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

Functional graphs


The best representation for a graph depends a little on the use case. The Graph type in containers uses an adjacency list and a few basic graph operations are provided.

One unique Haskell library, fgl, for Functional Graph Library, takes a different approach to programming with graphs, by considering graph as an inductive data-type.

One of the core ideas in fgl is contexts and decomposition. A context of a graph node is a triplet of the node's predecessors, successors, and the node itself. All graph manipulations can be expressed as inductive recursions over the contexts of a graph. Furthermore, it's surprisingly efficient.

For reference, here's a very, very small section of the fgl API:

-- module Data.Graph.Inductive.Graph

type Adj        b = [(b, Node)]

type Context  a b = (Adj b, Node, a, Adj b)

type Decomp g a b = (Mcontext a b, g a b)

empty :: Graph    gr => gr a b
match :: Graph    gr => Node → gr a b → Decomp gr a b
(&)   :: DynGraph gr => Context a...