A built-in self-test technique for high speed analog-to-digital converters

Fundação para a Ciência e a Tecnologia (FCT) - PhD grant (SFRH/BD/62568/2009

Towards the development of flexible, reliable, reconfigurable, and high-performance imaging systems

Current FPGAs can implement large systems because of the high density of reconfigurable logic resources in a single chip. FPGAs are comprehensive devices that combine flexibility and high performance in the same platform compared to other platform such as General-Purpose Processors (GPPs) and Application Specific Integrated Circuits (ASICs). The flexibility of modern FPGAs is further enhanced by introducing Dynamic Partial Reconfiguration (DPR) feature, which allows for changing the functionality of part of the system while other parts are functioning. FPGAs became an important platform for digital image processing applications because of the aforementioned features. They can fulfil the need of efficient and flexible platforms that execute imaging tasks efficiently as well as the reliably with low power, high performance and high flexibility. The use of FPGAs as accelerators for image processing outperforms most of the current solutions. Current FPGA solutions can to load part of the imaging application that needs high computational power on dedicated reconfigurable hardware accelerators while other parts are working on the traditional solution to increase the system performance. Moreover, the use of the DPR feature enhances the flexibility of image processing further by swapping accelerators in and out at run-time. The use of fault mitigation techniques in FPGAs enables imaging applications to operate in harsh environments following the fact that FPGAs are sensitive to radiation and extreme conditions. The aim of this thesis is to present a platform for efficient implementations of imaging tasks. The research uses FPGAs as the key component of this platform and uses the concept of DPR to increase the performance, flexibility, to reduce the power dissipation and to expand the cycle of possible imaging applications. In this context, it proposes the use of FPGAs to accelerate the Image Processing Pipeline (IPP) stages, the core part of most imaging devices. The thesis has a number of novel concepts. The first novel concept is the use of FPGA hardware environment and DPR feature to increase the parallelism and achieve high flexibility. The concept also increases the performance and reduces the power consumption and area utilisation. Based on this concept, the following implementations are presented in this thesis: An implementation of Adams Hamilton Demosaicing algorithm for camera colour interpolation, which exploits the FPGA parallelism to outperform other equivalents. In addition, an implementation of Automatic White Balance (AWB), another IPP stage that employs DPR feature to prove the mentioned novelty aspects. Another novel concept in this thesis is presented in chapter 6, which uses DPR feature to develop a novel flexible imaging system that requires less logic and can be implemented in small FPGAs. The system can be employed as a template for any imaging application with no limitation. Moreover, discussed in this thesis is a novel reliable version of the imaging system that adopts novel techniques including scrubbing, Built-In Self Test (BIST), and Triple Modular Redundancy (TMR) to detect and correct errors using the Internal Configuration Access Port (ICAP) primitive. These techniques exploit the datapath-based nature of the implemented imaging system to improve the system's overall reliability. The thesis presents a proposal for integrating the imaging system with the Robust Reliable Reconfigurable Real-Time Heterogeneous Operating System (R4THOS) to get the best out of the system. The proposal shows the suitability of the proposed DPR imaging system to be used as part of the core system of autonomous cars because of its unbounded flexibility. These novel works are presented in a number of publications as shown in section 1.3 later in this thesis

High performance communication on reconfigurable clusters

High Performance Computing (HPC) has matured to where it is an essential third pillar, along with theory and experiment, in most domains of science and engineering. Communication latency is a key factor that is limiting the performance of HPC, but can be addressed by integrating communication into accelerators. This integration allows accelerators to communicate with each other without CPU interactions, and even bypassing the network stack. Field Programmable Gate Arrays (FPGAs) are the accelerators that currently best integrate communication with computation. The large number of Multi-gigabit Transceivers (MGTs) on most high-end FPGAs can provide high-bandwidth and low-latency inter-FPGA connections. Additionally, the reconfigurable FPGA fabric enables tight coupling between computation kernel and network interface. Our thesis is that an application-aware communication infrastructure for a multi-FPGA system makes substantial progress in solving the HPC communication bottleneck. This dissertation aims to provide an application-aware solution for communication infrastructure for FPGA-centric clusters. Specifically, our solution demonstrates application-awareness across multiple levels in the network stack, including low-level link protocols, router microarchitectures, routing algorithms, and applications. We start by investigating the low-level link protocol and the impact of its latency variance on performance. Our results demonstrate that, although some link jitter is always present, we can still assume near-synchronous communication on an FPGA-cluster. This provides the necessary condition for statically-scheduled routing. We then propose two novel router microarchitectures for two different kinds of workloads: a wormhole Virtual Channel (VC)-based router for workloads with dynamic communication, and a statically-scheduled Virtual Output Queueing (VOQ)-based router for workloads with static communication. For the first (VC-based) router, we propose a framework that generates application-aware router configurations. Our results show that, by adding application-awareness into router configuration, the network performance of FPGA clusters can be substantially improved. For the second (VOQ-based) router, we propose a novel offline collective routing algorithm. This shows a significant advantage over a state-of-the-art collective routing algorithm. We apply our communication infrastructure to a critical strong-scaling HPC kernel, the 3D FFT. The experimental results demonstrate that the performance of our design is faster than that on CPUs and GPUs by at least one order of magnitude (achieving strong scaling for the target applications). Surprisingly, the FPGA cluster performance is similar to that of an ASIC-cluster. We also implement the 3D FFT on another multi-FPGA platform: the Microsoft Catapult II cloud. Its performance is also comparable or superior to CPU and GPU HPC clusters. The second application we investigate is Molecular Dynamics Simulation (MD). We model MD on both FPGA clouds and clusters. We find that combining processing and general communication in the same device leads to extremely promising performance and the prospect of MD simulations well into the us/day range with a commodity cloud

Optimising and evaluating designs for reconfigurable hardware

Growing demand for computational performance, and the rising cost for chip design and manufacturing make reconfigurable hardware increasingly attractive for digital system implementation. Reconfigurable hardware, such as field-programmable gate arrays (FPGAs), can deliver performance through parallelism while also providing flexibility to enable application builders to reconfigure them. However, reconfigurable systems, particularly those involving run-time reconfiguration, are often developed in an ad-hoc manner. Such an approach usually results in low designer productivity and can lead to inefficient designs. This thesis covers three main achievements that address this situation. The first achievement is a model that captures design parameters of reconfigurable hardware and performance parameters of a given application domain. This model supports optimisations for several design metrics such as performance, area, and power consumption. The second achievement is a technique that enhances the relocatability of bitstreams for reconfigurable devices, taking into account heterogeneous resources. This method increases the flexibility of modules represented by these bitstreams while reducing configuration storage size and design compilation time. The third achievement is a technique to characterise the power consumption of FPGAs in different activity modes. This technique includes the evaluation of standby power and dedicated low-power modes, which are crucial in meeting the requirements for battery-based mobile devices

Microarchitectural Low-Power Design Techniques for Embedded Microprocessors

With the omnipresence of embedded processing in all forms of electronics today, there is a strong trend towards wireless, battery-powered, portable embedded systems which have to operate under stringent energy constraints. Consequently, low power consumption and high energy efficiency have emerged as the two key criteria for embedded microprocessor design. In this thesis we present a range of microarchitectural low-power design techniques which enable the increase of performance for embedded microprocessors and/or the reduction of energy consumption, e.g., through voltage scaling. In the context of cryptographic applications, we explore the effectiveness of instruction set extensions (ISEs) for a range of different cryptographic hash functions (SHA-3 candidates) on a 16-bit microcontroller architecture (PIC24). Specifically, we demonstrate the effectiveness of light-weight ISEs based on lookup table integration and microcoded instructions using finite state machines for operand and address generation. On-node processing in autonomous wireless sensor node devices requires deeply embedded cores with extremely low power consumption. To address this need, we present TamaRISC, a custom-designed ISA with a corresponding ultra-low-power microarchitecture implementation. The TamaRISC architecture is employed in conjunction with an ISE and standard cell memories to design a sub-threshold capable processor system targeted at compressed sensing applications. We furthermore employ TamaRISC in a hybrid SIMD/MIMD multi-core architecture targeted at moderate to high processing requirements (> 1 MOPS). A range of different microarchitectural techniques for efficient memory organization are presented. Specifically, we introduce a configurable data memory mapping technique for private and shared access, as well as instruction broadcast together with synchronized code execution based on checkpointing. We then study an inherent suboptimality due to the worst-case design principle in synchronous circuits, and introduce the concept of dynamic timing margins. We show that dynamic timing margins exist in microprocessor circuits, and that these margins are to a large extent state-dependent and that they are correlated to the sequences of instruction types which are executed within the processor pipeline. To perform this analysis we propose a circuit/processor characterization flow and tool called dynamic timing analysis. Moreover, this flow is employed in order to devise a high-level instruction set simulation environment for impact-evaluation of timing errors on application performance. The presented approach improves the state of the art significantly in terms of simulation accuracy through the use of statistical fault injection. The dynamic timing margins in microprocessors are then systematically exploited for throughput improvements or energy reductions via our proposed instruction-based dynamic clock adjustment (DCA) technique. To this end, we introduce a 6-stage 32-bit microprocessor with cycle-by-cycle DCA. Besides a comprehensive design flow and simulation environment for evaluation of the DCA approach, we additionally present a silicon prototype of a DCA-enabled OpenRISC microarchitecture fabricated in 28 nm FD-SOI CMOS. The test chip includes a suitable clock generation unit which allows for cycle-by-cycle DCA over a wide range with fine granularity at frequencies exceeding 1 GHz. Measurement results of speedups and power reductions are provided

Hardware-Based Particle Filter with Evolutionary Resampling Stage

Autonomous systems require, in most of the cases, reasoning and decision-making capabilities. Moreover, the decision process has to occur in real time. Real-time computing means that every situation or event has to have an answer before a temporal deadline. In complex applications, these deadlines are usually in the order of milliseconds or even microseconds if the application is very demanding. In order to comply with these timing requirements, computing tasks have to be performed as fast as possible. The problem arises when computations are no longer simple, but very time-consuming operations. A good example can be found in autonomous navigation systems with visual-tracking submodules where Kalman filtering is the most extended solution. However, in recent years, some interesting new approaches have been developed. Particle filtering, given its more general problem-solving features, has reached an important position in the field. The aim of this thesis is to design, implement and validate a hardware platform that constitutes itself an embedded intelligent system. The proposed system would combine particle filtering and evolutionary computation algorithms to generate intelligent behavior. Traditional approaches to particle filtering or evolutionary computation have been developed in software platforms, including parallel capabilities to some extent. In this work, an additional goal is fully exploiting hardware implementation advantages. By using the computational resources available in a FPGA device, better performance results in terms of computation time are expected. These hardware resources will be in charge of extensive repetitive computations. With this hardware-based implementation, real-time features are also expected

A Practical Hardware Implementation of Systemic Computation

It is widely accepted that natural computation, such as brain computation, is far superior to typical computational approaches addressing tasks such as learning and parallel processing. As conventional silicon-based technologies are about to reach their physical limits, researchers have drawn inspiration from nature to found new computational paradigms. Such a newly-conceived paradigm is Systemic Computation (SC). SC is a bio-inspired model of computation. It incorporates natural characteristics and defines a massively parallel non-von Neumann computer architecture that can model natural systems efficiently. This thesis investigates the viability and utility of a Systemic Computation hardware implementation, since prior software-based approaches have proved inadequate in terms of performance and flexibility. This is achieved by addressing three main research challenges regarding the level of support for the natural properties of SC, the design of its implied architecture and methods to make the implementation practical and efficient. Various hardware-based approaches to Natural Computation are reviewed and their compatibility and suitability, with respect to the SC paradigm, is investigated. FPGAs are identified as the most appropriate implementation platform through critical evaluation and the first prototype Hardware Architecture of Systemic computation (HAoS) is presented. HAoS is a novel custom digital design, which takes advantage of the inbuilt parallelism of an FPGA and the highly efficient matching capability of a Ternary Content Addressable Memory. It provides basic processing capabilities in order to minimize time-demanding data transfers, while the optional use of a CPU provides high-level processing support. It is optimized and extended to a practical hardware platform accompanied by a software framework to provide an efficient SC programming solution. The suggested platform is evaluated using three bio-inspired models and analysis shows that it satisfies the research challenges and provides an effective solution in terms of efficiency versus flexibility trade-off

Crypto-processeur architecture, programmation et évaluation de la sécurité

Les architectures des processeurs et coprocesseurs cryptographiques se montrent fréquemment vulnérables aux différents types d attaques ; en particulier, celles qui ciblent une révélation des clés chiffrées. Il est bien connu qu une manipulation des clés confidentielles comme des données standards par un processeur peut être considérée comme une menace. Ceci a lieu par exemple lors d un changement du code logiciel (malintentionné ou involontaire) qui peut provoquer que la clé confidentielle sorte en clair de la zone sécurisée. En conséquence, la sécurité de tout le système serait irréparablement menacée. L objectif que nous nous sommes fixé dans le travail présenté, était la recherche d architectures matérielles reconfigurables qui peuvent fournir une sécurité élevée des clés confidentielles pendant leur génération, leur enregistrement et leur échanges en implantant des modes cryptographiques de clés symétriques et des protocoles. La première partie de ce travail est destinée à introduire les connaissances de base de la cryptographie appliquée ainsi que de l électronique pour assurer une bonne compréhension des chapitres suivants. Deuxièmement, nous présentons un état de l art des menaces sur la confidentialité des clés secrètes dans le cas où ces dernières sont stockées et traitées dans un système embarqué. Pour lutter contre les menaces mentionnées, nous proposons alors de nouvelles règles au niveau du design de l architecture qui peuvent augmenter la résistance des processeurs et coprocesseurs cryptographiques contre les attaques logicielles. Ces règles prévoient une séparation des registres dédiés à l enregistrement de clés et ceux dédiés à l enregistrement de données : nous proposons de diviser le système en zones : de données, du chiffreur et des clés et à isoler ces zones les unes des autres au niveau du protocole, du système, de l architecture et au niveau physique. Ensuite, nous présentons un nouveau crypto-processeur intitulé HCrypt, qui intègre ces règles de séparation et qui assure ainsi une gestion sécurisée des clés. Mises à part les instructions relatives à la gestion sécurisée de clés, quelques instructions supplémentaires sont dédiées à une réalisation simple des modes de chiffrement et des protocoles cryptographiques. Dans les chapitres suivants, nous explicitons le fait que les règles de séparation suggérées, peuvent également être étendues à l architecture d un processeur généraliste et coprocesseur. Nous proposons ainsi un crypto-coprocesseur sécurisé qui est en mesure d être utilisé en relation avec d autres processeurs généralistes. Afin de démontrer sa flexibilité, le crypto-coprocesseur est interconnecté avec les processeurs soft-cores de NIOS II, de MicroBlaze et de Cortex M1. Par la suite, la résistance du crypto-processeur par rapport aux attaques DPA est testée. Sur la base de ces analyses, l architecture du processeur HCrypt est modifiée afin de simplifier sa protection contre les attaques par canaux cachés (SCA) et les attaques par injection de fautes (FIA). Nous expliquons aussi le fait qu une réorganisation des blocs au niveau macroarchitecture du processeur HCrypt, augmente la résistance du nouveau processeur HCrypt2 par rapport aux attaques de type DPA et FIA. Nous étudions ensuite les possibilités pour pouvoir reconfigurer dynamiquement les parties sélectionnées de l architecture du processeur crypto-coprocesseur. La reconfiguration dynamique peut être très utile lorsque l algorithme de chiffrement ou ses implantations doivent être changés en raison de l apparition d une vulnérabilité Finalement, la dernière partie de ces travaux de thèse, est destinée à l exécution des tests de fonctionnalité et des optimisations stricts des deux versions du cryptoprocesseur HCryptArchitectures of cryptographic processors and coprocessors are often vulnerable to different kinds of attacks, especially those targeting the disclosure of encryption keys. It is well known that manipulating confidential keys by the processor as ordinary data can represent a threat: a change in the program code (malicious or unintentional) can cause the unencrypted confidential key to leave the security area. This way, the security of the whole system would be irrecoverably compromised. The aim of our work was to search for flexible and reconfigurable hardware architectures, which can provide high security of confidential keys during their generation, storage and exchange while implementing common symmetric key cryptographic modes and protocols. In the first part of the manuscript, we introduce the bases of applied cryptography and of reconfigurable computing that are necessary for better understanding of the work. Second, we present threats to security of confidential keys when stored and processed within an embedded system. To counteract these threats, novel design rules increasing robustness of cryptographic processors and coprocessors against software attacks are presented. The rules suggest separating registers dedicated to key storage from those dedicated to data storage: we propose to partition the system into the data, cipher and key zone and to isolate the zones from each other at protocol, system, architectural and physical levels. Next, we present a novel HCrypt crypto-processor complying with the separation rules and thus ensuring secure key management. Besides instructions dedicated to secure key management, some additional instructions are dedicated to easy realization of block cipher modes and cryptographic protocols in general. In the next part of the manuscript, we show that the proposed separation principles can be extended also to a processor-coprocessor architecture. We propose a secure crypto-coprocessor, which can be used in conjunction with any general-purpose processor. To demonstrate its flexibility, the crypto-coprocessor is interconnected with the NIOS II, MicroBlaze and Cortex M1 soft-core processors. In the following part of the work, we examine the resistance of the HCrypt cryptoprocessor to differential power analysis (DPA) attacks. Following this analysis, we modify the architecture of the HCrypt processor in order to simplify its protection against side channel attacks (SCA) and fault injection attacks (FIA). We show that by rearranging blocks of the HCrypt processor at macroarchitecture level, the new HCrypt2 processor becomes natively more robust to DPA and FIA. Next, we study possibilities of dynamically reconfiguring selected parts of the processor - crypto-coprocessor architecture. The dynamic reconfiguration feature can be very useful when the cipher algorithm or its implementation must be changed in response to appearance of some vulnerability. Finally, the last part of the manuscript is dedicated to thorough testing and optimizations of both versions of the HCrypt crypto-processor. Architectures of crypto-processors and crypto-coprocessors are often vulnerable to software attacks targeting the disclosure of encryption keys. The thesis introduces separation rules enabling crypto-processor/coprocessors to support secure key management. Separation rules are implemented on novel HCrypt crypto-processor resistant to software attacks targetting the disclosure of encryption keysST ETIENNE-Bib. électronique (422189901) / SudocSudocFranceF

Design techniques to enhance low-power wireless communication soc with reconfigurability and wake up radio

Nowadays, Internet of things applications are increasing, and each end-node has more demanding requirements such as energy efficiency and speed. The thesis proposes a heterogeneous elaboration unit for smart power applications, that consists of an ultra-low-power microcontroller coupled with a small (around 1k equivalent gates) soft-core of embedded FPGA. This digital system is implemented in 90-nm BCD technology of STMicroelectronics, and through the analysis presented in this thesis proves to have good performance in terms of power consumption and latency. The idea is to increase the system performance exploiting the embedded FPGA to managing smart power tasks. For the intended applications, a remarkable computational load is not required, it is just required the implementation of simple finite state machines, since they are event-driven applications. In this way, while the microcontroller deals with other system computations such as high-level communications, the eFPGA can efficiently manage smart power applications. An added value of the proposed elaboration unit is that a soft-core approach is applied to the whole digital system including the eFPGA, and hence, it is portable to different technologies. On the other hand, the configurability improvement has a straightforward drawback of about a 20–27% area overhead. The eFPGA usage to manage smart power applications, allows the system to reduce the required energy per task from about 400 to around 800 times compared to a processor implementation. The eFPGA utilization improves also the latency performance of the system reaching from 8 to 145 times less latency in terms of clock cycles. The thesis also introduces the architecture of a nano-watt wake-up radio integrated circuit implemented in 90-nm BCD technology of STMicroelectronics. The wake-up radio is an auxiliary always-on radio for medium-range applications that allows the IoT end-nodes to drastically reduce the power consumption during the node idle-listening communication phase