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Haskell Data Analysis cookbook

You're reading from   Haskell Data Analysis cookbook Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783286331
Length 334 pages
Edition 1st Edition
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Author (1):
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Nishant Shukla Nishant Shukla
Author Profile Icon Nishant Shukla
Nishant Shukla
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Hunt for Data FREE CHAPTER 2. Integrity and Inspection 3. The Science of Words 4. Data Hashing 5. The Dance with Trees 6. Graph Fundamentals 7. Statistics and Analysis 8. Clustering and Classification 9. Parallel and Concurrent Design 10. Real-time Data 11. Visualizing Data 12. Exporting and Presenting Index

Parallelizing pure functions using the Par monad

The Par monad from the Control.Monad.Par package is used to speed up pure functions using parallel threads. Information flow is guided by variables called IVar. We can put values to IVar in parallel or get values from it.

Getting ready

Install the Par monad on cabal as follows:

$ cabal install monad-par

How to do it…

  1. Import the Par monad as follows:
    import Control.Monad.Par
  2. Run a computation in parallel, and perform some interesting function such as counting the number of digits and printing it out.
    main = print $ length $ show $ runPar mypar
  3. Define an I/O type action as follows:
    mypar = do 
      v1 <- new :: Par (IVar Integer)
      v2 <- new :: Par (IVar Integer)
      fork $ put v1 task1
      fork $ put v2 task2
      v1' <- get v1
      v2' <- get v2
      return (v1' + v2')  
  4. Perform a time-consuming task as follows:
    task1 = 8^8^8
  5. Perform another time-consuming task as follows:
    task2 = 8^8^7
  6. Compile the code with the threaded and rtsopts...
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