Boost the performance of your Haskell applications using optimization, concurrency, and parallel programming
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
Who this book is for
To get the most out of this book, you need to have a working knowledge of reading and writing basic Haskell. No knowledge of performance, optimization, or concurrency is required.
Table of Contents
Identifying Bottlenecks
Choose the Correct Data Structures
Profile and Benchmark to Your Heart's Content 30
The Devil is in the Detail
Parallelize for Performance
I/O and Streaming
Concurrency Performance
Tweaking the Compiler and Runtime System
GHC Internals and Code Optimizations
Foreign Function Interface: Saving the Last CPU Cycle