Architectural Exploration of KeyRing Self-Timed Processors

RÉSUMÉ Les dernières décennies ont vu l’augmentation des performances des processeurs contraintes par les limites imposées par la consommation d’énergie des systèmes électroniques : des très basses consommations requises pour les objets connectés, aux budgets de dépenses électriques des serveurs, en passant par les limitations thermiques et la durée de vie des batteries des appareils mobiles. Cette forte demande en processeurs efficients en énergie, couplée avec les limitations de la réduction d’échelle des transistors—qui ne permet plus d’améliorer les performances à densité de puissance constante—, conduit les concepteurs de circuits intégrés à explorer de nouvelles microarchitectures permettant d’obtenir de meilleures performances pour un budget énergétique donné. Cette thèse s’inscrit dans cette tendance en proposant une nouvelle microarchitecture de processeur, appelée KeyRing, conçue avec l’intention de réduire la consommation d’énergie des processeurs. La fréquence d’opération des transistors dans les circuits intégrés est proportionnelle à leur consommation dynamique d’énergie. Par conséquent, les techniques de conception permettant de réduire dynamiquement le nombre de transistors en opération sont très largement adoptées pour améliorer l’efficience énergétique des processeurs. La technique de clock-gating est particulièrement usitée dans les circuits synchrones, car elle réduit l’impact de l’horloge globale, qui est la principale source d’activité. La microarchitecture KeyRing présentée dans cette thèse utilise une méthode de synchronisation décentralisée et asynchrone pour réduire l’activité des circuits. Elle est dérivée du processeur AnARM, un processeur développé par Octasic sur la base d’une microarchitecture asynchrone ad hoc. Bien qu’il soit plus efficient en énergie que des alternatives synchrones, le AnARM est essentiellement incompatible avec les méthodes de synthèse et d’analyse temporelle statique standards. De plus, sa technique de conception ad hoc ne s’inscrit que partiellement dans les paradigmes de conceptions asynchrones. Cette thèse propose une approche rigoureuse pour définir les principes généraux de cette technique de conception ad hoc, en faisant levier sur la littérature asynchrone. La microarchitecture KeyRing qui en résulte est développée en association avec une méthode de conception automatisée, qui permet de s’affranchir des incompatibilités natives existant entre les outils de conception et les systèmes asynchrones. La méthode proposée permet de pleinement mettre à profit les flots de conception standards de l’industrie microélectronique pour réaliser la synthèse et la vérification des circuits KeyRing. Cette thèse propose également des protocoles expérimentaux, dont le but est de renforcer la relation de causalité entre la microarchitecture KeyRing et une réduction de la consommation énergétique des processeurs, comparativement à des alternatives synchrones équivalentes.----------ABSTRACT Over the last years, microprocessors have had to increase their performances while keeping their power envelope within tight bounds, as dictated by the needs of various markets: from the ultra-low power requirements of the IoT, to the electrical power consumption budget in enterprise servers, by way of passive cooling and day-long battery life in mobile devices. This high demand for power-efficient processors, coupled with the limitations of technology scaling—which no longer provides improved performances at constant power densities—, is leading designers to explore new microarchitectures with the goal of pulling more performances out of a fixed power budget. This work enters into this trend by proposing a new processor microarchitecture, called KeyRing, having a low-power design intent. The switching activity of integrated circuits—i.e. transistors switching on and off—directly affects their dynamic power consumption. Circuit-level design techniques such as clock-gating are widely adopted as they dramatically reduce the impact of the global clock in synchronous circuits, which constitutes the main source of switching activity. The KeyRing microarchitecture presented in this work uses an asynchronous clocking scheme that relies on decentralized synchronization mechanisms to reduce the switching activity of circuits. It is derived from the AnARM, a power-efficient ARM processor developed by Octasic using an ad hoc asynchronous microarchitecture. Although it delivers better power-efficiency than synchronous alternatives, it is for the most part incompatible with standard timing-driven synthesis and Static Timing Analysis (STA). In addition, its design style does not fit well within the existing asynchronous design paradigms. This work lays the foundations for a more rigorous definition of this rather unorthodox design style, using circuits and methods coming from the asynchronous literature. The resulting KeyRing microarchitecture is developed in combination with Electronic Design Automation (EDA) methods that alleviate incompatibility issues related to ad hoc clocking, enabling timing-driven optimizations and verifications of KeyRing circuits using industry-standard design flows. In addition to bridging the gap with standard design practices, this work also proposes comprehensive experimental protocols that aims to strengthen the causal relation between the reported asynchronous microarchitecture and a reduced power consumption compared with synchronous alternatives. The main achievement of this work is a framework that enables the architectural exploration of circuits using the KeyRing microarchitecture

Identification of Soft-Error at Gate Level

Due to shrinking feature size and significant reduction in noise margins, as we are moving into very deep sub-micron technology, circuits have become more susceptible to manufacturing defects, noise-related transient faults and interference from radiation. Traditionally, soft errors have been a much greater concern in memories than in logic circuits. However, due to technology scaling, logic circuits have become equally susceptible to soft errors. Moreover, enhanced usage of commercial off the shelf (COTS) electronic components for avionics has also increased the importance of analyzing soft errors in hardware circuits. Conventionally, understanding soft error glitches requires circuit level modeling, which requires information available only at late stages in the design flow. Instead of this approach some researchers have produced modeling techniques using Reduced Order Binary Decision Diagrams (ROBDD) and Algebraic Decision Diagrams (ADD), which does allow analyzing soft error at an earlier stage in design flow. In this thesis, a new methodology for modeling soft errors glitch propagation path using Multiway Decision Graphs is introduced. This modeling technique is applicable on both combinational and asynchronous circuits. The proposed glitch propagation path modeling technique jointly takes care of logical and electrical masking. Our methodology involves new ways of injecting glitches including glitch injection in feedback paths of asynchronous circuits. This work presents a complete framework to exhaustively provide all the possible sequences of signals that lead to the possibility of glitch propagation to the primary output in combinational and asynchronous circuits. In addition, a new tool is developed based on the proposed methodology called Soft Error Glitch-Propagating Path Finder (SEGP-Finder) to automate the identification of these sequences of signals. This work helps designers identify the vulnerable circuit paths at the logic abstraction level. Also, this methodology allows designers to apply radiation tolerance techniques on reduced sets of possibilities. By applying our methodology on different combinational and asynchronous circuits an improvement in terms of possible-fault injection vectors is observed. As an example, approximately 8% of all the possible input vectors and sequences is required for obtaining exhaustive glitch propagation path identification in a representative implementation of a bundled data asynchronous circuit. To the best of our knowledge, this is the first time MDG based decision diagram based soft error identification approach is proposed for combinational and asynchronous circuits

A hardware-software codesign framework for cellular computing

Until recently, the ever-increasing demand of computing power has been met on one hand by increasing the operating frequency of processors and on the other hand by designing architectures capable of exploiting parallelism at the instruction level through hardware mechanisms such as super-scalar execution. However, both these approaches seem to have reached a plateau, mainly due to issues related to design complexity and cost-effectiveness. To face the stabilization of performance of single-threaded processors, the current trend in processor design seems to favor a switch to coarser-grain parallelization, typically at the thread level. In other words, high computational power is achieved not only by a single, very fast and very complex processor, but through the parallel operation of several processors, each executing a different thread. Extrapolating this trend to take into account the vast amount of on-chip hardware resources that will be available in the next few decades (either through further shrinkage of silicon fabrication processes or by the introduction of molecular-scale devices), together with the predicted features of such devices (e.g., the impossibility of global synchronization or higher failure rates), it seems reasonable to foretell that current design techniques will not be able to cope with the requirements of next-generation electronic devices and that novel design tools and programming methods will have to be devised. A tempting source of inspiration to solve the problems implied by a massively parallel organization and inherently error-prone substrates is biology. In fact, living beings possess characteristics, such as robustness to damage and self-organization, which were shown in previous research as interesting to be implemented in hardware. For instance, it was possible to realize relatively simple systems, such as a self-repairing watch. Overall, these bio-inspired approaches seem very promising but their interest for a wider audience is problematic because their heavily hardware-oriented designs lack some of the flexibility achievable with a general purpose processor. In the context of this thesis, we will introduce a processor-grade processing element at the heart of a bio-inspired hardware system. This processor, based on a single-instruction, features some key properties that allow it to maintain the versatility required by the implementation of bio-inspired mechanisms and to realize general computation. We will also demonstrate that the flexibility of such a processor enables it to be evolved so it can be tailored to different types of applications. In the second half of this thesis, we will analyze how the implementation of a large number of these processors can be used on a hardware platform to explore various bio-inspired mechanisms. Based on an extensible platform of many FPGAs, configured as a networked structure of processors, the hardware part of this computing framework is backed by an open library of software components that provides primitives for efficient inter-processor communication and distributed computation. We will show that this dual software–hardware approach allows a very quick exploration of different ways to solve computational problems using bio-inspired techniques. In addition, we also show that the flexibility of our approach allows it to exploit replication as a solution to issues that concern standard embedded applications

Embedded System Design

A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues

Embedded System Design

A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues

Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design – FMCAD 2021

The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing

Recent advances in petri nets and concurrency

CEUR Workshop Proceeding

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

Exploring the potential of brain-inspired computing

The gap between brains and computers regarding both their cognitive capability and power efficiency is remarkably huge. Brains process information massively in parallel and its constituents are intrinsically self-organizing, while in digital computers the execution of instructions is deterministic and rather serial. The recent progress in the development of dedicated hardware systems implementing physical models of neurons and synapses enables to efficiently emulate spiking neural networks. In this work, we verify the design and explore the potential for brain-inspired computing of such an analog neuromorphic system, called Spikey. We demonstrate the versatility of this highly configurable substrate by the implementation of a rich repertoire of network models, including models for signal propagation and enhancement, general purpose classifiers, cortical models and decorrelating feedback systems. Network emulations on Spikey are highly accelerated and consume less than 1 nJ per synaptic transmission. The Spikey system, hence, outperforms modern desktop computers in terms of fast and efficient network simulations closing the gap to brains. During this thesis the stability, performance and user-friendliness of the Spikey system was improved integrating it into the neuroscientific tool chain and making it available for the community. The implementation of networks suitable to solve everyday tasks, like object or speech recognition, qualifies this technology to be an alternative to conventional computers. Considering the compactness, computational capability and power efficiency, neuromorphic systems may qualify as a valuable complement to classical computation