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

Chapter 1. Identifying Bottlenecks

You have probably at least once written some very neat Haskell you were very proud of, until you test the code and it took ages to give an answer or even ran out of memory. This is very normal, especially if you are used to performance semantics in which performance can be analyzed on a step-by-step basis. Analyzing Haskell code requires a different mental model that is more akin to graph traversal.

Luckily, there is no reason to think that writing efficient Haskell is sorcery known only by math wizards or academics. Most bottlenecks are straightforward to identify with some understanding of Haskell's evaluation schema. This chapter will help you to reason about the performance of Haskell programs and to avoid some easily recognizable patterns of bad performance:

  • Understanding lazy evaluation schemas and their implications

  • Handling intended and unintended value memoization (CAFs)

  • Utilizing (guarded) recursion and the worker/wrapper pattern efficiently

  • Using accumulators correctly to avoid space leaks

  • Analyzing strictness and space usage of Haskell programs

  • Important compiler code optimizations, inlining and fusion