If you have a working knowledge of Haskell, this hands-on book shows you how to use the language's many APIs and frameworks for writing both parallel and concurrent programs. You'll 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…mehr
If you have a working knowledge of Haskell, this hands-on book shows you how to use the language's many APIs and frameworks for writing both parallel and concurrent programs. You'll 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 Strategies Parallelize ordinary Haskell code with the Par monad Build parallel array-based computations, using the Repa library Use the Accelerate library to run computations directly on the GPU Work with basic interfaces for writing concurrent code Build trees of threads for larger and more complex programs Learn how to build high-speed concurrent network servers Write distributed programs that run on multiple machines in a network
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.
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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 Colophon
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 Colophon
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