This proceedings volume contains selected papers that were presented in the 3rd International Symposium on Big data and Cloud Computing Challenges, 2016 held at VIT University, India on March 10 and 11. New research issues, challenges and opportunities shaping the future agenda in the field of Big Data and Cloud Computing are identified and presented throughout the book, which is intended for researchers, scholars, students, software developers and practitioners working at the forefront in their field. This book acts as a platform for exchanging ideas, setting questions for discussion, and sharing the experience in Big Data and Cloud Computing domain.​

The volume contains the papers presented at FICTA 2012: International Conference on Frontiers in Intelligent Computing: Theory and Applications held on December 22-23, 2012 in Bhubaneswar engineering College, Bhubaneswar, Odissa, India. It contains 86 papers contributed by authors from the globe. These research papers mainly focused on application of intelligent techniques which includes evolutionary computation techniques like genetic algorithm, particle swarm optimization techniques, teaching-learning based optimization etc for various engineering applications such as data mining, image processing, cloud computing, networking etc.

Containing over 300 entries in an A-Z format, the Encyclopedia of Parallel Computing provides easy, intuitive access to relevant information for professionals and researchers seeking access to any aspect within the broad field of parallel computing. Topics for this comprehensive reference were selected, written, and peer-reviewed by an international pool of distinguished researchers in the field. The Encyclopedia is broad in scope, covering machine organization, programming languages, algorithms, and applications. Within each area, concepts, designs, and specific implementations are presented. The highly-structured essays in this work comprise synonyms, a definition and discussion of the topic, bibliographies, and links to related literature. Extensive cross-references to other entries within the Encyclopedia support efficient, user-friendly searchers for immediate access to useful information. Key concepts presented in the Encyclopedia of Parallel Computing include; laws and metrics; specific numerical and non-numerical algorithms; asynchronous algorithms; libraries of subroutines; benchmark suites; applications; sequential consistency and cache coherency; machine classes such as clusters, shared-memory multiprocessors, special-purpose machines and dataflow machines; specific machines such as Cray supercomputers, IBM’s cell processor and Intel’s multicore machines; race detection and auto parallelization; parallel programming languages, synchronization primitives, collective operations, message passing libraries, checkpointing, and operating systems. Topics covered: Speedup, Efficiency, Isoefficiency, Redundancy, Amdahls law, Computer Architecture Concepts, Parallel Machine Designs, Benmarks, Parallel Programming concepts & design, Algorithms, Parallel applications. This authoritative reference will be published in two formats: print and online. The online edition features hyperlinks to cross-references and to additional significant research. Related Subjects: supercomputing, high-performance computing, distributed computing

This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2012, held in Tokyo, Japan, in September 2012. The 16 revised full papers, 5 poster papers presented with 1 invited talk were carefully reviewed and selected from 39 submissions. The focus of the papers is on following topics: compiling for parallelism, automatic parallelization, optimization of parallel programs, formal analysis and verification of parallel programs, parallel runtime systems, task-parallel libraries, parallel application frameworks, performance analysis tools, debugging tools for parallel programs, parallel algorithms and applications.

This book provides readers with a comprehensive, state-of-the-art overview of approximate computing, enabling the design trade-off of accuracy for achieving better power/performance efficiencies, through the simplification of underlying computing resources. The authors describe in detail various efforts to generate approximate hardware systems, while still providing an overview of support techniques at other computing layers. The book is organized by techniques for various hardware components, from basic building blocks to general circuits and systems.

Today's work is characterized by a high degree of innovation and thus demands a thorough overview of relevant knowledge in the world and in organizations. Semantic Work Environments support the work of the user by collecting knowledge about needs and providing processed and improved knowledge to be integrated into work. Emerging Technologies for Semantic Work Environments: Techniques, Methods, and Applications describes an overview of the emerging field of Semantic Work Environments by combining various research studies and underlining the similarities between different processes, issues and approaches in order to provide the reader with techniques, methods, and applications of the study.

"This book presents, discusses, shares ideas, results and experiences on the recent important advances and future challenges on enabling technologies for achieving higher performance"--Provided by publisher.

Collects in four chapters single monographs related to the fundamental advances in parallel computer systems and their developments from different points of view (from computer scientists, computer manufacturers, end users) and related to the establishment and evolution of grids fundamentals, implementation and deployment.

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the 33rd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include distributed massive data streams, storage systems, scientific workflow scheduling, cost optimization of data flows, and fusion strategies.