Simon Marlow

Parallel and Concurrent Programming in Haskell (eBook, PDF)

Techniques for Multicore and Multithreaded Programming

• Format: PDF

Produktbeschreibung

If you have a working knowledge of Haskell, this hands-on book shows you how to use the languages many APIs and frameworks for writing both parallel and concurrent programs. Youll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions.Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented:Express parallelism in Haskell with the Eval monad and Evaluation StrategiesParallelize ordinary Haskell code with the Par monadBuild parallel array-based computations, using the Repa libraryUse the Accelerate library to run computations directly on the GPUWork with basic interfaces for writing concurrent codeBuild trees of threads for larger and more complex programsLearn how to build high-speed concurrent network serversWrite distributed programs that run on multiple machines in a network

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Produktdetails

• Verlag: O'Reilly Media
• Seitenzahl: 322
• Erscheinungstermin: 12. Juli 2013
• Englisch
• ISBN-13: 9781449335922
• Artikelnr.: 39142466

Autorenporträt

Simon Marlow has been a prominent figure in the Haskell community formany years. He is the author of large parts of the Glasgow HaskellCompiler, including in particular its highly regarded mulitcoreruntime system, along with many of the libraries and tools thatHaskell programmers take for granted. Simon also contributes to thefunctional programming research community, and has a string of paperson subjects ranging from garbage collection to language design. Inrecent years Simon's focus has been on making Haskell an idealprogramming language for parallel and concurrent applications, both bydeveloping new programming models and building a high-qualityimplementation. Simon spent 14 years at Microsoft's Research laborotory in Cambridge,before taking a break in Spring 2013 to work on this book. Hecurrently works at Facebook UK.

Inhaltsangabe

Preface
Audience
How to Read This Book
Conventions Used in This Book
Using Sample Code
Safari® Books Online
How to Contact Us
Acknowledgments
Chapter 1: Introduction
1.1 Terminology: Parallelism and Concurrency
1.2 Tools and Resources
1.3 Sample Code
Parallel Haskell
Chapter 2: Basic Parallelism: The Eval Monad
2.1 Lazy Evaluation and Weak Head Normal Form
2.2 The Eval Monad, rpar, and rseq
2.3 Example: Parallelizing a Sudoku Solver
2.4 Deepseq
Chapter 3: Evaluation Strategies
3.1 Parameterized Strategies
3.2 A Strategy for Evaluating a List in Parallel
3.3 Example: The K-Means Problem
3.4 GC'd Sparks and Speculative Parallelism
3.5 Parallelizing Lazy Streams with parBuffer
3.6 Chunking Strategies
3.7 The Identity Property
Chapter 4: Dataflow Parallelism: The Par Monad
4.1 Example: Shortest Paths in a Graph
4.2 Pipeline Parallelism
4.3 Example: A Conference Timetable
4.4 Example: A Parallel Type Inferencer
4.5 Using Different Schedulers
4.6 The Par Monad Compared to Strategies
Chapter 5: Data Parallel Programming with Repa
5.1 Arrays, Shapes, and Indices
5.2 Operations on Arrays
5.3 Example: Computing Shortest Paths
5.4 Folding and Shape-Polymorphism
5.5 Example: Image Rotation
5.6 Summary
Chapter 6: GPU Programming with Accelerate
6.1 Overview
6.2 Arrays and Indices
6.3 Running a Simple Accelerate Computation
6.4 Scalar Arrays
6.5 Indexing Arrays
6.6 Creating Arrays Inside Acc
6.7 Zipping Two Arrays
6.8 Constants
6.9 Example: Shortest Paths
6.10 Example: A Mandelbrot Set Generator
Concurrent Haskell
Chapter 7: Basic Concurrency: Threads and MVars
7.1 A Simple Example: Reminders
7.2 Communication: MVars
7.3 MVar as a Simple Channel: A Logging Service
7.4 MVar as a Container for Shared State
7.5 MVar as a Building Block: Unbounded Channels
7.6 Fairness
Chapter 8: Overlapping Input/Output
8.1 Exceptions in Haskell
8.2 Error Handling with Async
8.3 Merging
Chapter 9: Cancellation and Timeouts
9.1 Asynchronous Exceptions
9.2 Masking Asynchronous Exceptions
9.3 The bracket Operation
9.4 Asynchronous Exception Safety for Channels
9.5 Timeouts
9.6 Catching Asynchronous Exceptions
9.7 mask and forkIO
9.8 Asynchronous Exceptions: Discussion
Chapter 10: Software Transactional Memory
10.1 Running Example: Managing Windows
10.2 Blocking
10.3 Blocking Until Something Changes
10.4 Merging with STM
10.5 Async Revisited
10.6 Implementing Channels with STM
10.7 An Alternative Channel Implementation
10.8 Bounded Channels
10.9 What Can We Not Do with STM?
10.10 Performance
10.11 Summary
Chapter 11: Higher-Level Concurrency Abstractions
11.1 Avoiding Thread Leakage
11.2 Symmetric Concurrency Combinators
11.3 Adding a Functor Instance
11.4 Summary: The Async API
Chapter 12: Concurrent Network Servers
12.1 A Trivial Server
12.2 Extending the Simple Server with State
12.3 A Chat Server
Chapter 13: Parallel Programming Using Threads
13.1 How to Achieve Parallelism with Concurrency
13.2 Example: Searching for Files
Chapter 14: Distributed Programming
14.1 The Distributed-Process Family of Packages
14.2 Distributed Concurrency or Parallelism?
14.3 A First Example: Pings
14.4 Multi-Node Ping
14.5 Typed Channels
14.6 Handling Failure
14.7 A Distributed Chat Server
14.8 Exercise: A Distributed Key-Value Store
Chapter 15: Debugging, Tuning, and Interfacing with Foreign Code
15.1 Debugging Concurrent Programs
15.2 Tuning Concurrent (and Parallel) Programs
15.3 Concurrency and the Foreign Function Interface
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