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. This has generated great interest in the study of algorithms for data processing on large distributed clusters. Algorithmic Aspects of Parallel;
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structures and indexing for cloud databases; new algorithmic aspects of parallel and distributed computing for cloud applications; scalable machine;
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raster data structures and details the algorithmic design for some major GIS operations. An implementation case study is included, based around a;
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The latest techniques and principles of parallel and grid database processing The growth in grid databases, coupled with the utility;
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geometry algorithms, data allocation strategies for parallel image processing algorithms, complexity analysis of parallel image operators. The;
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algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with;
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covers the use, administration, and tuning of these features: parallel query, parallel data loading, parallel DML (Data Manipulation Language;
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The volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be;
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the recent advances in big data processing; parallel architectures and systems; parallel software; parallel algorithms and applications; and;
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Parallel Computing Architectures and APIs: IoT Big Data Stream Processing commences from the point high-performance uniprocessors were;
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submissions. They deal with the recent advances in big data processing; parallel architectures and systems; parallel software; parallel algorithms and;
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in two main tracks: algorithmic aspects of large-scale data stores, and software tools and distributed architectures for cloud-based data;
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of Performance-Related Data in Parallel CFD Applications is available open access under a Creative Commons Attribution 4.0 International License via;
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Fourier transforms of large multidimensional data sets arise in many fields --ranging from seismology to medical imaging. The rapidly;
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Probabilistic data is motivated by the need to model uncertainty in large databases. Over the last twenty years or so, both the Database;
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The development of parallel processing, with the attendant technology of advanced software engineering, VLSI circuits, and artificial;
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Parallel programming is designed for the use of parallel computer systems for solving time-consuming problems that cannot be solved on a;
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shared digital data repositories and annotation standards for benchmarking the algorithmic feasibility and successive implementation;
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Parallel Supercomputing in MIMD Architectures is devoted to supercomputing on a wide variety of Multiple-Instruction-Multiple-Data (MIMD;
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; parallel I/O libraries and strategies for file striping, prefetching, and write behind; compilation strategies for out-of-core data access;
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While the areas of information management and management science are full of algorithmic challenges, the proliferation of data has called;
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This book constitutes the proceedings of the workshops of the 23rd International Conference on Parallel and Distributed Computing, Euro;
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common prefix (LCP) array, the document array and the Lyndon array. These data structures are the cornerstone of many algorithmic solutions;
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relatively simple operations need to be performed on a large number of data elements (pixels). Though many parallel processing architectures for;
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lack relevant research and understanding. Formal and Adaptive Methods for Automation of Parallel Programs Construction: Emerging Research;
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lack relevant research and understanding. Formal and Adaptive Methods for Automation of Parallel Programs Construction: Emerging Research;
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Parallel Processing, ICA3PP 2018, held in Guangzhou, China, in November 2018. The 141 full and 50 short papers presented were carefully;
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