Download e-book for kindle: Distributed Computing with Python by Francesco Pierfederici

By Francesco Pierfederici

Key Features

  • You'll learn how to write info processing courses in Python which are hugely on hand, trustworthy, and fault tolerant
  • Make use of Amazon internet companies besides Python to set up a robust distant computation system
  • Train Python to address data-intensive and source hungry applications

Book Description

CPU-intensive info processing projects became the most important contemplating the complexity of a few of the great info functions which are used this present day. lowering the CPU usage in step with procedure is essential to enhance the final pace of applications.

This publication will train 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 information processing job. we are going to hide synchronous and asynchronous versions, shared reminiscence and dossier structures, verbal exchange among quite a few techniques, synchronization, and more.

What you are going to Learn

  • Get an advent to parallel and disbursed 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 allotted platforms that utilize tens of hundreds of thousands of cores at a time and run on a number of the quickest supercomputers on the earth. He has additionally written loads of purposes of doubtful usefulness yet which are nice enjoyable. more often than not, 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 disbursed Applications
  8. The highway Ahead

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