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Describe the language features for parallelism ?

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By Team EasyExamNotes

Programming languages have evolved to include features that support parallelism, which is the ability to execute multiple tasks simultaneously.

Some of the key language features for parallelism are:

  1. Threads
  2. Synchronization
  3. Parallel constructs
  4. Parallel data structures
  5. Futures and Promises
  6. Task-based parallelism

1. Threads

Threads are lightweight processes that can execute independently of each other. Programming languages such as Java, C++, and Python provide support for creating and managing threads. This feature allows the developer to write code that can execute multiple tasks simultaneously.

2. Synchronization:

Synchronization is the process of coordinating the execution of threads to avoid data races and ensure data consistency. Programming languages provide various mechanisms for synchronization, such as locks, semaphores, and barriers.

3. Parallel constructs

Some programming languages provide constructs that allow the developer to specify parallelism directly in the code. For example, OpenMP and MPI provide constructs for parallel loops, parallel regions, and message passing, which can be used to write parallel code.

4. Parallel data structures

Parallel data structures are data structures that are optimized for parallel access. Examples include parallel arrays, hash tables, and trees. Programming languages such as Cilk and UPC provide support for parallel data structures.

5. Futures and Promises

Futures and Promises are constructs that allow the developer to specify asynchronous execution of tasks. Futures represent the result of a computation that may not have completed yet, while Promises represent a commitment to produce a result in the future. Programming languages such as Scala and Haskell provide support for Futures and Promises.

6. Task-based parallelism

Task-based parallelism is a programming model where the developer specifies tasks that can be executed in parallel. The system schedules the tasks dynamically based on the available resources. Programming languages such as TBB and Cilk Plus provide support for task-based parallelism.

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