Distributed Computing with Python

Francesco Pierfederici

  • 出版商: Packt Publishing
  • 出版日期: 2016-04-11
  • 售價: $1,610
  • 貴賓價: 9.5$1,530
  • 語言: 英文
  • 頁數: 170
  • 裝訂: Paperback
  • ISBN: 1785889699
  • ISBN-13: 9781785889691
  • 相關分類: Python程式語言
  • 海外代購書籍(需單獨結帳)

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商品描述

Key Features

  • You'll learn to write data processing programs in Python that are highly available, reliable, and fault tolerant
  • Make use of Amazon Web Services along with Python to establish a powerful remote computation system
  • Train Python to handle data-intensive and resource hungry applications

Book Description

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.

What You Will Learn

  • Get an introduction to parallel and distributed computing
  • See synchronous and asynchronous programming
  • Explore parallelism in Python
  • Distributed application with Celery
  • Python in the Cloud
  • Python on an HPC cluster
  • Test and debug distributed applications

About the Author

Francesco Pierfederici is a software engineer who loves Python. He has been working in the fields of astronomy, biology, and numerical weather forecasting for the last 20 years.

He has built large distributed systems that make use of tens of thousands of cores at a time and run on some of the fastest supercomputers in the world. He has also written a lot of applications of dubious usefulness but that are great fun. Mostly, he just likes to build things.

Table of Contents

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

商品描述(中文翻譯)

主要特點



  • 您將學習使用Python編寫高可用性、可靠性和容錯性的數據處理程序

  • 利用Amazon Web Services和Python建立強大的遠程計算系統

  • 訓練Python處理資料密集和資源需求高的應用程式

書籍描述


考慮到當今使用的各種大數據應用程式的複雜性,CPU密集型數據處理任務變得至關重要。減少每個進程的CPU利用率對於提高應用程式的整體速度非常重要。


本書將教您如何通過在單台機器上將計算分佈到多個處理器上來執行並行計算,從而提高大數據處理任務的整體性能。我們將涵蓋同步和異步模型、共享內存和文件系統、不同進程之間的通信、同步等內容。

您將學到什麼



  • 介紹並行和分佈式計算

  • 了解同步和異步編程

  • 探索Python中的並行性

  • 使用Celery進行分佈式應用程式

  • 在雲端中使用Python

  • 在HPC集群中使用Python

  • 測試和調試分佈式應用程式

關於作者


Francesco Pierfederici是一位熱愛Python的軟體工程師。他在天文學、生物學和數值天氣預報領域工作了20年。


他建立了使用數萬個核心並在世界上最快的超級計算機上運行的大型分佈式系統。他還寫了很多有點毫無用處但非常有趣的應用程式。大多數時候,他只是喜歡建造東西。

目錄



  1. 並行和分佈式計算簡介

  2. 異步編程

  3. Python中的並行性

  4. 分佈式應用程式 - 使用Celery

  5. 在雲端中使用Python

  6. 在HPC集群中使用Python

  7. 測試和調試分佈式應用程式

  8. 前進之路