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

Summary


We began this chapter with GHC primitives such as Int# and figured out the effects of strictness and unpacking annotations (bangs and UNPACK-pragmas) in data type definitions. We noted that tuples are lazy and that Bool is an algebraic data type, but we also noted that arrays and vectors represent Bool intelligently as single bits internally.

Then we considered working with numeric, binary, and textual data. We witnessed the performance of the bytestring, text, and vector libraries, all of which get their speed from fusion optimizations, in contrast to linked lists, which have a huge overhead despite also being subject to fusion to some degree. However, linked lists give rise to simple difference lists and zippers. The builder patterns for lists, bytestring, and text were introduced. We discovered that the array package is low-level and clumsy compared to the superior vector package, unless you must support Haskell 98. The Map type in containers was a binary tree, whereas some hashing...