Evaluation of advanced techniques for structural FPGA self-test

This thesis presents a comprehensive test generation framework for FPGA logic elements and interconnects. It is based on and extends the current state-of-the-art. The purpose of FPGA testing in this work is to achieve reliable reconfiguration for a FPGA-based runtime reconfigurable system. A pre-configuration test is performed on a portion of the FPGA before it is reconfigured as part of the system to ensure that the FPGA fabric is fault-free. The implementation platform is the Xilinx Virtex-5 FPGA family. Existing literature in FPGA testing is evaluated and reviewed thoroughly. The various approaches are compared against one another qualitatively and the approach most suitable to the target platform is chosen. The array testing method is employed in testing the FPGA logic for its low hardware overhead and optimal test time. All tests are additionally pipelined to reduce test application time and use a high test clock frequency. A hybrid fault model including both structural and functional faults is assumed. An algorithm for the optimization of the number of required FPGA test configurations is developed and implemented in Java using a pseudo-random set-covering heuristic. Optimal solutions are obtained for Virtex-5 logic slices. The algorithm effort is parameterizable with the number of loop iterations each of which take approximately one second for a Virtex-5 sliceL circuit. A flexible test architecture for interconnects is developed. Arbitrary wire types can be tested in the same test configuration with no hardware overhead. Furthermore, a routing algorithm is integrated with the test template generation to select the wires under test and route them appropriately. Nine test configurations are required to achieve full test coverage for the FPGA logic. For interconnect testing, a local router-based on depth-first graph traversal is implemented in Java as the basis for creating systematic interconnect test templates. Pent wire testing is additionally implemented as a proof of concept. The test clock frequency for all tests exceeds 170 MHz and the hardware overhead is always lower than seven CLBs. All implemented tests are parameterizable such that they can be applied to any portion of the FPGA regardless of size or position

Circuit design and analysis for on-FPGA communication systems

On-chip communication system has emerged as a prominently important subject in Very-Large- Scale-Integration (VLSI) design, as the trend of technology scaling favours logics more than interconnects. Interconnects often dictates the system performance, and, therefore, research for new methodologies and system architectures that deliver high-performance communication services across the chip is mandatory. The interconnect challenge is exacerbated in Field-Programmable Gate Array (FPGA), as a type of ASIC where the hardware can be programmed post-fabrication. Communication across an FPGA will be deteriorating as a result of interconnect scaling. The programmable fabrics, switches and the specific routing architecture also introduce additional latency and bandwidth degradation further hindering intra-chip communication performance. Past research efforts mainly focused on optimizing logic elements and functional units in FPGAs. Communication with programmable interconnect received little attention and is inadequately understood. This thesis is among the first to research on-chip communication systems that are built on top of programmable fabrics and proposes methodologies to maximize the interconnect throughput performance. There are three major contributions in this thesis: (i) an analysis of on-chip interconnect fringing, which degrades the bandwidth of communication channels due to routing congestions in reconfigurable architectures; (ii) a new analogue wave signalling scheme that significantly improves the interconnect throughput by exploiting the fundamental electrical characteristics of the reconfigurable interconnect structures. This new scheme can potentially mitigate the interconnect scaling challenges. (iii) a novel Dynamic Programming (DP)-network to provide adaptive routing in network-on-chip (NoC) systems. The DP-network architecture performs runtime optimization for route planning and dynamic routing which, effectively utilizes the in-silicon bandwidth. This thesis explores a new horizon in reconfigurable system design, in which new methodologies and concepts are proposed to enhance the on-FPGA communication throughput performance that is of vital importance in new technology processes

Fault and Defect Tolerant Computer Architectures: Reliable Computing With Unreliable Devices

This research addresses design of a reliable computer from unreliable device technologies. A system architecture is developed for a fault and defect tolerant (FDT) computer. Trade-offs between different techniques are studied and yield and hardware cost models are developed. Fault and defect tolerant designs are created for the processor and the cache memory. Simulation results for the content-addressable memory (CAM)-based cache show 90% yield with device failure probabilities of 3 x 10(-6), three orders of magnitude better than non fault tolerant caches of the same size. The entire processor achieves 70% yield with device failure probabilities exceeding 10(-6). The required hardware redundancy is approximately 15 times that of a non-fault tolerant design. While larger than current FT designs, this architecture allows the use of devices much more likely to fail than silicon CMOS. As part of model development, an improved model is derived for NAND Multiplexing. The model is the first accurate model for small and medium amounts of redundancy. Previous models are extended to account for dependence between the inputs and produce more accurate results

Simulation for Reliability, Hardware Security, and Ising Computing in VLSI Chip Design

The continued scaling of VLSI circuits has provided a wealth of opportunities andchallenges to the VLSI circuit design area. Both these challenges and opportunities, however,require new simulation tools that can enable their solution or exploitation as classicalmethods typically dealt with problem domains with smaller scales or less complexity. Inthis dissertation, simulation methods are presented to address the emerging VLSI designtopics of Electromigration induced aging and Ising computing and are then applied to theapplication areas of hardware security and graph partitioning respectively.The Electromigration aging effect in VLSI circuits is a long-term reliability issueaffecting current carrying metal wires leading to IR drop degradation. Typically, simpleanalytical equations can determine a wire’s effective age or if it will be affected by the EMaging effect at all. However, these classical methods are overly conservative and can lead toover design or unnecessary design iterations. Furthermore, it is expected that the EM agingeffect will become more severe in future Integrated Cirucits (ICs) due to increasing currentdensities and the prevalance of polycrystaline copper atom structures seen at small wiredimensions. For this reason, more comprehensive simulation techniques that can efficientlysimulate the EM effect with less conservative results can help mitigate overdesign andincrease design margins while reducing design iterations.The area of Hardware Security is becoming increasingly important as the chipsupply chain becomes more globalized and the integrity of chips becomes more diffiuclt toverify. Utilizing the accurate simulation techniques for EM, we can utilize this reliabilityeffect to demonstrate how a reliability based attack could be perpatrated. Furthermore, wecan utilize this aging effect as a defense mechanism to help us validate the integrity of anIC and detect counterfeit chips in the component supply chain market.Ising computing is an emerging method of solving combinatorial optimization problemsby simulating the interactions of so-called spin glasses and their interactions. Borrowingconcepts from quantum computing, this methods mimics the quantum interaction betweenspin glasses in such a way that finding a ground state of these spin glass models leadsto the solution of a particular problem. In this dissertation, effective methods of simulatingthe spin glass interactions using General Purpose Graphics Processing Units (GPGPUs)and finding their ground state are developed.In addition to the GPU based Ising model simulations, important combinatorialproblems can be mapped to the Ising model. In this dissertation the Ising solver is appliedto graph partitioning which can be utilized in VLSI design and many other domains as well.Specifically, solvers for the maxcut problem and the balanced min-cut partitioning problemare developed

High level design and control of adaptive multiprocessor system-on-chips

The design of modern embedded systems is getting more and more complex, as more func- tionality is integrated into these systems. At the same time, in order to meet the compu- tational requirements while keeping a low level power consumption, MPSoCs have emerged as the main solutions for such embedded systems. Furthermore, embedded systems are be- coming more and more adaptive, as the adaptivity can bring a number of benefits, such as software flexibility and energy efficiency. This thesis targets the safe design of such adaptive MPSoCs. First, each system configuration must be analyzed concerning its functional and non- functional properties. We present an abstract design and analysis framework, which allows for faster and cost-effective implementation decisions. This framework is intended as an intermediate reasoning support for system level software/hardware co-design environments. It can prune the design space at its largest, and identify candidate design solutions in a fast and efficient way. In the framework, we use an abstract clock-based encoding to model system behaviors. Different mapping and scheduling scenarios of applications on MPSoCs are analyzed via clock traces representing system simulations. Among properties of interest are functional behavioral correctness, temporal performance and energy consumption. Second, the reconfiguration management of adaptive MPSoCs must be addressed. We are specially interested in MPSoCs implemented on reconfigurable hardware architectures (i.e., FPGA fabrics), which provide a good flexibility and computational efficiency for adap- tive MPSoCs. We propose a general design framework based on the discrete controller syn- thesis (DCS) technique to address this issue. The main advantage of this technique is that it allows the automatic controller synthesis w.r.t. a given specification of control objectives. In the framework, the system reconfiguration behavior is modeled in terms of synchronous parallel automata. The reconfiguration management computation problem w.r.t. multiple objectives regarding e.g., resource usages, performance and power consumption is encoded as a DCS problem. The existing BZR programming language and Sigali tool are employed to perform DCS and generate a controller that satisfies the system requirements. Finally, we investigate two different ways of combining the two proposed design frame- works for adaptive MPSoCs. Firstly, they are combined to construct a complete design flow for adaptive MPSoCs. Secondly, they are combined to present how the designed run-time manager by the second framework can be integrated into the first framework so that high level simulations can be performed to assess the run-time manager.La conception de systèmes embarqués modernes est de plus en plus complexe, car plus de fonctionnalités sont intégrées dans ces systèmes. En même temps, afin de répondre aux exigences de calcul tout en conservant une consommation d'énergie de faible niveau, MPSoCs sont apparus comme les principales solutions pour tels systèmes embarqués. En outre, les systèmes embarqués sont de plus en plus adaptatifs, comme l’adaptabilité peut apporter un certain nombre d'avantages, tels que la flexibilité du logiciel et l'efficacité énergétique. Cette thèse vise la conception sécuritaire de ces MPSoCs adaptatifs. Tout d'abord, chaque configuration de système doit être analysée en ce qui concerne ses propriétés fonctionnelles et non fonctionnelles. Nous présentons un cadre abstraite de conception et d’analyse qui permet des décisions d’implémentation plus rapide et plus rentable. Ce cadre est conçu comme un support de raisonnement intermédiaire pour les environnements de co-conception de logiciel / matériel au niveau de système. Il peut élaguer l'espace de conception à sa plus grande portée, et identifier les candidats de solutions de conception de manière rapide et efficace. Dans ce cadre, nous utilisons un codage basé sur l’horloge abstrait pour modéliser les comportements du système. Différents scénarios d'applications de mapping et de planification sur MPSoCs sont analysés via les traces d'horloge qui représentent les simulations du système. Les propriétés d'intérêt sont l’exactitude du comportement fonctionnel, la performance temporelle et la consommation d'énergie. Deuxièmement, la gestion de la reconfiguration de MPSoCs adaptatifs doit être abordée. Nous sommes particulièrement intéressés par les MPSoCs implémentés sur des architectures reconfigurables de hardware (ex. FPGA tissus) qui offrent une bonne flexibilité et une efficacité de calcul pour les MPSoCs adaptatifs. Nous proposons un cadre général de conception basésur la technique de la synthèse de contrôleurs discrets (SCD) pour résoudre ce problème. L’avantage principal de cette technique est qu'elle permet une synthèse d'un contrôleur automatique vis-à-vis d’une spécification donnée des objectifs de contrôle. Dans ce cadre, le comportement de reconfiguration du système est modélisé en termes d'automates synchrones en parallèle. Le problème de calcul de la gestion reconfiguration vis-à-vis de multiples objectifs concernant, par exemple, les usages des ressources, la performance et la consommation d’énergie est codé comme un problème de SCD . Le langage de programmation BZR existant et l’outil Sigali sont employés pour effectuer SCD et générer un contrôleur qui satisfait aux exigences du système. Finalement, nous étudions deux façons différentes de combiner les deux cadres de conception proposées pour MPSoCs adaptatifs. Tout d'abord, ils sont combinés pour construire un flot de conception complet pour MPSoCs adaptatifs. Deuxièmement, ils sont combinés pour présenter la façon dont le gestionnaire d'exécution conçu dans le second cadre peut être intégré dans le premier cadre de sorte que les simulations de haut niveau peuvent être effectuées pour évaluer le gestionnaire d'exécution

Interconnect technologies for very large spiking neural networks

In the scope of this thesis, a neural event communication architecture has been developed for use in an accelerated neuromorphic computing system and with a packet-based high performance interconnection network. Existing neuromorphic computing systems mostly use highly customised interconnection networks, directly routing single spike events to their destination. In contrast, the approach of this thesis uses a general purpose packet-based interconnection network and accumulates multiple spike events at the source node into larger network packets destined to common destinations. This is required to optimise the payload efficiency, given relatively large packet headers as compared to the size of neural spike events. Theoretical considerations are made about the efficiency of different event aggregation strategies. Thereby, important factors are the number of occurring event network-destinations and their relative frequency, as well as the number of available accumulation buffers. Based on the concept of Markov Chains, an analytical method is developed and used to evaluate these aggregation strategies. Additionally, some of these strategies are stochastically simulated in order to verify the analytical method and evaluate them beyond its applicability. Based on the results of this analysis, an optimisation strategy is proposed for the mapping of neural populations onto interconnected neuromorphic chips, as well as the joint assignment of event network-destinations to a set of accumulation buffers. During this thesis, such an event communication architecture has been implemented on the communication FPGAs in the BrainScaleS-2 accelerated neuromorphic computing system. Thereby, its usability can be scaled beyond single chip setups. For this, the EXTOLL network technology is used to transport and route the aggregated neural event packets with high bandwidth and low latency. At the FPGA, a network bandwidth of up to 12 Gbit/s is usable at a maximum payload efficiency of 94 %. The latency has been measured in the scope of this thesis to a range between 1.6 μs and 2.3 μs across the network between two neuron circuits on separate chips. This latency is thereby mostly dominated by the path from the neuromorphic chip across the communication FPGA into the network and back on the receiving side. As the EXTOLL network hardware itself is clocked at a much higher frequency than the FPGAs, the latency is expected to scale in the order of only approximately 75 ns for each additional hop through the network. For being able to globally interpret the arrival timestamps that are transmitted with every spike event, the system time counters on the FPGAs are synchronised across the network. For this, the global interrupt mechanism implemented in the EXTOLL hardware is characterised and used within this thesis. With this, a synchronisation accuracy of ±40ns could be measured. At the end of this thesis, the successful emulation of a neural signal propagation model, distributed across two BrainScaleS-2 chips and FPGAs is demonstrated using the implemented event communication architecture and the described synchronisation mechanism

The IPS fidelity scale as a guideline to implement Supported Employment

info:eu-repo/semantics/publishe

Can my chip behave like my brain?

Many decades ago, Carver Mead established the foundations of neuromorphic systems. Neuromorphic systems are analog circuits that emulate biology. These circuits utilize subthreshold dynamics of CMOS transistors to mimic the behavior of neurons. The objective is to not only simulate the human brain, but also to build useful applications using these bio-inspired circuits for ultra low power speech processing, image processing, and robotics. This can be achieved using reconfigurable hardware, like field programmable analog arrays (FPAAs), which enable configuring different applications on a cross platform system. As digital systems saturate in terms of power efficiency, this alternate approach has the potential to improve computational efficiency by approximately eight orders of magnitude. These systems, which include analog, digital, and neuromorphic elements combine to result in a very powerful reconfigurable processing machine.Ph.D