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

Trivia at term-level


In this section, we look at lazy patterns, using the magic hash, controlling inlining and using rewrite rules. These are small things used rarely in applications, but nevertheless are very convenient where applicable.

We'll start with lazy patterns. Where strict pattern annotations use bangs and mean "Evaluate this argument to WHNF immediately," lazy pattern annotations use tildes and imply "Don't even bother pattern-matching unless a binding is really requested." So this errors:

> let f (a,b) = 5
> f undefined
*** Exception: Prelude.undefined

But with a lazy pattern match, we are all okay:

> let f ~(a,b) = 5
> f undefined
5

A more realistic use case for lazy patterns is the classic server-client setting. The client makes requests sequentially and can change the request based on previous responses. We can express this in Haskell elegantly with just linked lists. The server is slightly simpler than the client: it just applies a computation on every request...