Book Image

Parallel Programming with Python

By : Jan Palach, Jan Palach V Cruz da Silva
Book Image

Parallel Programming with Python

By: Jan Palach, Jan Palach V Cruz da Silva

Overview of this book

Table of Contents (16 chapters)
Parallel Programming with Python
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

Why use parallel programming?


Since computing systems have evolved, they have started to provide mechanisms that allow us to run independent pieces of a specific program in parallel with one another, thus enhancing the response and the general performance. Moreover, we can easily verify that the machines are equipped with more processors and these with plenty of more cores. So, why not take advantage of this architecture?

Parallel programming is a reality in all contexts of system development, from smart phones and tablets, to heavy duty computing in research centers. A solid basis in parallel programming will allow a developer to optimize the performance of an application. This results in enhancement of user experience as well as consumption of computing resources, thereby taking up less processing time for the accomplishment of complex tasks.

As an example of parallelism, let us picture a scenario in which an application that, amongst other tasks, selects information from a database, and this database has considerable size. Consider as well, the application being sequential, in which tasks must be run one after another in a logical sequence. When a user requests data, the rest of the system will be blocked until the data return is not concluded. However, making use of parallel programming, we will be allowed to create a new worker that which will seek information in this database without blocking other functions in the application, thus enhancing its use.