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Book Is ForThose new data-parallel programming and computer programmers interested in data-parallel programming using C++.;
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code examples to illustrate key topics. Data parallelism in C++ enables access to parallel resources in a modern heterogeneous system;
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Data-Parallel Programming demonstrates that architecture-independent parallel programming is possible by describing in detail how programs;
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Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate;
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Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate;
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A parallel series to 'Country Files'. Includes maps, graphs, charts, data boxes, websites and key fact panels. Simple, clear text and full;
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Symposium on Advances of Distributed and Parallel Computing (ADPC 2013), 5 papers of the International Workshop on Big Data Computing (BDC 2013), 10;
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using C programs? Using the under-employed printer adapter (that is, the parallel port of your PC), you can turn your computer into a powerful;
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parallel (BSP) model to design and implement parallel algorithms in the areas of scientific computing and big data, and provides a full treatment;
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parallel (BSP) model to design and implement parallel algorithms in the areas of scientific computing and big data, and provides a full treatment;
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Algorithms and Data Structures in C++ introduces modern issues in the theory of algorithms, emphasizing complexity, graphs, parallel;
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of massively-parallel computing with the comfort of sequential programming. Parallel Programming Using C++ describes fifteen parallel programming;
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The SpringerBrief introduces FasTensor, a powerful parallel data programming model developed for big data applications. This book also;
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Learn the fundamentals of x86 Single instruction multiple data (SIMD) programming using C++ intrinsic functions and x86-64 assembly;
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Learn the fundamentals of x86 Single instruction multiple data (SIMD) programming using C++ intrinsic functions and x86-64 assembly;
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programming allows the developer to remain focused on the work an application needs to perform. In Pro .NET 4 Parallel Programming in C#, Adam;
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Multiple Data; heterogeneous systems, a new parallel programming model to offload computation to accelerators; and the expected further development;
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This book discusses advanced topics such as R core programing, object oriented R programing, parallel computing with R, and spatial data;
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This book discusses advanced topics such as R core programing, object oriented R programing, parallel computing with R, and spatial data;
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An introduction to parallel programming with openmpi using C. It is written so that someone with even a basic understanding of programming;
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, then this book is for you. If you are already comfortable with C# but want to learn more about parallel design patterns, threads, tasks, and;
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any online entitlements included with the product. The Definitive Guide to C# From using LINQ to covariance and from string formatting to;
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Over 70 recipes to get you writing powerful and efficient multithreaded, asynchronous, and parallel programs in C# 6.0 About This Book;
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simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance;
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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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