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Parallel Programming with Python

You're reading from   Parallel Programming with Python Develop efficient parallel systems using the robust Python environment.

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783288397
Length 124 pages
Edition 1st Edition
Languages
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Author (1):
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 Palach Palach
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Palach
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Table of Contents (10) Chapters Close

Preface 1. Contextualizing Parallel, Concurrent, and Distributed Programming FREE CHAPTER 2. Designing Parallel Algorithms 3. Identifying a Parallelizable Problem 4. Using the threading and concurrent.futures Modules 5. Using Multiprocessing and ProcessPoolExecutor 6. Utilizing Parallel Python 7. Distributing Tasks with Celery 8. Doing Things Asynchronously Index

Defining threads

Threads are different execution lines in a process. Let us picture a program as if it was a hive, and there is a process of collecting pollen inside this hive. This collection process is carried out by several worker bees who work simultaneously in order to solve the problem of lack of pollen. The worker bees play the role of threads, acting inside a process and sharing resources to perform their tasks.

Threads belong to the same process and share the same memory space. Hence, the developer's task is to control and access these areas of memory.

Advantages and disadvantages of using threads

Some advantages and disadvantages have to be taken into account when deciding on the use of threads, and it depends on the language and operating system used to implement a solution.

The advantages of using threads are as follows:

  • The speed of communication of the threads in the same process, data location, and shared information is fast
  • The creation of threads is less costly than the...
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