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


In this chapter, we have learned to build distributed systems using the Cloud Haskell platform: launching nodes and processes, communicating via direct message passing between processes and with more flexible typed channels, passing remotely executed procedures in closures, and handling failure with process linking and monitoring. You now know how to build distributed systems with Cloud Haskell.

The next chapter will be about Functional Reactive Programming (FRP) and related Haskell libraries. Reactive programming, and especially FRP, challenges prevalent imperative control flow by a different notion of time. In imperative animation, for instance, timing is more or less implicit in the code, whereas in FRP, time would be just one more argument or input to an animation system. Reactive programming extends beyond just animation, though.