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

Threads and concurrency primitives


One of the basic forms of concurrent programming involves sharing read-write data between threads. Usually data is shared via references. From fastest to most flexible, the three types of mutable references in Haskell are IORef, MVar, and STM. All three can be used, at least to some extent, in a thread-safe manner. We start our concurrent journey with a simple reference, IORef, and work our way to arbitrarily complex transactions using STM.

Threads and mutable references

The most basic reference type in Haskell is IORef. The core IORef API is compact, one datatype and a few atomic operations:

module Data.IORef

data IORef a

newIORef :: a → IO (IORef a)
readIORef :: IORef a → IO a
writeIORef :: IORef a → a → IO ()
modifyIORef :: IORef a → (a → a) → IO ()
atomicModifyIORef :: IORef a → (a → (a, b)) → IO b

IORef is always full, that is, there is always a value to be read without blocking. They're just simple mutable references. IORef is very fast. They're the...