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Parallel and Concurrent Programming in Haskell

Parallel and Concurrent Programming in Haskell

Parallel and Concurrent Programming in Haskell
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Parallel and Concurrent Programming in Haskell Papeback -

by Simon Marlow

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O'Reilly Media, Incorporated , pp. 322 . Papeback. New.
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Details

  • Title Parallel and Concurrent Programming in Haskell
  • Author Simon Marlow
  • Binding Papeback
  • Edition INTERNATIONAL ED
  • Condition New
  • Pages 319
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media, Incorporated
  • Publication date pp. 322
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index, Price on Product - Canadian, Table of Contents
  • Bookseller's Inventory # 654519358
  • ISBN 9781449335946 / 1449335942
  • Weight 1.12 lbs (0.51 kg)
  • Dimensions 9.47 x 6.72 x 0.69 in (24.05 x 17.07 x 1.75 cm)
  • Category Computers - Languages / Programming
  • Library of Congress subjects Parallel programming (Computer science), Haskell (Computer program language)
  • Dewey Decimal Code 004.35
  • Quantity available 3

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Reader reviews for Parallel and Concurrent Programming in Haskell

From the publisher

If you have a working knowledge of Haskell, this hands-on book shows you how to use the language's many APIs and frameworks for writing both parallel and concurrent programs. You'll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions.

Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented:

  • Express parallelism in Haskell with the Eval monad and Evaluation Strategies
  • Parallelize ordinary Haskell code with the Par monad
  • Build parallel array-based computations, using the Repa library
  • Use the Accelerate library to run computations directly on the GPU
  • Work with basic interfaces for writing concurrent code
  • Build trees of threads for larger and more complex programs
  • Learn how to build high-speed concurrent network servers
  • Write distributed programs that run on multiple machines in a network
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