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Haskell High Performance Programming

Haskell High Performance Programming

By : Thomasson
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Haskell High Performance Programming

Haskell High Performance Programming

3 (2)
By: 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 (16 chapters)
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15
Index

Summary

In this chapter, we have walked very quickly through a big bunch of libraries in different application areas. New libraries are constantly developed, and current ones are being improved. Lists in this chapter should be taken only as a guideline. It's always a good idea to do a little research before using a new library. The Haskell-Cafe mailing list is a good place to be notified about new libraries and major new releases, and is relatively low traffic.

During the course of this book, we have navigated many topics that have hopefully helped you become a better Haskeller.

If you followed closely the first few chapters, you have a good working understanding of lazy evaluation and its traps. You can use seq, bang patterns, and pragmas where necessary. You know many high-performance data structures and are able to use them effectively. In the middle chapters, we learned to test and benchmark, that lazy I/O has drawbacks, to parallelize code, to do concurrency safely and to compile...

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