Single event upset testing of flash based field programmable gate arrays

In the last 50 years microelectronics have advanced at an exponential rate, causing microelectronic devices to shrink, have very low operating voltages and increased complexities; all this has made circuits more sensitive to various kinds of failures. These trends allowed soft errors, which up until recently was just a concern for space application, to become a major source of system failures of electronic products. The aim of this research paper was to investigate different mitigation techniques that prevent these soft errors in a Video Graphics Array (VGA) controller which is commonly used in projecting images captured by cameras. This controller was implemented on a Flash Based Field Programmable Gate array (FPGA). A test set-up was designed and implemented at NRF iThemba LABS, which was used to conduct the experiments necessary to evaluate the effectiveness of different mitigation techniques. The set-up was capable of handling multiple Device Under Tests (DUT) and had the ability to change the angle of incidence of each DUT. The DUTs were radiated with a 66MeV proton beam while the monitoring equipment observed any errors that had occurred. The results obtained indicated that all the implemented mitigation techniques tested on the VGA system improved the system’s capability of mitigating Single Event Upsets (SEU). The most effective mitigation technique was the OR-AND Multiplexer Single Event Transient (SET) filter technique. It was thus shown that mitigation techniques are viable options to prevent SEU in a VGA controller. The permanent SEU testing set-up which was designed and manufactured and was used to conduct the experiments, proved to be a practical option for further microelectronics testing at iThemba LABS

Mitigation of single event upsets in a XILINX ARTIX-7 field programmable gate array

Field programmable gate arrays are increasingly being used in harsh environments like space where high energy particles from radiation affect the integrity of the data. Before deployment of satellites in space, characterisation and consequently mitigation of radiation effects is necessary to avoid failure. By irradiating a digital microelectronic device, using accelerated energetic particles, it is possible to predict the likelihood of an event effect happening. Such irradiation tests can only be done at a particle accelerator facility such as iThemba LABS in Cape Town. It is the one of the few particle accelerators in the southern hemisphere and offers the capacity to perform these event effect characterisation tests. Triple Modular Redundancy (TMR) is a commonly used mitigation technique in microelectronics. Although effective, it has the downside of increased resource area. A DMR-Filter combination mitigation technique was developed at the Nelson Mandela University. It uses fewer resources than TMR and it is envisaged to significantly reduce event upsets in a FPGA. This research project seeks to investigate the effectiveness of the DMR-Filter combination mitigation technique in reducing the likelihood of event upsets occurring in Xilinx’s Artix-7 FPGA when exposed to highly accelerated particles, similar to those in space

High-performance hardware accelerators for image processing in space applications

Mars is a hard place to reach. While there have been many notable success stories in getting probes to the Red Planet, the historical record is full of bad news. The success rate for actually landing on the Martian surface is even worse, roughly 30%. This low success rate must be mainly credited to the Mars environment characteristics. In the Mars atmosphere strong winds frequently breath. This phenomena usually modifies the lander descending trajectory diverging it from the target one. Moreover, the Mars surface is not the best place where performing a safe land. It is pitched by many and close craters and huge stones, and characterized by huge mountains and hills (e.g., Olympus Mons is 648 km in diameter and 27 km tall). For these reasons a mission failure due to a landing in huge craters, on big stones or on part of the surface characterized by a high slope is highly probable. In the last years, all space agencies have increased their research efforts in order to enhance the success rate of Mars missions. In particular, the two hottest research topics are: the active debris removal and the guided landing on Mars. The former aims at finding new methods to remove space debris exploiting unmanned spacecrafts. These must be able to autonomously: detect a debris, analyses it, in order to extract its characteristics in terms of weight, speed and dimension, and, eventually, rendezvous with it. In order to perform these tasks, the spacecraft must have high vision capabilities. In other words, it must be able to take pictures and process them with very complex image processing algorithms in order to detect, track and analyse the debris. The latter aims at increasing the landing point precision (i.e., landing ellipse) on Mars. Future space-missions will increasingly adopt Video Based Navigation systems to assist the entry, descent and landing (EDL) phase of space modules (e.g., spacecrafts), enhancing the precision of automatic EDL navigation systems. For instance, recent space exploration missions, e.g., Spirity, Oppurtunity, and Curiosity, made use of an EDL procedure aiming at following a fixed and precomputed descending trajectory to reach a precise landing point. This approach guarantees a maximum landing point precision of 20 km. By comparing this data with the Mars environment characteristics, it is possible to understand how the mission failure probability still remains really high. A very challenging problem is to design an autonomous-guided EDL system able to even more reduce the landing ellipse, guaranteeing to avoid the landing in dangerous area of Mars surface (e.g., huge craters or big stones) that could lead to the mission failure. The autonomous behaviour of the system is mandatory since a manual driven approach is not feasible due to the distance between Earth and Mars. Since this distance varies from 56 to 100 million of km approximately due to the orbit eccentricity, even if a signal transmission at the light speed could be possible, in the best case the transmission time would be around 31 minutes, exceeding so the overall duration of the EDL phase. In both applications, algorithms must guarantee self-adaptability to the environmental conditions. Since the Mars (and in general the space) harsh conditions are difficult to be predicted at design time, these algorithms must be able to automatically tune the internal parameters depending on the current conditions. Moreover, real-time performances are another key factor. Since a software implementation of these computational intensive tasks cannot reach the required performances, these algorithms must be accelerated via hardware. For this reasons, this thesis presents my research work done on advanced image processing algorithms for space applications and the associated hardware accelerators. My research activity has been focused on both the algorithm and their hardware implementations. Concerning the first aspect, I mainly focused my research effort to integrate self-adaptability features in the existing algorithms. While concerning the second, I studied and validated a methodology to efficiently develop, verify and validate hardware components aimed at accelerating video-based applications. This approach allowed me to develop and test high performance hardware accelerators that strongly overcome the performances of the actual state-of-the-art implementations. The thesis is organized in four main chapters. Chapter 2 starts with a brief introduction about the story of digital image processing. The main content of this chapter is the description of space missions in which digital image processing has a key role. A major effort has been spent on the missions in which my research activity has a substantial impact. In particular, for these missions, this chapter deeply analizes and evaluates the state-of-the-art approaches and algorithms. Chapter 3 analyzes and compares the two technologies used to implement high performances hardware accelerators, i.e., Application Specific Integrated Circuits (ASICs) and Field Programmable Gate Arrays (FPGAs). Thanks to this information the reader may understand the main reasons behind the decision of space agencies to exploit FPGAs instead of ASICs for high-performance hardware accelerators in space missions, even if FPGAs are more sensible to Single Event Upsets (i.e., transient error induced on hardware component by alpha particles and solar radiation in space). Moreover, this chapter deeply describes the three available space-grade FPGA technologies (i.e., One-time Programmable, Flash-based, and SRAM-based), and the main fault-mitigation techniques against SEUs that are mandatory for employing space-grade FPGAs in actual missions. Chapter 4 describes one of the main contribution of my research work: a library of high-performance hardware accelerators for image processing in space applications. The basic idea behind this library is to offer to designers a set of validated hardware components able to strongly speed up the basic image processing operations commonly used in an image processing chain. In other words, these components can be directly used as elementary building blocks to easily create a complex image processing system, without wasting time in the debug and validation phase. This library groups the proposed hardware accelerators in IP-core families. The components contained in a same family share the same provided functionality and input/output interface. This harmonization in the I/O interface enables to substitute, inside a complex image processing system, components of the same family without requiring modifications to the system communication infrastructure. In addition to the analysis of the internal architecture of the proposed components, another important aspect of this chapter is the methodology used to develop, verify and validate the proposed high performance image processing hardware accelerators. This methodology involves the usage of different programming and hardware description languages in order to support the designer from the algorithm modelling up to the hardware implementation and validation. Chapter 5 presents the proposed complex image processing systems. In particular, it exploits a set of actual case studies, associated with the most recent space agency needs, to show how the hardware accelerator components can be assembled to build a complex image processing system. In addition to the hardware accelerators contained in the library, the described complex system embeds innovative ad-hoc hardware components and software routines able to provide high performance and self-adaptable image processing functionalities. To prove the benefits of the proposed methodology, each case study is concluded with a comparison with the current state-of-the-art implementations, highlighting the benefits in terms of performances and self-adaptability to the environmental conditions

Firmware Development and Integration for ALICE TPC and PHOS Front-end Electronics: A Trigger Based Readout and Control System operating in a Radiation Environment

The readout electronics in PHOS and TPC - two of the major detectors of the ALICE experiment at the LHC - consist of a set of Front End Cards (FECs) that digitize, process and buffer the data from the detector sensors. The FECs are connected to a Readout Control Unit (RCU) via two sets of custom made PCB backplanes. For PHOS, 28 FECs are connected to one RCU, while for TPC the number is varying from 18 to 25 FECs depending on location. The RCU is in charge of the data readout, including reception and distribution of triggers and in moving the data from the FECs to the Data Acquisition System. In addition it does low level control tasks. The RCU consists of an RCU Motherboard that hosts a Detector Control System (DCS) board and a Source Interface Unit. The DCS board is an embedded computer running Linux that controls the readout electronics. All the mentioned devices are implemented in commercial grade SRAM based Field Programmable Gate Arrays (FPGAs). Even if these devices are not very radiation tolerant, they are chosen because of their cost and flexibility, and most importantly the possibility to easily do future upgrades of the electronics. Since physical shielding of the electronics is not possible in ALICE due to the architecture of the detector, the radiation related errors need to be handled with other techniques such as firmware mitigation techniques. The main objective of this thesis has been to make firmware modules for the FPGAs reciding in different parts of the readout electronics. Because of the flexibility of the designs, some of them have, with minor adaptations, been applied in different devices surrounding the readout electronics. Additionally, effort has been put into testing and integration of the system. In detail, the work presented in this thesis can be summarized as follows: - Firmware design for radiation environments. All firmware modules that are designed are to be used in a radiation environment, and then special precautions need to be taken. Additionally, a state-of-the-art solution has been designed for protecting the main FPGA on the RCU Motherboard against radiation induced functional failures. - Implementation of Trigger Handling for the TPC/PHOS Readout Electronics. The triggers are received from the global trigger system via an optical link and are handled by an Application Spesific Integrated Circuit (ASIC) on the DCS board. The problem is that the DCS board might have occasional down time 6 due to radiation related errors, so a special interface module is designed for the main FPGA on the RCU Motherboard. This module decodes and verifies the information received from the trigger system. As it is a generic design it has also been implemented as part of the BusyBox. The BusyBox is an important device in the trigger path of the TPC and PHOS sub-detectors. - Testing and Verification of all firmware modules. All firmware modules have been extensively verified with computer simulation before being tested in real hardware. - Maintenance of the DCS board for TPC/PHOS and of the different Fee firmware modules in general. - System Integration and System Level Tests. A big contribution has been done integrating and testing all the modules and sub-systems. This concern both locally on the RCU and the BusyBox, as well as making all the devices play together on a larger scale. - Testing and Verification of all firmware modules. All firmware modules have been extensively verified with computer simulation before being tested in real hardware. - Maintenance of the DCS board for TPC/PHOS and of the different Fee firmware modules in general. - System Integration and System Level Tests. A big contribution has been done integrating and testing all the modules and sub-systems. This concern both locally on the RCU and the BusyBox, as well as making all the devices play together on a larger scale. As the presented electronics are located in a radiation environment and are physically unavailable after commissioning, effort has been put into making designs that are reliable, scalable and possible to upgrade. This has been ensured by following a systematic design approach where testability, version management and documentation are key elements. Some parts of the work described in this thesis have been published and presented in international peer reviewed publications and conferences

Low-Power and Programmable Analog Circuitry for Wireless Sensors

Embedding networks of secure, wirelessly-connected sensors and actuators will help us to conscientiously manage our local and extended environments. One major challenge for this vision is to create networks of wireless sensor devices that provide maximal knowledge of their environment while using only the energy that is available within that environment. In this work, it is argued that the energy constraints in wireless sensor design are best addressed by incorporating analog signal processors. The low power-consumption of an analog signal processor allows persistent monitoring of multiple sensors while the device\u27s analog-to-digital converter, microcontroller, and transceiver are all in sleep mode. This dissertation describes the development of analog signal processing integrated circuits for wireless sensor networks. Specific technology problems that are addressed include reconfigurable processing architectures for low-power sensing applications, as well as the development of reprogrammable biasing for analog circuits

Low-Power and Programmable Analog Circuitry for Wireless Sensors

Embedding networks of secure, wirelessly-connected sensors and actuators will help us to conscientiously manage our local and extended environments. One major challenge for this vision is to create networks of wireless sensor devices that provide maximal knowledge of their environment while using only the energy that is available within that environment. In this work, it is argued that the energy constraints in wireless sensor design are best addressed by incorporating analog signal processors. The low power-consumption of an analog signal processor allows persistent monitoring of multiple sensors while the device\u27s analog-to-digital converter, microcontroller, and transceiver are all in sleep mode. This dissertation describes the development of analog signal processing integrated circuits for wireless sensor networks. Specific technology problems that are addressed include reconfigurable processing architectures for low-power sensing applications, as well as the development of reprogrammable biasing for analog circuits

Digital neural circuits : from ions to networks

PhD ThesisThe biological neural computational mechanism is always fascinating to human beings since it shows several state-of-the-art characteristics: strong fault tolerance, high power efficiency and self-learning capability. These behaviours lead the developing trend of designing the next-generation digital computation platform. Thus investigating and understanding how the neurons talk with each other is the key to replicating these calculation features. In this work I emphasize using tailor-designed digital circuits for exactly implementing bio-realistic neural network behaviours, which can be considered a novel approach to cognitive neural computation. The first advance is that biological real-time computing performances allow the presented circuits to be readily adapted for real-time closed-loop in vitro or in vivo experiments, and the second one is a transistor-based circuit that can be directly translated into an impalpable chip for high-level neurologic disorder rehabilitations. In terms of the methodology, first I focus on designing a heterogeneous or multiple-layer-based architecture for reproducing the finest neuron activities both in voltage-and calcium-dependent ion channels. In particular, a digital optoelectronic neuron is developed as a case study. Second, I focus on designing a network-on-chip architecture for implementing a very large-scale neural network (e.g. more than 100,000) with human cognitive functions (e.g. timing control mechanism). Finally, I present a reliable hybrid bio-silicon closed-loop system for central pattern generator prosthetics, which can be considered as a framework for digital neural circuit-based neuro-prosthesis implications. At the end, I present the general digital neural circuit design principles and the long-term social impacts of the presented work

Nouvelles Architectures Hybrides (Logique / Mémoires Non-Volatiles et technologies associées.)

Les nouvelles approches de technologies mémoires permettront une intégration dite back-end, où les cellules élémentaires de stockage seront fabriquées lors des dernières étapes de réalisation à grande échelle du circuit. Ces approches innovantes sont souvent basées sur l'utilisation de matériaux actifs présentant deux états de résistance distincts. Le passage d'un état à l'autre est contrôlé en courant ou en tension donnant lieu à une caractéristique I-V hystérétique. Nos mémoires résistives sont composées d'argent en métal électrochimiquement actif et de sulfure amorphe agissant comme électrolyte. Leur fonctionnement repose sur la formation réversible et la dissolution d'un filament conducteur. Le potentiel d'application de ces nouveaux dispositifs n'est pas limité aux mémoires ultra-haute densité mais aussi aux circuits embarqués. En empilant ces mémoires dans la troisième dimension au niveau des interconnections des circuits logiques CMOS, de nouvelles architectures hybrides et innovantes deviennent possibles. Il serait alors envisageable d'exploiter un fonctionnement à basse énergie, à haute vitesse d'écriture/lecture et de haute performance telles que l'endurance et la rétention. Dans cette thèse, en se concentrant sur les aspects de la technologie de mémoire en vue de développer de nouvelles architectures, l'introduction d'une fonctionnalité non-volatile au niveau logique est démontrée par trois circuits hybrides: commutateurs de routage non volatiles dans un Field Programmable Gate Arrays, un 6T-SRAM non volatile, et les neurones stochastiques pour un réseau neuronal. Pour améliorer les solutions existantes, les limitations de la performances des dispositifs mémoires sont identifiés et résolus avec des nouveaux empilements ou en fournissant des défauts de circuits tolérants.Novel approaches in the field of memory technology should enable backend integration, where individual storage nodes will be fabricated during the last fabrication steps of the VLSI circuit. In this case, memory operation is often based upon the use of active materials with resistive switching properties. A topology of resistive memory consists of silver as electrochemically active metal and amorphous sulfide acting as electrolyte and relies on the reversible formation and dissolution of a conductive filament. The application potential of these new memories is not limited to stand-alone (ultra-high density), but is also suitable for embedded applications. By stacking these memories in the third dimension at the interconnection level of CMOS logic, new ultra-scalable hybrid architectures becomes possible which exploit low energy operation, fast write/read access and high performance with respect to endurance and retention. In this thesis, focusing on memory technology aspects in view of developing new architectures, the introduction of non-volatile functionality at the logic level is demonstrated through three hybrid (CMOS logic ReRAM devices) circuits: nonvolatile routing switches in a Field Programmable Gate Array, nonvolatile 6T-SRAMs, and stochastic neurons of an hardware neural network. To be competitive or even improve existing solutions, limitations on the memory devices performances are identified and solved by stack engineering of CBRAM devices or providing faults tolerant circuits.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF