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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 this book covers

Chapter 1, An Introduction to Parallel and Distributed Computing, takes you through the basic theoretical foundations of parallel and distributed computing.

Chapter 2, Asynchronous Programming, describes the two main programming styles used in distributed applications: synchronous and asynchronous programming.

Chapter 3, Parallelism in Python, shows you how to do more than one thing at the same time in your Python code, using nothing more than the Python standard library.

Chapter 4, Distributed Applications – with Celery, teaches you how to build simple distributed applications using Celery and some of its competitors: Python-RQ and Pyro.

Chapter 5, Python in the Cloud, shows how you can deploy your Python applications on the cloud using Amazon Web Services.

Chapter 6, Python on an HPC Cluster, shows how to deploy your Python applications on a classic HPC cluster, typical of many universities and national labs.

Chapter 7, Testing and Debugging Distributed Applications, talks about the challenges of testing, profiling, and debugging distributed applications in Python.

Chapter 8, The Road Ahead, looks at what you have learned so far and which directions interested readers could take to push their development of distributed systems further.

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