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  • Book Overview & Buying Concurrency with Modern C++
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Concurrency with Modern C++

Concurrency with Modern C++

By : Rainer Grimm
Buy this Book
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Concurrency with Modern C++

Concurrency with Modern C++

By: Rainer Grimm
Buy this Book

Overview of this book

C++11 is the first C++ standard that deals with concurrency. The story goes on with C++17 and will continue with C++20/23. Concurrency with Modern C++ is a practical guide that gets you to grips with concurrent programming in Modern C++. Starting with the C++ memory model and using many ready-to-run code examples, the book covers everything you need to improve your C++ multithreading skills. You'll gain insight into different design patterns. You'll also uncover the general consideration you have to keep in mind while designing a concurrent data structure. The final chapter in the book talks extensively about the common pitfalls of concurrent programming and ways to overcome these hurdles. By the end of the book, you'll have the skills to build your own concurrent programs and enhance your knowledge base.
Table of Contents (19 chapters)
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1
Reader Testimonials
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Reader Testimonials
2
Introduction
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Introduction
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Conventions
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Source Code
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How you should read the book?
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Personal Notes
3
Concurrency with Modern C++
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Concurrency with Modern C++
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C++11 and C++14: The Foundation
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C++17: Parallel Algorithms of the Standard Template Library
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The Near Future: C++20
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Case Studies
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The Future: C++23
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Patterns and Best Practices
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Challenges
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Time Library
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CppMem
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Glossary
4
Memory Model
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Memory Model
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Basics of the Memory Model
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The Contract
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Atomics
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The Class Template std::atomic_ref (C++20)
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The Synchronisation and Ordering Constraints
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Fences
5
Multithreading
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Multithreading
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Threads
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Shared Data
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Thread-Local Data
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Condition Variables
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Tasks
6
Parallel Algorithms of the Standard Template Library
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Parallel Algorithms of the Standard Template Library
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Execution Policies
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Algorithms
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The New Algorithms
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Performance
7
The Near Future: C++20
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The Near Future: C++20
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A Cooperatively Interruptible Joining Thread
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Atomic Smart Pointers
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Latches and Barriers
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Semaphores
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Coroutines
8
Case Studies
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Case Studies
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Calculating the Sum of a Vector
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Thread-Safe Initialisation of a Singleton
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Ongoing Optimisation with CppMem
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Conclusion
9
The Future: C++23
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The Future: C++23
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Executors
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Extended Futures
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Transactional Memory
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Task Blocks
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Data-Parallel Vector Library
10
Patterns and Best Practices
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Patterns and Best Practices
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History
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Invaluable Value
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Pattern versus Best Practices
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Anti-Pattern
11
Synchronisation Patterns
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Synchronisation Patterns
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Dealing with Sharing
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Dealing with Mutation
12
Concurrent Architecture
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Concurrent Architecture
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Active Object
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Monitor Object
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Half-Sync/Half-Async
13
Best Practices
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Best Practices
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General
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Multithreading
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Memory Model
14
Lock-Based Data Structures
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Lock-Based Data Structures
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General Considerations
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Concurrent Stack
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Concurrent Queue
15
Challenges
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Challenges
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ABA Problem
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Blocking Issues
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Breaking of Program Invariants
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Data Races
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Deadlocks
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False Sharing
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Lifetime Issues of Variables
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Moving Threads
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Race Conditions
16
The Time Library
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The Time Library
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The Interplay of Time Point, Time Duration, and Clock
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Time Point
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Time Duration
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Clocks
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Sleep and Wait
17
CppMem - An Overview
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CppMem - An Overview
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The simplified Overview
18
Glossary
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Glossary
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ACID
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CAS
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Callable Unit
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Complexity
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Concurrency
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Critical Section
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Eager Evaluation
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Executor
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Function Objects
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Lambda Functions
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Lazy evaluation
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Lock-free
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Lost Wakeup
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Math Laws
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Memory Location
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Memory Model
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Modification Order
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Monad
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Non-blocking
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Parallelism
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Predicate
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Pattern
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RAII
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Release Sequence
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Sequential Consistency
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Sequence Point
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Spurious Wakeup
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Thread
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Total order
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TriviallyCopyable
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volatile
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wait-free
19
Index
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Index

Monad

Haskell as a pure functional language has only pure functions. A key feature of these pure functions is that they always return the same result when given the same arguments. Thanks to this property called referential transparency a Haskell function cannot have side effects; therefore, Haskell has a conceptional issue. The world is full of calculations that have side effects. These are calculations that can fail, that can return an unknown number of results, or that are dependent on the environment. To solve this conceptional issue, Haskell uses monads and embeds them in the pure functional language.

The classical monads encapsulate one side effect:

  • I/O monad: Calculations that deal with input and output.
  • Maybe monad: Calculations that maybe return a result.
  • Error monad: Calculations that can fail.
  • List monad: Calculations that can have an arbitrary number of results.
  • State monad: Calculations that build a state.
  • Reader monad: Calculations that read from the...
CONTINUE READING
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Tech Concepts
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Programming languages
73
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Concurrency with Modern C++
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