Improving low latency applications for reconfigurable devices

This thesis seeks to improve low latency application performance via architectural improvements in reconfigurable devices. This is achieved by improving resource utilisation and access, and by exploiting the different environments within which reconfigurable devices are deployed. Our first contribution leverages devices deployed at the network level to enable the low latency processing of financial market data feeds. Financial exchanges transmit messages via two identical data feeds to reduce the chance of message loss. We present an approach to arbitrate these redundant feeds at the network level using a Field-Programmable Gate Array (FPGA). With support for any messaging protocol, we evaluate our design using the NASDAQ TotalView-ITCH, OPRA, and ARCA data feed protocols, and provide two simultaneous outputs: one prioritising low latency, and one prioritising high reliability with three dynamically configurable windowing methods. Our second contribution is a new ring-based architecture for low latency, parallel access to FPGA memory. Traditional FPGA memory is formed by grouping block memories (BRAMs) together and accessing them as a single device. Our architecture accesses these BRAMs independently and in parallel. Targeting memory-based computing, which stores pre-computed function results in memory, we benefit low latency applications that rely on: highly-complex functions; iterative computation; or many parallel accesses to a shared resource. We assess square root, power, trigonometric, and hyperbolic functions within the FPGA, and provide a tool to convert Python functions to our new architecture. Our third contribution extends the ring-based architecture to support any FPGA processing element. We unify E heterogeneous processing elements within compute pools, with each element implementing the same function, and the pool serving D parallel function calls. Our implementation-agnostic approach supports processing elements with different latencies, implementations, and pipeline lengths, as well as non-deterministic latencies. Compute pools evenly balance access to processing elements across the entire application, and are evaluated by implementing eight different neural network activation functions within an FPGA.Open Acces

Database System Acceleration on FPGAs

Relational database systems provide various services and applications with an efficient means for storing, processing, and retrieving their data. The performance of these systems has a direct impact on the quality of service of the applications that rely on them. Therefore, it is crucial that database systems are able to adapt and grow in tandem with the demands of these applications, ensuring that their performance scales accordingly. In the past, Moore's law and algorithmic advancements have been sufficient to meet these demands. However, with the slowdown of Moore's law, researchers have begun exploring alternative methods, such as application-specific technologies, to satisfy the more challenging performance requirements. One such technology is field-programmable gate arrays (FPGAs), which provide ideal platforms for developing and running custom architectures for accelerating database systems. The goal of this thesis is to develop a domain-specific architecture that can enhance the performance of in-memory database systems when executing analytical queries. Our research is guided by a combination of academic and industrial requirements that seek to strike a balance between generality and performance. The former ensures that our platform can be used to process a diverse range of workloads, while the latter makes it an attractive solution for high-performance use cases. Throughout this thesis, we present the development of a system-on-chip for database system acceleration that meets our requirements. The resulting architecture, called CbMSMK, is capable of processing the projection, sort, aggregation, and equi-join database operators and can also run some complex TPC-H queries. CbMSMK employs a shared sort-merge pipeline for executing all these operators, which results in an efficient use of FPGA resources. This approach enables the instantiation of multiple acceleration cores on the FPGA, allowing it to serve multiple clients simultaneously. CbMSMK can process both arbitrarily deep and wide tables efficiently. The former is achieved through the use of the sort-merge algorithm which utilizes the FPGA RAM for buffering intermediate sort results. The latter is achieved through the use of KeRRaS, a novel variant of the forward radix sort algorithm introduced in this thesis. KeRRaS allows CbMSMK to process a table a few columns at a time, incrementally generating the final result through multiple iterations. Given that acceleration is a key objective of our work, CbMSMK benefits from many performance optimizations. For instance, multi-way merging is employed to reduce the number of merge passes required for the execution of the sort-merge algorithm, thus improving the performance of all our pipeline-breaking operators. Another example is our in-depth analysis of early aggregation, which led to the development of a novel cache-based algorithm that significantly enhances aggregation performance. Our experiments demonstrate that CbMSMK performs on average 5 times faster than the state-of-the-art CPU-based database management system MonetDB.:I Database Systems & FPGAs 1 INTRODUCTION 1.1 Databases & the Importance of Performance 1.2 Accelerators & FPGAs 1.3 Requirements 1.4 Outline & Summary of Contributions 2 BACKGROUND ON DATABASE SYSTEMS 2.1 Databases 2.1.1 Storage Model 2.1.2 Storage Medium 2.2 Database Operators 2.2.1 Projection 2.2.2 Filter 2.2.3 Sort 2.2.4 Aggregation 2.2.5 Join 2.2.6 Operator Classification 2.3 Database Queries 2.4 Impact of Acceleration 3 BACKGROUND ON FPGAS 3.1 FPGA 3.1.1 Logic Element 3.1.2 Block RAM (BRAM) 3.1.3 Digital Signal Processor (DSP) 3.1.4 IO Element 3.1.5 Programmable Interconnect 3.2 FPGADesignFlow 3.2.1 Specifications 3.2.2 RTL Description 3.2.3 Verification 3.2.4 Synthesis, Mapping, Placement, and Routing 3.2.5 TimingAnalysis 3.2.6 Bitstream Generation and FPGA Programming 3.3 Implementation Quality Metrics 3.4 FPGA Cards 3.5 Benefits of Using FPGAs 3.6 Challenges of Using FPGAs 4 RELATED WORK 4.1 Summary of Related Work 4.2 Platform Type 4.2.1 Accelerator Card 4.2.2 Coprocessor 4.2.3 Smart Storage 4.2.4 Network Processor 4.3 Implementation 4.3.1 Loop-based implementation 4.3.2 Sort-based Implementation 4.3.3 Hash-based Implementation 4.3.4 Mixed Implementation 4.4 A Note on Quantitative Performance Comparisons II Cache-Based Morphing Sort-Merge with KeRRaS (CbMSMK) 5 OBJECTIVES AND ARCHITECTURE OVERVIEW 5.1 From Requirements to Objectives 5.2 Architecture Overview 5.3 Outlineof Part II 6 COMPARATIVE ANALYSIS OF OPENCL AND RTL FOR SORT-MERGE PRIMITIVES ON FPGAS 6.1 Programming FPGAs 6.2 RelatedWork 6.3 Architecture 6.3.1 Global Architecture 6.3.2 Sorter Architecture 6.3.3 Merger Architecture 6.3.4 Scalability and Resource Adaptability 6.4 Experiments 6.4.1 OpenCL Sort-Merge Implementation 6.4.2 RTLSorters 6.4.3 RTLMergers 6.4.4 Hybrid OpenCL-RTL Sort-Merge Implementation 6.5 Summary & Discussion 7 RESOURCE-EFFICIENT ACCELERATION OF PIPELINE-BREAKING DATABASE OPERATORS ON FPGAS 7.1 The Case for Resource Efficiency 7.2 Related Work 7.3 Architecture 7.3.1 Sorters 7.3.2 Sort-Network 7.3.3 X:Y Mergers 7.3.4 Merge-Network 7.3.5 Join Materialiser (JoinMat) 7.4 Experiments 7.4.1 Experimental Setup 7.4.2 Implementation Description & Tuning 7.4.3 Sort Benchmarks 7.4.4 Aggregation Benchmarks 7.4.5 Join Benchmarks 7. Summary 8 KERRAS: COLUMN-ORIENTED WIDE TABLE PROCESSING ON FPGAS 8.1 The Scope of Database System Accelerators 8.2 Related Work 8.3 Key-Reduce Radix Sort(KeRRaS) 8.3.1 Time Complexity 8.3.2 Space Complexity (Memory Utilization) 8.3.3 Discussion and Optimizations 8.4 Architecture 8.4.1 MSM 8.4.2 MSMK: Extending MSM with KeRRaS 8.4.3 Payload, Aggregation and Join Processing 8.4.4 Limitations 8.5 Experiments 8.5.1 Experimental Setup 8.5.2 Datasets 8.5.3 MSMK vs. MSM 8.5.4 Payload-Less Benchmarks 8.5.5 Payload-Based Benchmarks 8.5.6 Flexibility 8.6 Summary 9 A STUDY OF EARLY AGGREGATION IN DATABASE QUERY PROCESSING ON FPGAS 9.1 Early Aggregation 9.2 Background & Related Work 9.2.1 Sort-Based Early Aggregation 9.2.2 Cache-Based Early Aggregation 9.3 Simulations 9.3.1 Datasets 9.3.2 Metrics 9.3.3 Sort-Based Versus Cache-Based Early Aggregation 9.3.4 Comparison of Set-Associative Caches 9.3.5 Comparison of Cache Structures 9.3.6 Comparison of Replacement Policies 9.3.7 Cache Selection Methodology 9.4 Cache System Architecture 9.4.1 Window Aggregator 9.4.2 Compressor & Hasher 9.4.3 Collision Detector 9.4.4 Collision Resolver 9.4.5 Cache 9.5 Experiments 9.5.1 Experimental Setup 9.5.2 Resource Utilization and Parameter Tuning 9.5.3 Datasets 9.5.4 Benchmarks on Synthetic Data 9.5.5 Benchmarks on Real Data 9.6 Summary 10 THE FULL PICTURE 10.1 System Architecture 10.2 Benchmarks 10.3 Meeting the Objectives III Conclusion 11 SUMMARY AND OUTLOOK ON FUTURE RESEARCH 11.1 Summary 11.2 Future Work BIBLIOGRAPHY LIST OF FIGURES LIST OF TABLE

Enhancing Real-time Embedded Image Processing Robustness on Reconfigurable Devices for Critical Applications

Nowadays, image processing is increasingly used in several application fields, such as biomedical, aerospace, or automotive. Within these fields, image processing is used to serve both non-critical and critical tasks. As example, in automotive, cameras are becoming key sensors in increasing car safety, driving assistance and driving comfort. They have been employed for infotainment (non-critical), as well as for some driver assistance tasks (critical), such as Forward Collision Avoidance, Intelligent Speed Control, or Pedestrian Detection. The complexity of these algorithms brings a challenge in real-time image processing systems, requiring high computing capacity, usually not available in processors for embedded systems. Hardware acceleration is therefore crucial, and devices such as Field Programmable Gate Arrays (FPGAs) best fit the growing demand of computational capabilities. These devices can assist embedded processors by significantly speeding-up computationally intensive software algorithms. Moreover, critical applications introduce strict requirements not only from the real-time constraints, but also from the device reliability and algorithm robustness points of view. Technology scaling is highlighting reliability problems related to aging phenomena, and to the increasing sensitivity of digital devices to external radiation events that can cause transient or even permanent faults. These faults can lead to wrong information processed or, in the worst case, to a dangerous system failure. In this context, the reconfigurable nature of FPGA devices can be exploited to increase the system reliability and robustness by leveraging Dynamic Partial Reconfiguration features. The research work presented in this thesis focuses on the development of techniques for implementing efficient and robust real-time embedded image processing hardware accelerators and systems for mission-critical applications. Three main challenges have been faced and will be discussed, along with proposed solutions, throughout the thesis: (i) achieving real-time performances, (ii) enhancing algorithm robustness, and (iii) increasing overall system's dependability. In order to ensure real-time performances, efficient FPGA-based hardware accelerators implementing selected image processing algorithms have been developed. Functionalities offered by the target technology, and algorithm's characteristics have been constantly taken into account while designing such accelerators, in order to efficiently tailor algorithm's operations to available hardware resources. On the other hand, the key idea for increasing image processing algorithms' robustness is to introduce self-adaptivity features at algorithm level, in order to maintain constant, or improve, the quality of results for a wide range of input conditions, that are not always fully predictable at design-time (e.g., noise level variations). This has been accomplished by measuring at run-time some characteristics of the input images, and then tuning the algorithm parameters based on such estimations. Dynamic reconfiguration features of modern reconfigurable FPGA have been extensively exploited in order to integrate run-time adaptivity into the designed hardware accelerators. Tools and methodologies have been also developed in order to increase the overall system dependability during reconfiguration processes, thus providing safe run-time adaptation mechanisms. In addition, taking into account the target technology and the environments in which the developed hardware accelerators and systems may be employed, dependability issues have been analyzed, leading to the development of a platform for quickly assessing the reliability and characterizing the behavior of hardware accelerators implemented on reconfigurable FPGAs when they are affected by such faults

Virtualizing Reconfigurable Architectures: From Fpgas To Beyond

With field-programmable gate arrays (FPGAs) being widely deployed in data centers to enhance the computing performance, an efficient virtualization support is required to fully unleash the potential of cloud FPGAs. However, the system support for FPGAs in the context of the cloud environment is still in its infancy, which leads to a low resource utilization due to the tight coupling between compilation and resource allocation. Moreover, the system support proposed in existing works is limited to a homogeneous FPGA cluster comprising identical FPGA devices, which is hard to be extended to a heterogeneous FPGA cluster that comprises multiple types of FPGAs. As the FPGA cloud is expected to become increasingly heterogeneous due to the hardware rolling upgrade strategy, it is necessary to provide efficient virtualization support for the heterogeneous FPGA cluster. In this dissertation, we first identify three pairs of conflicting requirements from runtime management and offline compilation, which are related to the tradeoff between flexibility and efficiency. These conflicting requirements are the fundamental reason why the single-level abstraction proposed in prior works for the homogeneous FPGA cluster cannot be trivially extended to the heterogeneous cluster. To decouple these conflicting requirements, we provide a two-level system abstraction. Specifically, the high-level abstraction is FPGA-agnostic and provides a simple and homogeneous view of the FPGA resources to simplify the runtime management and maximize the flexibility. On the contrary, the low-level abstraction is FPGA-specific and exposes sufficient low-level hardware details to the compilation framework to ensure the mapping quality and maximize the efficiency. This generic two-level system abstraction can also be specialized to the homogeneous FPGA cluster and/or be extended to leverage application-specific information to further improve the efficiency. We also develop a compilation framework and a modular runtime system with a heuristic-based runtime management policy to support this two-level system abstraction. By enabling a dynamic FPGA sharing at the sub-FPGA granularity, the proposed virtualization solution can deploy 1.62x more applications using the same amount of FPGA resources and reduce the compilation time by 22.6% (perform as many compilation tasks in parallel as possible) with an acceptable virtualization overhead, i.e., Finally, we use Liquid Silicon as a case study to show that the proposed virtualization solution can be extended to other spatial reconfigurable architectures. Liquid Silicon is a homogeneous reconfigurable architecture enabled by the non-volatile memory technology (i.e., RRAM). It extends the configuration capability of existing FPGAs from computation to the whole spectrum ranging from computation to data storage. It allows users to better customize hardware by flexibly partitioning hardware resources between computation and memory based on the actual usage. Instead of naively applying the proposed virtualization solution onto Liquid Silicon, we co-optimize the system abstraction and Liquid Silicon architecture to improve the performance

FPGA embedded system for ultrasonic non-destructive testing

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonLong Range Ultrasonic Testing (LRUT) is an emerging ultrasound Non-destructive Testing (NDT) method. The LRUT is a variant of the conventional NDT approach. By using ultrasound guided waves (UGWs) , it is efficient in quick long range defect scanning, which is impossible with other traditional NDT techniques. Increasing numbers of requirements for quick long range testing have led to urgent need for the improvement of testing methods and the development of new testing equipment to help researchers in laboratory and help technicians in field inspection. The market for multi-channel ultrasonic instruments is characterized by small volumes of sales and a high ratio of development costs to sale price. The consequence is that the investment required to develop an instrument is significant and upgrades and other changes to instrument specification or configuration are difficult for many manufacturers to justify. These factors are particularly relevant for long range guided wave technology, where the technology is still relatively new in the market place and the instrumentation has different characteristics from other type of ultrasonic systems. In order to support the design and manufacture of the Teletest®MK4 system, Plant Integrity Ltd has supported this study into the use of a field-programmable gates array (FPGA) based control circuits for the electronics, which allows the component count to be decreased and also permits the system to be modified via flexible reconfiguration of the FPGA. This has benefits of reduction of size, weight and power consumption of the electronics and provides a means of upgrading the product without expensive re-design of the hardware. FPGA device has been the enabling technology and main thrust behind the evolution of many technologies, unleashing new opportunities for improving the performance of the LRUT equipment and providing more functions for industrial and academic applications. A novel system has been developed to provide multichannel waveform generation, data capture and signal processing for advanced lab-based research and faster- field testing. This system includes an FPGA to process multichannel data in parallel and to provide the flexibility of reconfiguration for various testing applications proposed by new research. The design was tested in pre-prototype hardware. Subsequent construction of the commercial prototype unit enabled successful operation of the design to be demonstrated. Implementation of the FPGA design reduced component count, PCB dimensions and power consumption. Though the SpartanTM 3A DSP FPGA and Xilinx ISE software have been used in this project, the concepts of the design can be applied to other FPGA devices from other FPGA vendors using other design softwares.TWI Ltd; Plant Integrity Lt

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

Separation logic for high-level synthesis

High-level synthesis (HLS) promises a significant shortening of the digital hardware design cycle by raising the abstraction level of the design entry to high-level languages such as C/C++. However, applications using dynamic, pointer-based data structures remain difficult to implement well, yet such constructs are widely used in software. Automated optimisations that leverage the memory bandwidth of dedicated hardware implementations by distributing the application data over separate on-chip memories and parallelise the implementation are often ineffective in the presence of dynamic data structures, due to the lack of an automated analysis that disambiguates pointer-based memory accesses. This thesis takes a step towards closing this gap. We explore recent advances in separation logic, a rigorous mathematical framework that enables formal reasoning about the memory access of heap-manipulating programs. We develop a static analysis that automatically splits heap-allocated data structures into provably disjoint regions. Our algorithm focuses on dynamic data structures accessed in loops and is accompanied by automated source-to-source transformations which enable loop parallelisation and physical memory partitioning by off-the-shelf HLS tools. We then extend the scope of our technique to pointer-based memory-intensive implementations that require access to an off-chip memory. The extended HLS design aid generates parallel on-chip multi-cache architectures. It uses the disjointness property of memory accesses to support non-overlapping memory regions by private caches. It also identifies regions which are shared after parallelisation and which are supported by parallel caches with a coherency mechanism and synchronisation, resulting in automatically specialised memory systems. We show up to 15x acceleration from heap partitioning, parallelisation and the insertion of the custom cache system in demonstrably practical applications.Open Acces

Dependability-driven Strategies to Improve the Design and Verification of Safety-Critical HDL-based Embedded Systems

[ES] La utilización de sistemas empotrados en cada vez más ámbitos de aplicación está llevando a que su diseño deba enfrentarse a mayores requisitos de rendimiento, consumo de energía y área (PPA). Asimismo, su utilización en aplicaciones críticas provoca que deban cumplir con estrictos requisitos de confiabilidad para garantizar su correcto funcionamiento durante períodos prolongados de tiempo. En particular, el uso de dispositivos lógicos programables de tipo FPGA es un gran desafío desde la perspectiva de la confiabilidad, ya que estos dispositivos son muy sensibles a la radiación. Por todo ello, la confiabilidad debe considerarse como uno de los criterios principales para la toma de decisiones a lo largo del todo flujo de diseño, que debe complementarse con diversos procesos que permitan alcanzar estrictos requisitos de confiabilidad. Primero, la evaluación de la robustez del diseño permite identificar sus puntos débiles, guiando así la definición de mecanismos de tolerancia a fallos. Segundo, la eficacia de los mecanismos definidos debe validarse experimentalmente. Tercero, la evaluación comparativa de la confiabilidad permite a los diseñadores seleccionar los componentes prediseñados (IP), las tecnologías de implementación y las herramientas de diseño (EDA) más adecuadas desde la perspectiva de la confiabilidad. Por último, la exploración del espacio de diseño (DSE) permite configurar de manera óptima los componentes y las herramientas seleccionados, mejorando así la confiabilidad y las métricas PPA de la implementación resultante. Todos los procesos anteriormente mencionados se basan en técnicas de inyección de fallos para evaluar la robustez del sistema diseñado. A pesar de que existe una amplia variedad de técnicas de inyección de fallos, varias problemas aún deben abordarse para cubrir las necesidades planteadas en el flujo de diseño. Aquellas soluciones basadas en simulación (SBFI) deben adaptarse a los modelos de nivel de implementación, teniendo en cuenta la arquitectura de los diversos componentes de la tecnología utilizada. Las técnicas de inyección de fallos basadas en FPGAs (FFI) deben abordar problemas relacionados con la granularidad del análisis para poder localizar los puntos débiles del diseño. Otro desafío es la reducción del coste temporal de los experimentos de inyección de fallos. Debido a la alta complejidad de los diseños actuales, el tiempo experimental dedicado a la evaluación de la confiabilidad puede ser excesivo incluso en aquellos escenarios más simples, mientras que puede ser inviable en aquellos procesos relacionados con la evaluación de múltiples configuraciones alternativas del diseño. Por último, estos procesos orientados a la confiabilidad carecen de un soporte instrumental que permita cubrir el flujo de diseño con toda su variedad de lenguajes de descripción de hardware, tecnologías de implementación y herramientas de diseño. Esta tesis aborda los retos anteriormente mencionados con el fin de integrar, de manera eficaz, estos procesos orientados a la confiabilidad en el flujo de diseño. Primeramente, se proponen nuevos métodos de inyección de fallos que permiten una evaluación de la confiabilidad, precisa y detallada, en diferentes niveles del flujo de diseño. Segundo, se definen nuevas técnicas para la aceleración de los experimentos de inyección que mejoran su coste temporal. Tercero, se define dos estrategias DSE que permiten configurar de manera óptima (desde la perspectiva de la confiabilidad) los componentes IP y las herramientas EDA, con un coste experimental mínimo. Cuarto, se propone un kit de herramientas que automatiza e incorpora con eficacia los procesos orientados a la confiabilidad en el flujo de diseño semicustom. Finalmente, se demuestra la utilidad y eficacia de las propuestas mediante un caso de estudio en el que se implementan tres procesadores empotrados en un FPGA de Xilinx serie 7.[CA] La utilització de sistemes encastats en cada vegada més àmbits d'aplicació està portant al fet que el seu disseny haja d'enfrontar-se a majors requisits de rendiment, consum d'energia i àrea (PPA). Així mateix, la seua utilització en aplicacions crítiques provoca que hagen de complir amb estrictes requisits de confiabilitat per a garantir el seu correcte funcionament durant períodes prolongats de temps. En particular, l'ús de dispositius lògics programables de tipus FPGA és un gran desafiament des de la perspectiva de la confiabilitat, ja que aquests dispositius són molt sensibles a la radiació. Per tot això, la confiabilitat ha de considerar-se com un dels criteris principals per a la presa de decisions al llarg del tot flux de disseny, que ha de complementar-se amb diversos processos que permeten aconseguir estrictes requisits de confiabilitat. Primer, l'avaluació de la robustesa del disseny permet identificar els seus punts febles, guiant així la definició de mecanismes de tolerància a fallades. Segon, l'eficàcia dels mecanismes definits ha de validar-se experimentalment. Tercer, l'avaluació comparativa de la confiabilitat permet als dissenyadors seleccionar els components predissenyats (IP), les tecnologies d'implementació i les eines de disseny (EDA) més adequades des de la perspectiva de la confiabilitat. Finalment, l'exploració de l'espai de disseny (DSE) permet configurar de manera òptima els components i les eines seleccionats, millorant així la confiabilitat i les mètriques PPA de la implementació resultant. Tots els processos anteriorment esmentats es basen en tècniques d'injecció de fallades per a poder avaluar la robustesa del sistema dissenyat. A pesar que existeix una àmplia varietat de tècniques d'injecció de fallades, diverses problemes encara han d'abordar-se per a cobrir les necessitats plantejades en el flux de disseny. Aquelles solucions basades en simulació (SBFI) han d'adaptar-se als models de nivell d'implementació, tenint en compte l'arquitectura dels diversos components de la tecnologia utilitzada. Les tècniques d'injecció de fallades basades en FPGAs (FFI) han d'abordar problemes relacionats amb la granularitat de l'anàlisi per a poder localitzar els punts febles del disseny. Un altre desafiament és la reducció del cost temporal dels experiments d'injecció de fallades. A causa de l'alta complexitat dels dissenys actuals, el temps experimental dedicat a l'avaluació de la confiabilitat pot ser excessiu fins i tot en aquells escenaris més simples, mentre que pot ser inviable en aquells processos relacionats amb l'avaluació de múltiples configuracions alternatives del disseny. Finalment, aquests processos orientats a la confiabilitat manquen d'un suport instrumental que permeta cobrir el flux de disseny amb tota la seua varietat de llenguatges de descripció de maquinari, tecnologies d'implementació i eines de disseny. Aquesta tesi aborda els reptes anteriorment esmentats amb la finalitat d'integrar, de manera eficaç, aquests processos orientats a la confiabilitat en el flux de disseny. Primerament, es proposen nous mètodes d'injecció de fallades que permeten una avaluació de la confiabilitat, precisa i detallada, en diferents nivells del flux de disseny. Segon, es defineixen noves tècniques per a l'acceleració dels experiments d'injecció que milloren el seu cost temporal. Tercer, es defineix dues estratègies DSE que permeten configurar de manera òptima (des de la perspectiva de la confiabilitat) els components IP i les eines EDA, amb un cost experimental mínim. Quart, es proposa un kit d'eines (DAVOS) que automatitza i incorpora amb eficàcia els processos orientats a la confiabilitat en el flux de disseny semicustom. Finalment, es demostra la utilitat i eficàcia de les propostes mitjançant un cas d'estudi en el qual s'implementen tres processadors encastats en un FPGA de Xilinx serie 7.[EN] Embedded systems are steadily extending their application areas, dealing with increasing requirements in performance, power consumption, and area (PPA). Whenever embedded systems are used in safety-critical applications, they must also meet rigorous dependability requirements to guarantee their correct operation during an extended period of time. Meeting these requirements is especially challenging for those systems that are based on Field Programmable Gate Arrays (FPGAs), since they are very susceptible to Single Event Upsets. This leads to increased dependability threats, especially in harsh environments. In such a way, dependability should be considered as one of the primary criteria for decision making throughout the whole design flow, which should be complemented by several dependability-driven processes. First, dependability assessment quantifies the robustness of hardware designs against faults and identifies their weak points. Second, dependability-driven verification ensures the correctness and efficiency of fault mitigation mechanisms. Third, dependability benchmarking allows designers to select (from a dependability perspective) the most suitable IP cores, implementation technologies, and electronic design automation (EDA) tools. Finally, dependability-aware design space exploration (DSE) allows to optimally configure the selected IP cores and EDA tools to improve as much as possible the dependability and PPA features of resulting implementations. The aforementioned processes rely on fault injection testing to quantify the robustness of the designed systems. Despite nowadays there exists a wide variety of fault injection solutions, several important problems still should be addressed to better cover the needs of a dependability-driven design flow. In particular, simulation-based fault injection (SBFI) should be adapted to implementation-level HDL models to take into account the architecture of diverse logic primitives, while keeping the injection procedures generic and low-intrusive. Likewise, the granularity of FPGA-based fault injection (FFI) should be refined to the enable accurate identification of weak points in FPGA-based designs. Another important challenge, that dependability-driven processes face in practice, is the reduction of SBFI and FFI experimental effort. The high complexity of modern designs raises the experimental effort beyond the available time budgets, even in simple dependability assessment scenarios, and it becomes prohibitive in presence of alternative design configurations. Finally, dependability-driven processes lack an instrumental support covering the semicustom design flow in all its variety of description languages, implementation technologies, and EDA tools. Existing fault injection tools only partially cover the individual stages of the design flow, being usually specific to a particular design representation level and implementation technology. This work addresses the aforementioned challenges by efficiently integrating dependability-driven processes into the design flow. First, it proposes new SBFI and FFI approaches that enable an accurate and detailed dependability assessment at different levels of the design flow. Second, it improves the performance of dependability-driven processes by defining new techniques for accelerating SBFI and FFI experiments. Third, it defines two DSE strategies that enable the optimal dependability-aware tuning of IP cores and EDA tools, while reducing as much as possible the robustness evaluation effort. Fourth, it proposes a new toolkit (DAVOS) that automates and seamlessly integrates the aforementioned dependability-driven processes into the semicustom design flow. Finally, it illustrates the usefulness and efficiency of these proposals through a case study consisting of three soft-core embedded processors implemented on a Xilinx 7-series SoC FPGA.Tuzov, I. (2020). Dependability-driven Strategies to Improve the Design and Verification of Safety-Critical HDL-based Embedded Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/159883TESI

Evaluation of single photon avalanche diode arrays for imaging fluorescence correlation spectroscopy : FPGA-based data readout and fast correlation analysis on CPUs, GPUs and FPGAs

The metabolism of all living organisms, and specifically also of their smallest constituents, the cell, is based on chemical reactions. A key factor determining the speed of these processes is transport of reactants, energy, and information within the and between the cells of an organism. It has been shown that the relevant transport processes also depend on the spatial organization of the cells. Such transport processes are typically investigated using fluorescence correlation spectroscopy (FCS) in combination with fluorescent labeling of the molecules of interest. In FCS, one observes the fluctuating fluorescence signal from a femtoliter-sized sub-volume within the sample (e.g. a cell). The variations in the intensity arise from the particles moving in and out of this sub-volume. By means of an autocorrelation analysis of the intensity signal, conclusion can be drawn regarding the concentration and the mobility parameters, such as the diffusion coefficient. Typically, one uses the laser focus of a confocal microscope for FCS measurements. But with this microscopy technique, FCS is limited to a single spot a every time. In order to conduct parallel multi-spot measurements, i.e. to create diffusion maps, FCS can be combined with the lightsheet based selective plane illumination microscopy (SPIM). This recent widefield microscopy technique allows observing a small plane of a sample (1-3um thick), which can be positioned arbitrarily. Usually, FCS on a SPIM is done using fast electron-multiplying charge-coupled device (EMCCD) cameras, which offer a limited temporal resolution (500us). Such a temporal resolution only allows measuring the motion of intermediately sized particles within a cell reliably. The limited temporal resolution renders the detection of even smaller molecules impossible. In this thesis, arrays of single photon avalanche diodes (SPADs) were used as detectors. Although SPAD-based image sensors still lack in sensitivity, they provide a significantly better temporal resolution (1-10us for full frames) that is not achievable with sensitive cameras and seem to be the ideal sensors for SPIM-FCS. In the course of this work, two recent SPAD arrays (developed in the groups of Prof. Edoardo Charbon, TU Delft, the Netherlands, and EPFL, Switzerland) were extensively characterized with regards to their suitability for SPIM-FCS. The evaluated SPAD arrays comprise 32x32 and 512x128 pixels and allow for frame rates of up to 300000 or 150000 frames per second, respectively. With these specifications, the latter array is one of the largest and fastest sensors that is currently available. During full-frame readout, it delivers a data rate of up to 1.2 GiB/s. For both arrays, suitable readout-hardware-based on field programmable gate arrays (FPGAs) was designed. To cope with the high data rate and to allow real-time correlation analysis, correlation algorithms were implemented and characterized on the three major high performance computing platforms, namely FPGAs, CPUs, and graphics processing units (GPUs). Of all three platforms, the GPU performed best in terms of correlation analysis, and a speed of 2.6 over real time was achieved for the larger SPAD array. Beside the lack in sensitivity, which could be accounted for by microlenses, a major drawback of the evaluated SPAD arrays was their afterpulsing. It appeared that the temporal structure superimposed the signal of the diffusion. Thus, extracting diffusion properties from the autocorrelation analysis only proved impossible. By additionally performing a spatial cross-correlation analysis such influences could be significantly minimized. Furthermore, this approach allowed for the determination of absolute diffusion coefficients without prior calibration. With that, spatially resolved measurements of fluorescent proteins in living cells could be conducted successfully

A Heterogeneous System Architecture for Low-Power Wireless Sensor Nodes in Compute-Intensive Distributed Applications

Wireless Sensor Networks (WSNs) combine embedded sensing and processing capabilities with a wireless communication infrastructure, thus supporting distributed monitoring applications. WSNs have been investigated for more than three decades, and recent social and industrial developments such as home automation, or the Internet of Things, have increased the commercial relevance of this key technology. The communication bandwidth of the sensor nodes is limited by the transportation media and the restricted energy budget of the nodes. To still keep up with the ever increasing sensor count and sampling rates, the basic data acquisition and collection capabilities of WSNs have been extended with decentralized smart feature extraction and data aggregation algorithms. Energy-efficient processing elements are thus required to meet the ever-growing compute demands of the WSN motes within the available energy budget. The Hardware-Accelerated Low Power Mote (HaLoMote) is proposed and evaluated in this thesis to address the requirements of compute-intensive WSN applications. It is a heterogeneous system architecture, that combines a Field Programmable Gate Array (FPGA) for hardware-accelerated data aggregation with an IEEE 802.15.4 based Radio Frequency System-on-Chip for the network management and the top-level control of the applications. To properly support Dynamic Power Management (DPM) on the HaLoMote, a Microsemi IGLOO FPGA with a non-volatile configuration storage was chosen for a prototype implementation, called Hardware-Accelerated Low Energy Wireless Embedded Sensor Node (HaLOEWEn). As for every multi-processor architecture, the inter-processor communication and coordination strongly influences the efficiency of the HaLoMote. Therefore, a generic communication framework is proposed in this thesis. It is tightly coupled with the DPM strategy of the HaLoMote, that supports fast transitions between active and idle modes. Low-power sleep periods can thus be scheduled within every sampling cycle, even for sampling rates of hundreds of hertz. In addition to the development of the heterogeneous system architecture, this thesis focuses on the energy consumption trade-off between wireless data transmission and in-sensor data aggregation. The HaLOEWEn is compared with typical software processors in terms of runtime and energy efficiency in the context of three monitoring applications. The building blocks of these applications comprise hardware-accelerated digital signal processing primitives, lossless data compression, a precise wireless time synchronization protocol, and a transceiver scheduling for contention free information flooding from multiple sources to all network nodes. Most of these concepts are applicable to similar distributed monitoring applications with in-sensor data aggregation. A Structural Health Monitoring (SHM) application is used for the system level evaluation of the HaLoMote concept. The Random Decrement Technique (RDT) is a particular SHM data aggregation algorithm, which determines the free-decay response of the monitored structure for subsequent modal identification. The hardware-accelerated RDT executed on a HaLOEWEn mote requires only 43 % of the energy that a recent ARM Cortex-M based microcontroller consumes for this algorithm. The functionality of the overall WSN-based SHM system is shown with a laboratory-scale demonstrator. Compared to reference data acquired by a wire-bound laboratory measurement system, the HaLOEWEn network can capture the structural information relevant for the SHM application with less than 1 % deviation