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Distributed Computing with Python

Distributed Computing with Python

By : Pierfederici
4.3 (3)
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Distributed Computing with Python

Distributed Computing with Python

4.3 (3)
By: Pierfederici

Overview of this book

CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications. This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more.
Table of Contents (10 chapters)
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9
Index

What you need for this book

The following software and hardware is recommended:

  • Python 3.5 or later
  • A laptop or desktop computer running Linux or Mac OS X
  • Ideally, some extra computers or some extra virtual machines to test your distributed applications

All software mentioned in this book is free of charge and can be downloaded from the Internet with the exception of PBS Pro, which is commercial. Most of the PBS Pro functionality, however, is available in its close sibling Torque, which is open source.

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