Concurrent Programming In Ml
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Concurrent Programming in ML
Author: John H. Reppy
language: en
Publisher: Cambridge University Press
Release Date: 1999-08-13
Concurrent Programming ML (CML), included as part of the SML of New Jersey (SML/NJ) distribution, combines the best features of concurrent programming and functional programming. This practical, "how-to" book focuses on the use of concurrency to implement naturally concurrent applications. In addition to a tutorial introduction to programming in CML, the book presents three extended examples using CML for practical systems programming: a parallel software build system, a simple concurrent window manager, and an implementation of distributed tuple spaces. This book also illustrates advanced SML programming techniques, and includes a chapter on the implementation of concurrency using features provided by the SML/NJ system. It will be of interest to programmers, students, and professional researchers working in computer language development.
ML with Concurrency
Author: Flemming Nielson
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Both functional and concurrent programming are relatively new paradigms with great promise. In this book, a survey is provided of extensions to Standard ML, one of the most widely used functional languages, with new primitives for concurrent programming. Computer scientists and graduate students will find this a valuable guide to this topic.
Parallel and Concurrent Programming in Haskell
Author: Simon Marlow
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2013-07-12
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