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

Parallel and concurrent programming


The libraries in this subsection are as follows:

  • Control.Concurrent (base): The basic concurrency primitives

  • parallel: Primitive parallel programming and parallel evaluation strategies

  • monad-par: Provides the Par and ParIO monads for simple pure and IO parallel programming

  • abstract-par, monad-par-extras: Add-on libraries to monad-par, that add extra combinators and a further abstraction layer over different Par implementations

  • repa: Data-parallel arrays

Parallel programming and the use and features of libraries parallel and monad-par is considered in Chapter 5, Parallelize for Performance. The RePa library is also featured in that chapter.

In short, the parallel library is used to express parallelism deterministically, and more importantly to separate parallelism from program logic. This enhances modularity and composition. The monad-par library, on the other hand, ties computation with its parallel evaluation, in return giving more control over how evaluation...