Book Image

Haskell High Performance Programming

By : Samuli Thomasson
Book Image

Haskell High Performance Programming

By: Samuli Thomasson

Overview of this book

Haskell, with its power to optimize the code and its high performance, is a natural candidate for high performance programming. It is especially well suited to stacking abstractions high with a relatively low performance cost. This book addresses the challenges of writing efficient code with lazy evaluation and techniques often used to optimize the performance of Haskell programs. We open with an in-depth look at the evaluation of Haskell expressions and discuss optimization and benchmarking. You will learn to use parallelism and we'll explore the concept of streaming. We’ll demonstrate the benefits of running multithreaded and concurrent applications. Next we’ll guide you through various profiling tools that will help you identify performance issues in your program. We’ll end our journey by looking at GPGPU, Cloud and Functional Reactive Programming in Haskell. At the very end there is a catalogue of robust library recommendations with code samples. By the end of the book, you will be able to boost the performance of any app and prepare it to stand up to real-world punishment.
Table of Contents (21 chapters)
Haskell High Performance Programming
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Handling tabular data


If you need O(1) general indexing, a table-like data structure is virtually your only option. The Haskell report specifies the array package, which provides tables indexed by anything with an instance for a Ix typeclass.

Immutable arrays come in two flavors (we'll discuss mutable arrays later):

  • Data.Array.Array: Immutable arrays of boxed values

  • Data.Array.Unboxed.UArray: Immutable arrays of unboxed values

A common use case for Immutable arrays is memoization. For example, a table of Fibonacci numbers could be constructed as follows:

-- file: fib-array-mem.hs
import Data.Array

fib :: Int -> Array Int Integer
fib n = arr where
  arr = listArray (1,n) $ 1 : 1 : [ arr!(i-2) + arr!(i-1)| i <- [3..n] ]

We can also index by a tuple, which gives the array extra dimensions. The symmetric Pascal matrix will serve as an example:

pascal :: Int -> Array (Int, Int) Integer
pascal n = arr where
  arr = array ((1,1),(n,n)) $
    [ ((i,1),1) | i <- [1..n] ] ++
    [ ((1,j),1)...