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

Control and utility libraries


The libraries in this subsection are as follows:

  • conduit, io-streams, and pipes: General streaming libraries, that avoid problems with lazy IO

  • lens: Solving the "nested record update" problem in a "batteries included" fashion

  • convertible: Conversions between types using a single function without information loss

  • basic-prelude, classy-prelude: Prelude alternatives that encourage best practices in modern Haskell

  • chunked-data: Class abstractions to different builders, zipping, and reading and writing to files and handles

Streaming libraries are generally aimed at countering problems with lazy IO. Refer to Chapter 6, I/O and Streaming, for an in-depth discussion about problems with lazy IO and Haskell streaming libraries.

Using lenses

Lenses can be thought of as a generalization of getters and setters that compose well. A sore point of vanilla Haskell is nested record updates. The syntax is not very nice, for instance, this:

update rec new_c = rec { field_c = (field_c rec...