Human Computer Interaction

Distributed Computing with Python by Francesco Pierfederici

By Francesco Pierfederici

Key Features

  • You'll discover ways to write info processing courses in Python which are hugely on hand, trustworthy, and fault tolerant
  • Make use of Amazon internet providers besides Python to set up a strong distant computation system
  • Train Python to deal with data-intensive and source hungry applications

Book Description

CPU-intensive information processing projects became the most important contemplating the complexity of a few of the vast info functions which are used this present day. lowering the CPU usage consistent with approach is essential to enhance the final velocity of applications.

This e-book will educate you ways to accomplish parallel execution of computations via dispensing them throughout a number of processors in one laptop, hence bettering the general functionality of a large info processing job. we are going to disguise synchronous and asynchronous types, shared reminiscence and dossier platforms, communique among numerous methods, synchronization, and more.

What you are going to Learn

  • Get an advent to parallel and allotted 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 dispensed 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 outfitted huge allotted platforms that utilize tens of hundreds of thousands of cores at a time and run on a few of the quickest supercomputers on the planet. He has additionally written loads of functions of doubtful usefulness yet which are nice enjoyable. quite often, he simply loves to construct things.

Table of Contents

  1. An creation to Parallel and dispensed 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 dispensed Applications
  8. The highway Ahead

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