschränkte (zum Beispiel im Kontext von Hörelektronik) sowie völlig gesunde Menschen (zum Beispiel in der Unterhaltungsindustrie). Die Zukunft der BCI-Forschung hängt jedoch auch von der Verfügbarkeit zuverlässiger BCI-Hardware ab, die den Einsatz in der realen Welt gewährleistet. Das im Rahmen dieser Arbeit konzipierte und implementierte CereBridge-System stellt einen bedeutenden Fortschritt in der Brain-Computer-Interface-Technologie dar, da es die gesamte Hardware zur Erfassung und Verarbeitung von EEG-Signalen in ein mobiles System integriert. Die Architektur der Verarbeitungshardware basiert auf einem FPGA mit einem ARM Cortex-M3 innerhalb eines heterogenen ICs, was Flexibilität und Effizienz bei der EEG-Signalverarbeitung gewährleistet. Der modulare Aufbau des Systems, bestehend aus drei einzelnen Boards, gewährleistet die Anpassbarkeit an unterschiedliche Anforderungen. Das komplette System wird an der Kopfhaut befestigt, kann autonom arbeiten, benötigt keine externe Interaktion und wiegt einschließlich der 16-Kanal-EEG-Sensoren nur ca. 56 g. Der Fokus liegt auf voller Mobilität. Das vorgeschlagene anpassbare Datenflusskonzept erleichtert die Untersuchung und nahtlose Integration von Algorithmen und erhöht die Flexibilität des Systems. Dies wird auch durch die Möglichkeit unterstrichen, verschiedene Algorithmen auf EEG-Daten anzuwenden, um unterschiedliche Anwendungsziele zu erreichen. High-Level Synthesis (HLS) wurde verwendet, um die Algorithmen auf das FPGA zu portieren, was den Algorithmenentwicklungsprozess beschleunigt und eine schnelle Implementierung von Algorithmusvarianten ermöglicht. Evaluierungen haben gezeigt, dass das CereBridge-System in der Lage ist, die gesamte Signalverarbeitungskette zu integrieren, die für verschiedene BCI-Anwendungen erforderlich ist. Darüber hinaus kann es mit einer Batterie von mehr als 31 Stunden Dauerbetrieb betrieben werden, was es zu einer praktikablen Lösung für mobile Langzeit-EEG-Aufzeichnungen und reale BCI-Studien macht. Im Vergleich zu bestehenden Forschungsplattformen bietet das CereBridge-System eine bisher unerreichte Leistungsfähigkeit und Ausstattung für ein mobiles BCI. Es erfüllt nicht nur die relevanten Anforderungen an ein mobiles BCI-System, sondern ebnet auch den Weg für eine schnelle Übertragung von Algorithmen aus dem Labor in reale Anwendungen. Im Wesentlichen liefert diese Arbeit einen umfassenden Entwurf für die Entwicklung und Implementierung eines hochmodernen mobilen EEG-basierten BCI-Systems und setzt damit einen neuen Standard für BCI-Hardware, die in der Praxis eingesetzt werden kann.Brain-Computer Interfaces (BCIs) are innovative systems that enable direct communication between the brain and external devices. These interfaces have emerged as a transformative solution not only for individuals with neurological injuries, but also for a broader range of individuals, encompassing both medical and non-medical applications. Historically, the challenge of neurological injury being static after an initial recovery phase has driven researchers to explore innovative avenues. Since the 1970s, BCIs have been at one forefront of these efforts. As research has progressed, BCI applications have expanded, showing potential in a wide range of applications, including those for less severely disabled (e.g. in the context of hearing aids) and completely healthy individuals (e.g. entertainment industry). However, the future of BCI research also depends on the availability of reliable BCI hardware to ensure real-world application. The CereBridge system designed and implemented in this work represents a significant leap forward in brain-computer interface technology by integrating all EEG signal acquisition and processing hardware into a mobile system. The processing hardware architecture is centered around an FPGA with an ARM Cortex-M3 within a heterogeneous IC, ensuring flexibility and efficiency in EEG signal processing. The modular design of the system, consisting of three individual boards, ensures adaptability to different requirements. With a focus on full mobility, the complete system is mounted on the scalp, can operate autonomously, requires no external interaction, and weighs approximately 56g, including 16 channel EEG sensors. The proposed customizable dataflow concept facilitates the exploration and seamless integration of algorithms, increasing the flexibility of the system. This is further underscored by the ability to apply different algorithms to recorded EEG data to meet different application goals. High-Level Synthesis (HLS) was used to port algorithms to the FPGA, accelerating the algorithm development process and facilitating rapid implementation of algorithm variants. Evaluations have shown that the CereBridge system is capable of integrating the complete signal processing chain required for various BCI applications. Furthermore, it can operate continuously for more than 31 hours with a 1800mAh battery, making it a viable solution for long-term mobile EEG recording and real-world BCI studies. Compared to existing research platforms, the CereBridge system offers unprecedented performance and features for a mobile BCI. It not only meets the relevant requirements for a mobile BCI system, but also paves the way for the rapid transition of algorithms from the laboratory to real-world applications. In essence, this work provides a comprehensive blueprint for the development and implementation of a state-of-the-art mobile EEG-based BCI system, setting a new benchmark in BCI hardware for real-world applicability

The Design For An Aerial Monitoring System For Environmental Surveillance Applications

Natural hazards are occurring at an alarming rate around the world. Before beginning suitable rescue and aid efforts in a disaster-stricken area, it is required to conduct an investigation. Military officials often must patrol risky locations to seek any potential threat, illegal activity, or intrusion within a country's borders that can put the lives of inhabitants in jeopardy. Such locations carry a very significant risk to human life. Other than UAVs or high-tech drones, nanosatellites such as CanSat can be utilized for aerial surveillance and monitoring in Unmanned Aerial Systems (UAS). It can also provide real-time data to a control room or computer. The telemetry type of CanSat is utilized in this project to gather and send data from the flight and environmental conditions in real-time for processing by a base station. The major parts employed in the CanSat design are the microcontroller and power supply. In addition to those stated above, the mission may incorporate other elements. These FPGAs in spacecraft enable more efficient processing by transferring the design to hardware. There are many difficulties in designing nanosatellites such as CanSat. Firstly, is difficult in designing nanosatellites using FPGAs technology and integrate them with the sensors because FPGAs consist of simple logic elements, which can be combined to implement the peripherals previously mentioned, but only interact with most other digital electronics. The design of CanSat needs to fit the microcontroller as the main unit with all the major subsystems found in a satellite, such as power, sensors, and a communication system, into the minimal volume. Besides, using those microcontrollers is less efficient to get the high-speed real-time data in an aerial surveillance application. The primary goal of this work is to develop a telemetry CanSat utilizing an FPGA DE10-Lite Development Board (Altera Max 10), Arduino Uno R3 Microcontroller, and an appropriate sensor (Temperature and humidity sensor, GPS Module, Barometric Sensor, Accelerometer Sensor) and a wireless communication system. The CanSat will then monitor and collect real-time telemetry data from a ground station. Finally, the telemetry data from various places and altitudes below 1km will be analyzed

High-level synthesis design of scalable ultrafast ultrasound beamformer with single FPGA

Ultrafast ultrasound imaging is essential for advanced ultrasound imaging techniques such as ultrasound localization microscopy (ULM) and functional ultrasound (fUS). Current ultrafast ultrasound imaging is challenged by the ultrahigh data bandwidth associated with the radio frequency (RF) signal, and by the latency of the computationally expensive beamforming process. As such, continuous ultrafast data acquisition and beamforming remain elusive with existing software beamformers based on CPUs or GPUs. To address these challenges, the proposed work introduces a novel method of implementing an ultrafast ultrasound beamformer specifically for ultrafast plane wave imaging (PWI) on a field programmable gate array (FPGA) by using high-level synthesis. A parallelized implementation of the beamformer on a single FPGA was proposed by 1) utilizing a delay compression technique to reduce the delay profile size, which enables both run-time pre-calculated delay profile loading from external memory and delay reuse 2) vectorizing channel data fetching which is enabled by delay reuse, and 3) using fixed summing networks to reduce consumption of logic resources. Our proposed method presents two unique advantages over current FPGA beamformers: 1) high scalability that allows fast adaptation to different FPGA resources and beamforming speed demands by using Xilinx High-Level Synthesis as the development tool, and 2) allow a compact form factor design by using a single FPGA to complete the beamforming instead of multiple FPGAs. With the proposed method, a sustainable average beamforming rate of 4.83 G samples/second in terms of input raw RF sample was achieved. The resulting image quality of the proposed beamformer was compared with the software beamformer on the Verasonics Vantage system for both phantom imaging and in vivo imaging of a mouse brain

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.