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 TABLES

Die Einführung des AUTOSAR Standards in der Softwareentwicklung für Steuergeräte ermöglicht die Entwicklung von Kundenfunktionalitäten unabhängig von der Zielplattform. Eine AUTOSAR konforme Applikation wird anschließend für eine konkrete Zielplattform konfiguriert. Diese Flexibilität bringt auch neue Herausforderungen für den Test eines Steuergerätes mit sich. Diese Arbeit präsentiert einen Ansatz, der sowohl durch statische Analysen von Konfigurationen und Quellcode, als auch durch dynamische Tests den Entwicklungsprozess von AUTOSAR Systemen unterstützt. Der dynamische Test überprüft auf der Zielplattform die Schichten der Basissoftware und der RTE und unterstützt bei der Fehlerlokalisierung. Der präsentierte Ansatz ist für alle Versionen der AUTOSAR Classic Plattform anwendbar und nutzt nur Methoden, die durch den AUTOSAR Standard erlaubt sind. Für diese Arbeit wurde eine Wissensbasis entworfen und umgesetzt, die das Architekturwissen des AUTOSAR Standards vorhält. In der Wissensbasis sind Schichten, Stacks und Basissoftwaremodule mit ihren Eigenschaften abgelegt. Durch die Arbeit konnten verschiedenen Projekte mit AUTOSAR Architektur überprüft, verglichen und optimiert werden.:1. Einleitung 2. Grundlagen 3. Stand der Technik 4. Konzept 5. Implementierung 6. Ergebnisse 7. Zusammenfassung und Ausblick A. AUTOSAR Basissoftwaremodule in Wissensbasis / The introduction of the AUTOSAR standard in software development for electronic control units enables the development of customer functionalities independent of the target platform. An AUTOSAR-compliant application is configured for a specific target platform. This flexibility leads to new challenges for testing of electronic control units. This work presents an approach for supporting the development and test process of AUTOSAR systems by static analysis and dynamic tests. The dynamic test checks the different layers of the basic software and RTE on the target platform. Moreover, error localization is supported. The presented approach can be used for all versions of the AUTOSAR Classic platform and only uses methods that are permitted by the AUTOSAR standard. A knowledge base was designed and implemented for this work, which contains the architecture knowledge of the AUTOSAR standard. Layers, stacks and basic software modules with their properties are stored in the knowledge base. The work enabled various projects with AUTOSAR architecture to be checked, compared and optimized.:1. Einleitung 2. Grundlagen 3. Stand der Technik 4. Konzept 5. Implementierung 6. Ergebnisse 7. Zusammenfassung und Ausblick A. AUTOSAR Basissoftwaremodule in Wissensbasis

Voice interaction is an established automatization and accessibility feature. While many satisfactory speech recognition solutions are available today, the interpretation of text se-mantic is in some use-cases difficult. Differentiated can be two types of text semantic ex-traction models: probabilistic and pure rule-based. Rule-based reasoning is formalizable into grammars and enables fast language validation, transparent decision-making and easy customization. In this thesis we develop a context-free ANTLR semantic grammar to control software by speech in a medical, smart glasses related, domain. The implementation is preceded by research of state-of-the-art, requirements consultation and a thorough design of reusable system abstractions. Design includes definitions of DSL, meta grammar, generic system ar-chitecture and tool support. Additionally, we investigate trivial and experimental grammar improvement techniques. Due to multifaceted flexibility and robustness of the designed framework, we indicate its usability in critical and adaptive systems. We determine 75% semantic recognition accuracy in the medical main use-case. We compare it against se-mantic extraction using SpaCy and two fine-tuned AI classifiers. The evaluation reveals high accuracy of BERT for sequence classification and big potential of hybrid solutions with AI techniques on top grammars, essentially for detection of alerts. The accuracy is strong dependent on input quality, highlighting the importance of speech recognition tailored to specific vocabulary.:1 Introduction 1 1.1 Motivation 1 1.2 CAIS.ME Project 2 1.3 Problem Statement 2 1.4 Thesis Overview 3 2 Related Work 4 3 Foundational Concepts and Systems 6 3.1 Human-Computer Interaction in Speech 6 3.2 Speech Recognition 7 3.2.1 Open-source technologies 8 3.2.2 Other technologies 9 3.3 Language Recognition 9 3.3.1 Regular expressions 10 3.3.2 Lexical tokenization 10 3.3.3 Parsing 10 3.3.4 Domain Specific Languages 11 3.3.5 Formal grammars 11 3.3.6 Natural Language Processing 12 3.3.7 Model-Driven Engineering 14 4 State-of-the-Art: Grammars 15 4.1 Overview 15 4.2 Workbenches for Grammar Design 16 4.2.1 ANTLR 16 4.2.2 Xtext 17 4.2.3 JetBrains MPS 17 4.2.4 Other tools 18 4.3 Design Approaches 19 5 Problem Analysis 23 5.1 Methodology 23 5.2 Identification of Use-Cases 24 5.3 Requirements Analysis 26 5.3.1 Functional requirements 26 5.3.2 Qualitative requirements 26 5.3.3 Acceptance criteria 27 6 Design 29 6.1 Preprocessing 29 6.2 Underlying Domain Specific Modelling 31 6.2.1 Language model definition 31 6.2.2 Formalization 32 6.2.3 Constraints 32 6.3 Generic Grammar Syntax 33 6.4 Architecture 36 6.5 Integration of AI Techniques 38 6.6 Grammar Improvement 40 6.6.1 Identification of synonyms 40 6.6.2 Automatic addition of synonyms 42 6.6.3 Addition of same-meaning strings 42 6.6.4 Addition and modification of rules 43 6.7 Processing of unrecognized input 44 6.8 Summary 45 7 Implementation and Evaluation 47 7.1 Development Environment 47 7.2 Implementation 48 7.2.1 Grammar model transformation 48 7.2.2 Output construction 50 7.2.3 Testing 50 7.2.4 Reusability for similar use-cases 51 7.3 Limitations and Challenges 52 7.4 Comparison to NLP Solutions 54 8 Conclusion 58 8.1 Summary of Findings 58 8.2 Future Research and Development 60 Acronyms 62 Bibliography 63 List of Figures 73 List of Tables 74 List of Listings 75

The integration of an opto-mechatronic screening module into the biomanufacturing workstation enables the automated, reproducible and user-independent production and analysis of hydrogels-based 3D cell cultures.:I. Introduction II. Methods and Materials III. Results IV. Conclusion References

Dies ist ein kurzer Überblick über Python-Projekte abseits von Einsatzmöglichkeiten im Beruf.:1. Einleitung 2. Python unterrichten 3. Mit Python promovieren 4. Mit Python chatten lassen 4.1. Implementation 4.2. Literaturwissenschaftlicher Hintergrund 5. Mit Python leben 6. Mit Python basteln Literatur

We present a case study as part of a work-in-progress project about multimodal sentiment analysis on historic German plays, taking Emilia Galotti by G. E. Lessing as our initial use case. We analyze the textual version and an audio version (audiobook). We focus on ready-to-use sentiment analysis methods: For the textual component, we implement a naive lexicon-based approach and another approach that enhances the lexicon by means of several NLP methods. For the audio analysis, we use the free version of the Vokaturi tool. We compare the results of all approaches and evaluate them against the annotations of a human expert, which serves as a gold standard. For our use case, we can show that audio and text sentiment analysis behave very differently: textual sentiment analysis tends to predict sentiment as rather negative and audio sentiment as rather positive. Compared to the gold standard, the textual sentiment analysis achieves accuracies of 56% while the accuracy for audio sentiment analysis is only 32%. We discuss possible reasons for these mediocre results and give an outlook on further steps we want to pursue in the context of multimodal sentiment analysis on historic plays.

We present a formal modeling approach for the design and simulation of Multi-Unmanned Aerial Vehicle (multi-UAV) inspection scenarios, where planning is based on model checking. As demonstration, we formalize and simulate a compositional UAV inspection system of a solar park using bigraphical reactive systems, which introduce the notion of time-varying bigraphs. Specifically, the UAV system is modeled as a process-algebraic expression, whose semantics is a bigraph state in a labeled transition system. The underlying Multi-Agent Path Finding problem is solved model-theoretically using Planning-by-Model-Checking. It solves the inherently connected collision-free path planning problem for multiple UAVs subject to contexts and local conditions. First, a bigraph is constructed algebraically, which can be decomposed systematically into separate parts with interfaces. The layered composite model accounts for location, navigation, UAVs, and contexts, which enables simple configuration and extension (changeability). Second, the executable operational semantics of our formal bigraph model are given by bigraphical reactive systems, where rules constitute the behavioral component of our model. Rules reconfigure the bigraph to simulate state changes, i.e., they allow to alter the conditions under which UAVs are permitted to move. Properties can be attached to nodes of the bigraph and evaluated in a simulation over the traces of the transition system according to some cost-based policies. In essence, the inherent multi-UAV path planning problem of our scenario is formulated as a reachability problem and solved by model checking the generated transition system. The bigraph-algebraic expression also allows us to reason about potential parallelization opportunities when moving UAVs. Moreover, we sketch how to directly simulate the bigraph specification in a ROS-based Gazebo simulation by examining the inspection and monitoring of a solar park as an application. The reactive system specification provides the blueprint for analysis, simulation, implementation and execution. Thus, the same algorithm used for verification is used as well for the simulation in ROS/Gazebo to execute plans.:1 Introduction 2 Overview: Scenario Description and Formal Modeling Approach 3 Background: Bigraphs and Model Checking 4 Construction of the UAV System via Composition 5 Making the Drones Fly: Executable Model Semantics 6 Collision-Free Path Planning Problem 7 Prototypical Implementation 8 Discussion 9 Related Work 10 Conclusion A UAV State Machine B Bigraphical Reactive Systems C RPO/IPO Semantic

Sowohl in der Forschung als auch in der industriellen Anwendung erfahren drahtlose Sensornetze (engl. Wireless Sensor Networks, WSN) eine immer höhere Popularität. Dies liegt nicht zuletzt an den Forschungsgebieten Car2X-Kommunikation, Internet of Things sowie Umweltüberwachung als Teil des Katastrophenschutzes. Typischer Schwerpunkt ist das energieeffiziente und latenzarme Übertragen von Informationen in einem drahtlos verknüpften Netz aus stark ressourcenbeschränkten Hardwareplattformen. Die Dissertation beschäftigt sich mit der Forschungsfrage, inwieweit Methoden und konkrete Algorithmen aus dem Big-Data-Computing vorteilhaft in drahtlosen Sensornetzen eingesetzt werden können. Während es im ersten Moment nicht intuitiv erscheinen mag, dass Ansätze aus dem Big-Data-Bereich, die bereits konventionelle Rechensysteme an ihre Grenzen bringen, für Sensornetze relevant sein sollen, zeigt die Arbeit Parallelen auf, die zwischen klassischem Big Data und einer Teilgruppe von Sensornetzen existieren. Im Rahmen der Arbeit wird dazu der Begriff drahtloses Big-Data-Sensornetz (Big Data WSN) definiert und darauf aufbauend werden Anforderungen an ein Datenaggregationssystem für ebensolche Sensornetze erörtert sowie konkrete Big-Data-Algorithmen konzeptionell übertragen und adaptiert. Es wird gezeigt, dass sich sogenannte datenbank-orientierte Aggregationssysteme zur Umsetzung dieser Anforderungen eignen und dass ein solches existierendes System für Big Data WSN erweitert werden kann. Die Hauptbeiträge der Dissertation sind die Vorstellung eines Routingverfahrens für Big Data WSN, das anwendungsrelevante Knoten energieeffizient ermittelt, die Übertragung von Big Data Algorithmen auf WSN zur Reduzierung der zu übertragenden beziehungsweise zu speichernden Datenmenge sowie ein Ereignissystem zur Steigerung der Energieeffizienz und Verringerung der Latenz von Ereignisreaktionen.:1. Einleitung 2. Grundlagen 3. Stand der Forschung 4. Konzeptionierung eines Aggregationsverfahrens für WSN im Big-Data-Kontext 5. Big-Data-WSN-Aggregationssystem Planetary 6. Auswertung und Ergebnisse 7. Zusammenfassung Anhang

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