Distributed Computing with Python by Francesco Pierfederici

By Francesco Pierfederici

Key Features

  • You'll discover ways to write facts processing courses in Python which are hugely to be had, trustworthy, and fault tolerant
  • Make use of Amazon internet companies in addition to Python to set up a robust distant computation system
  • Train Python to address data-intensive and source hungry applications

Book Description

CPU-intensive facts processing initiatives became an important contemplating the complexity of some of the vast facts purposes which are used this day. decreasing the CPU usage consistent with method is essential to enhance the general pace of applications.

This e-book will educate you ways to accomplish parallel execution of computations by means of allotting them throughout a number of processors in one laptop, hence bettering the final functionality of a giant info processing job. we'll conceal synchronous and asynchronous types, shared reminiscence and dossier structures, verbal exchange among a number of approaches, synchronization, and more.

What you are going to Learn

  • Get an creation to parallel and dispensed computing
  • See synchronous and asynchronous programming
  • Explore parallelism in Python
  • Distributed software with Celery
  • Python within the Cloud
  • Python on an HPC cluster
  • Test and debug disbursed applications

About the Author

Francesco Pierfederici is a software program engineer who loves Python. He has been operating within the fields of astronomy, biology, and numerical climate forecasting for the final 20 years.

He has equipped huge dispensed platforms that utilize tens of millions of cores at a time and run on the various quickest supercomputers on the planet. He has additionally written loads of functions of doubtful usefulness yet which are nice enjoyable. in general, he simply loves to construct things.

Table of Contents

  1. An advent to Parallel and allotted Computing
  2. Asynchronous Programming
  3. Parallelism in Python
  4. Distributed purposes – with Celery
  5. Python within the Cloud
  6. Python on an HPC Cluster
  7. Testing and Debugging allotted Applications
  8. The highway Ahead

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