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With the growing popularity of the Semantic Web, more and more semantic data and data sources become available and accessible for everyone. By establishing semantic links between the data, answers to (complex) queries can be evaluated based on the data on multiple providers instead of just one. This book motivates, introduces, and details techniques for processing heterogeneous structured data on the Web by providing a comprehensive overview for database researchers and practitioners about this new publishing paradigm on the web, and show how the abundance of data published as Linked Data can serve as a fertile ground for database research and experimentation--

Information systems --- Library automation --- Computer architecture. Operating systems --- Linked data --- Database management --- Data structures (Computer science) --- Semantic web --- Heterogeneous computing --- Linked data. --- Database management. --- Semantic Web. --- Heterogeneous computing. --- Computers --- Database Management --- General. --- Data Mining. --- Internet --- Data structures (Computer science).

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This book provides embedded software developers with techniques for programmingheterogeneous Multi-Processor Systems-on-Chip (MPSoCs), capable of executing multiple applications simultaneously. It describes a set of algorithms and methodologies to narrow the software productivity gap, as well as an in-depth description of the underlying problems and challenges of today’s programming practices. The authors present four different tool flows: A parallelism extraction flow for applications writtenusing the C programming language, a mapping and scheduling flow for parallel applications, a special mapping flow for baseband applications in the context of Software Defined Radio (SDR) and a final flow for analyzing multiple applications at design time. The tool flows are evaluated on Virtual Platforms (VPs), which mimic different characteristics of state-of-the-art heterogeneous MPSoCs.   • Provides a novel set of algorithms and methodologies for programming heterogeneous Multi-Processor Systems-on-Chip (MPSoCs); • Equips embedded software developers with a unified presentation of sequential and parallel programming; • Focuses on industry-relevant methodologies and uses real case studies to demonstrate techniques; • Enables solution of multi-application problems, with generalized and unified programming models.

Embedded computer systems --- Systems on a chip. --- SOC design --- Systems on chip --- Programming. --- Computer architecture -- Congresses. --- Embedded computer systems -- Congresses. --- Embedded computer systems -- Design and construction. --- Heterogeneous computing. --- Systems engineering. --- Computer science. --- Electronics. --- Circuits and Systems. --- Processor Architectures. --- Electronics and Microelectronics, Instrumentation. --- Informatics --- Science --- Engineering systems --- System engineering --- Engineering --- Industrial engineering --- System analysis --- Electrical engineering --- Physical sciences --- Design and construction --- Electronic circuits. --- Microprocessors. --- Microelectronics. --- Microminiature electronic equipment --- Microminiaturization (Electronics) --- Electronics --- Microtechnology --- Semiconductors --- Miniature electronic equipment --- Minicomputers --- Electron-tube circuits --- Electric circuits --- Electron tubes

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Numerical programs often use parallel programming techniques such as OpenMP to compute the program's output values as efficient as possible. In addition, derivative values of these output values with respect to certain input values play a crucial role. To achieve code that computes not only the output values simultaneously but also the derivative values, this work introduces several source-to-source transformation rules. These rules are based on a technique called algorithmic differentiation. The main focus of this work lies on the important reverse mode of algorithmic differentiation. The inherent data-flow reversal of the reverse mode must be handled properly during the transformation. The first part of the work examines the transformations in a very general way since pragma-based parallel regions occur in many different kinds such as OpenMP, OpenACC, and Intel Phi. The second part describes the transformation rules of the most important OpenMP constructs. Contents Introduction with Examples from Numerical Optimization Algorithmic Differentiation by Source Transformation Transformation rules for Parallel Code Regions (e.g. OpenMP 3.1) Static Program Analysis Target Groups Lecturers and students of computer science Computer scientists, engineers, mathematicians and numerical analysts The Author Michael Förster is currently Research Associate of the Institute Software and Tools for Computational Engineering, RWTH Aachen University.

Parallel programming (Computer science) --- OpenMP. --- Heterogeneous computing. --- Computer networks. --- OpenMP (Application program interface) --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Heterogeneous processing (Computers) --- High performance computing --- Parallel processing (Electronic computers) --- Computer programming --- Distributed processing --- Open Multi-Processing (Application program interface) --- Computer science. --- Artificial intelligence. --- Engineering mathematics. --- Mathematics of Computing. --- Artificial Intelligence. --- Mathematical and Computational Engineering. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Engineering --- Engineering analysis --- Mathematical analysis --- Informatics --- Science --- Mathematics --- Computer science --- Applied mathematics. --- Mathematics. --- Computer science—Mathematics. --- Computer mathematics --- Mathematical and Computational Engineering Applications. --- Data processing.