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Haskell High Performance Programming
Haskell High Performance Programming

Haskell High Performance Programming: Write Haskell programs that are robust and fast enough to stand up to the needs of today

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Haskell High Performance Programming

Chapter 1. Identifying Bottlenecks

You have probably at least once written some very neat Haskell you were very proud of, until you test the code and it took ages to give an answer or even ran out of memory. This is very normal, especially if you are used to performance semantics in which performance can be analyzed on a step-by-step basis. Analyzing Haskell code requires a different mental model that is more akin to graph traversal.

Luckily, there is no reason to think that writing efficient Haskell is sorcery known only by math wizards or academics. Most bottlenecks are straightforward to identify with some understanding of Haskell's evaluation schema. This chapter will help you to reason about the performance of Haskell programs and to avoid some easily recognizable patterns of bad performance:

  • Understanding lazy evaluation schemas and their implications
  • Handling intended and unintended value memoization (CAFs)
  • Utilizing (guarded) recursion and the worker/wrapper pattern efficiently
  • Using accumulators correctly to avoid space leaks
  • Analyzing strictness and space usage of Haskell programs
  • Important compiler code optimizations, inlining and fusion
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Key benefits

  • 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

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.

Who is this book 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.

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
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 26, 2016
Length: 408 pages
Edition : 1st
Language : English
ISBN-13 : 9781786464217
Vendor :
The Glasgow Haskell Team
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Length: 408 pages
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ISBN-13 : 9781786464217
Vendor :
The Glasgow Haskell Team
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Table of Contents

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

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(2 Ratings)
5 star 0%
4 star 50%
3 star 0%
2 star 50%
1 star 0%
Oswald Michael Nov 19, 2019
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
This book is ok to get an overview over performance in Haskell. On certain topics it does not delve very deep (which I would have wished for). But to get a bit of feel about what matters for performance in Haskell, it is really ok.Some Haskell source had a bad formatting inside (spaces got removed, so identifiers are not right), but with a little understanding it is clear what is meant.
Amazon Verified review Amazon
Kevin S. Van Horn Feb 26, 2020
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
The book is full of typos and inconsistencies that suggest the author never did a final review of the manuscript. New concepts (e.g. guarded recursion) are often ambiguously or incompletely defined, or defined only by example. Very sloppy writing.
Amazon Verified review Amazon
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