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

Ephemeral data structures


Lazy evaluation, functional code, and persistent data structures are nice and all, but they are not meant to wholly replace imperative strict evaluation, imperative code, and ephemeral structures. Nor vice versa. Instead, all complement each other. Although the default evaluation in Haskell is strict and a functional style is strongly encouraged, Haskell is more than capable of providing for programming in imperative style:

 

"In short, Haskell is the world's finest imperative programming language."

 
 --Simon Peyton Jones (in his paper Tackling the Awkward Squad)

Imperative programming calls for sequential processing. In Haskell, we tackle sequential steps with monads. The monad of choice for ephemeral data structures is IO or ST. ST (for state threads) behaves a bit more nicely than IO in that you cannot launch missiles from ST. An ST action can be executed in pure code, or converted to an IO action:

import Control.Monad.ST

runST :: (forall s. ST s a) -> a
stToIO...