Haskell is an elegant language. It allows us to express in code exactly what we mean, in a clean and compact style. The nice features, including referential transparency and call-by-need evaluation, not only help the programmer be more efficient, but also help Haskell compilers to optimize programs in ways that are otherwise plain impossible. For example, the garbage collector of GHC is notoriously fast, not least thanks to its ability to exploit the immutability of Haskell values.
Unfortunately, high expressivity is a double-edged sword. Reasoning the exact order of evaluation in Haskell programs is, in general, not an easy task. A lack of understanding of the lazy call-by-need evaluation in Haskell will for sure lead the programmer to introduce space leaks sooner or later. A productive Haskell programmer not only has to know how to read and write the language, which is a hard enough skill to achieve in itself, they also need to understand a new evaluation schema and some related details. Of course, in order to not make things too easy, just knowing the language well will not get you very far. In addition, one has to be familiar with at least a few common libraries and, of course, the application domain itself.
This book will give you working knowledge of high-performance Haskell programming, including parallelism and concurrency. In this book, we will cover the language, GHC, and the common libraries of Haskell.
Chapter 1, Identifying Bottlenecks, introduces you to basic techniques for optimal evaluation and avoiding space leaks.
Chapter 2, Choose the Correct Data Structures, works with and optimizes both immutable and mutable data structures.
Chapter 3, Profile and Benchmark to Your Heart's Content, profiles Haskell programs using GHC and benchmarking using Criterion.
Chapter 4, The Devil's in the Detail, explains the small details that affect performance in Haskell programs, including code sharing, specializing, and simplifier rules.
Chapter 5, Parallelize for Performance, exploits parallelism in Haskell programs using the RePa library for data parallelism.
Chapter 6, I/O and Streaming, talks about the pros and cons of lazy and strict I/O in Haskell and explores the concept of streaming.
Chapter 7, Concurrency Performance, explores the different aspects of concurrent programming, such as shared variables, exception handling, and software-transactional memory.
Chapter 8, Tweaking the Compiler and Runtime System, chooses the optimal compiler and runtime parameters for Haskell programs compiled with GHC.
Chapter 9, GHC Internals and Code Optimizations, delves deeper into the compilation pipeline, and understands the intermediate representations of GHC.
Chapter 10, Foreign Function Interface, calls safely to and from C in Haskell using GHC and its FFI support.
Chapter 11, Programming for the GPU with Accelerate, uses the Accelerate library to program backend-agnostic GPU programs and executes on CUDA-enabled systems.
Chapter 12, Scaling to the Cloud with Cloud Haskell, uses the Cloud Haskell ecosystem to build distributed systems with Haskell.
Chapter 13, Functional Reactive Programming, introduces three Haskell FRP libraries, including Elerea, Yampa, and Reactive-banana.
Chapter 14, Library Recommendations, talks about a catalogue of robust Haskell libraries, accompanied with overviews and examples.
To run most examples in this book, all you need is a working, relatively recent, installation of GHC and some Haskell libraries. Examples are built for nix-like systems, although they are easily adapted for a Windows machine.
The recommended minimum version for GHC is 7.6. The Haskell libraries needed are introduced in the chapters in which they are used. In Chapter 4, The Devil's in the Detail, we use the Haskell Stack tool to perform some tasks, but it isn't strictly required, although it is recommended to install Stack.
In Chapter 11, Programming for the GPU Using Accelerate, executing the CUDA versions of examples requires a CUDA-enabled system and the installation of the CUDA platform.
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.
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include directive."
A block of code is set as follows:
mySum [1..100]
= 1 + mySum [2..100]
= 1 + (2 + mySum [2..100])
= 1 + (2 + (3 + mySum [2..100]))
= ...
= 1 + (2 + (... + mySum [100]))
= 1 + (2 + (... + (100 + 0)))When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
mySum [1..100]
= 1 + mySum [2..100]
= 1 + (2 + mySum [2..100])
= 1 + (2 + (3 + mySum [2..100]))
= ...
= 1 + (2 + (... + mySum [100]))
= 1 + (2 + (... + (100 + 0)))Any command-line input or output is written as follows:
> let xs = enumFromTo 1 5 :: [Int] > :sprint xs
New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Clicking the Next button moves you to the next screen."
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