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 started this chapter from GHC internal representation Core. We looked at the differences in Core syntax as opposed to Haskell syntax, among them explicit boxing, recursive bindings, explicit specialization and the passing of class dictionaries. Next, we took a glance at STG, the next internal representation after Core that's even simpler. Then we considered how GHC exposes its primitives: magic hash, unlifted types, and the unlifted kind.

Our second subject was code generation with GHC using GHC Generics. The essential idea with Generics is to represent every datatype as a sum of products using a handful of indexed datatypes (:+:, :*:, and so on). It then becomes easy to write general functions over all datatypes by converting to or from the general sum-of-products representation. Then we looked at full-blown code generation using Template Haskell, which enabled us to generate code, declarations and expressions by directly manipulating the program's abstract syntax tree.

In the...