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

Data parallel programming – Repa


Repa (regular parallel) is a Haskell library providing regular parallel arrays. Repa performs very well in image processing, for example. Doing computations on large data structures in parallel is Repa's specialty. Repa is installed with:

stack install repa

The parts on Repa in this chapter are written for version 3.4.0.2 of the Repa library. The main interface is exported by the Data.Array.Repa module.

At first glance, the library perhaps looks a bit complex. For instance, the parallel sum function has this daunting type signature:

sumAllP:: (Shape sh, Source r a, Elt a, Unbox a, Num a, Monad m)=> Array r sh a -> m a

Repa uses a lot of classes to overload functionality over different types of array. The type of immutable arrays in Repa contains three type variables:

data Array r sh e

Here, r defines representation, sh defines shape, and e defines the array elements' type. For example, a one-dimensional array of unboxed Int is given by:

Array U DIM1 Int

Mutable...