Haskell High Performance Programming Front Cover

Haskell High Performance Programming

  • Length: 408 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2016-09-26
  • ISBN-10: 1786464217
  • ISBN-13: 9781786464217
  • Sales Rank: #1315599 (See Top 100 Books)
Description

Key Features

  • Explore the benefits of lazy evaluation, compiler features, and tools and libraries designed for high performance
  • Write fast programs at extremely high levels of abstraction
  • Work through practical examples that will help you address the challenges of writing efficient code

Book Description

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.

What you will learn

  • Program idiomatic Haskell that’s also surprisingly efficient
  • Improve performance of your code with data parallelism, inlining, and strictness annotations
  • Profile your programs to identify space leaks and missed opportunities for optimization
  • Find out how to choose the most efficient data and control structures
  • Optimize the Glasgow Haskell Compiler and runtime system for specific programs
  • See how to smoothly drop to lower abstractions wherever necessary
  • Execute programming for the GPU with Accelerate
  • Implement programming to easily scale to the cloud with Cloud Haskell

About the Author

Samuli Thomasson is a long-time functional programming enthusiast from Finland who has used Haskell extensively, both as a pastime and commercially, for over four years. He enjoys working with great tools that help in getting things done nice and fast.

His current job at RELEX Solutions consists of providing technical solutions to a variety of practical problems. Besides functional programming, Samuli is interested in distributed systems, which he also studies at the University of Helsinki.

Table of Contents

Chapter 1. Identifying Bottlenecks
Chapter 2. Choosing the Correct Data Structures
Chapter 3. Profile and Benchmark to Your Heart’s Content
Chapter 4. The Devil’s in the Detail
Chapter 5. Parallelize for Performance
Chapter 6. I/O and Streaming
Chapter 7. Concurrency and Performance
Chapter 8. Tweaking the Compiler and Runtime System (GHC)
Chapter 9. GHC Internals and Code Generation
Chapter 10. Foreign Function Interface
Chapter 11. Programming for the GPU with Accelerate
Chapter 12. Scaling to the Cloud with Cloud Haskell
Chapter 13. Functional Reactive Programming
Chapter 14. Library Recommendations

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