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Professional Parallel Programming with C#: Master Parallel Extensions with .NET 4

Professional Parallel Programming with C#: Master Parallel Extensions with .NET 4
  • Автор: Gaston Hillar
  • Издательство: Wrox
  • Год: 2010
  • Язык: Английский
  • Страниц: 576
  • Формат: pdf
  • Размер: 70 Мб

Описание книги Professional Parallel Programming with C#: Master Parallel Extensions with .NET 4:
As PC processors explode from one or two to now eight processors, there is an urgent need for programmers to master concurrent programming. This book dives deep into the latest technologies available to programmers for creating professional parallel applications using C#, .NET 4, and Visual Studio 2010. The book covers task-based programming, coordination data structures, PLINQ, thread pools, asynchronous programming model, and more. It also teaches other parallel programming techniques, such as SIMD and vectorization.

Are you maximizing the processing power in your multi-core computer systems? With this resource, you discover how to do exactly that, while gaining insight into concurrent programming with tasks to create professional parallel applications using C# 4, .Net 4, and Visual Studio 2010. You learn other parallel programming techniques, including modern single instruction, multiple data instructions and vectorization. Plus, you explore the possibilities offered by modern parallel libraries and advanced Intel tools with C#. Use the new lightweight coordination structures to tackle the most complex concurrent programming problems and develop your own customized solutions.

Professional Parallel Programming with C#:

- Focuses on creating scalable and reliable parallelized designs targeting the new Task Parallel Library and .NET 4
- Walks you through imperative data parallelism, imperative task parallelism, concurrent collections, and coordination data structures
- Describes advanced declarative data parallelism with PLINQ
- Describes how to debug anonymous methods, tasks, and threads by using the new Visual Studio® 2010 parallel debugging features
- Demonstrates how to partition data sources to load-balance the workload among diverse tasks and threads