Distributed Computing with Python
暫譯: 使用 Python 的分散式計算
Francesco Pierfederici
- 出版商: Packt Publishing
- 出版日期: 2016-04-11
- 售價: $1,660
- 貴賓價: 9.5 折 $1,577
- 語言: 英文
- 頁數: 170
- 裝訂: Paperback
- ISBN: 1785889699
- ISBN-13: 9781785889691
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相關分類:
Python、程式語言
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相關主題
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
- An Introduction to Parallel and Distributed Computing
- Asynchronous Programming
- Parallelism in Python
- Distributed Applications – with Celery
- Python in the Cloud
- Python on an HPC Cluster
- Testing and Debugging Distributed Applications
- The Road Ahead
商品描述(中文翻譯)
關鍵特點
- 您將學會編寫高可用性、可靠性和容錯的 Python 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 處理數據密集型和資源需求高的應用程序
書籍描述
考慮到當今各種大數據應用的複雜性，CPU 密集型數據處理任務變得至關重要。降低每個進程的 CPU 使用率對於提高應用程序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配到多個處理器來執行計算的並行執行，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、共享記憶體和檔案系統、各進程之間的通信、同步等內容。
您將學到的內容
- 獲得並行和分佈式計算的介紹
- 了解同步和異步編程
- 探索 Python 中的並行性
- 使用 Celery 的分佈式應用程序
- 雲端中的 Python
- 在 HPC 集群上的 Python
- 測試和調試分佈式應用程序
關於作者
**Francesco Pierfederici** 是一位熱愛 Python 的軟體工程師。他在天文學、生物學和數值氣象預報領域工作了 20 年。
他構建了大型分佈式系統，利用數萬個核心同時運行，並在世界上一些最快的超級計算機上運行。他還編寫了許多用途可疑但非常有趣的應用程序。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. 使用 Celery 的分佈式應用程序
5. 雲端中的 Python
6. 在 HPC 集群上的 Python
7. 測試和調試分佈式應用程序
8. 前進的道路
