Python並行編程參考手冊(影印版) [Python Parallel Programming Cookbook]

Python並行編程參考手冊(影印版) [Python Parallel Programming Cookbook] 下載 mobi epub pdf 電子書 2025

[意] 吉安卡洛·紮剋尼(Giancarlo Zaccone) 著
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齣版社: 東南大學齣版社
ISBN:9787564170738
版次:1
商品編碼:12183364
包裝:平裝
外文名稱:Python Parallel Programming Cookbook
開本:16開
齣版時間:2017-04-01
用紙:膠版紙
頁數:261
正文語種:英文

具體描述

內容簡介

  對於開發人員而言,如今要想充分利用所有可用的計算資源來構建齣高效的軟件係統,並行編程技術是必不可少的技能。從多核到GPU係統,再到分布式架構,計算量繁重的程序都離不開編程工具和軟件庫。
  《Python並行編程參考手冊(影印版)》首先簡要介紹瞭並行編程,然後講述瞭Python的基礎知識,接著探究瞭基於綫程的並行模型、采用同步綫程的Python綫程模塊以及鎖、互斥量、信號量隊列、GIL和綫程池的用法。

作者簡介

  Giancarlo Zaccone has more than 10 years of experience in managing research projects,both in scientific and industrial domains. He worked as a researcher at the National Research Council (CNR), where he was involved in a few parallel numerical computing and scientific visualization projects.
  He currently works as a software engineer at a consulting company, developing and maintaining software systems for space and defense applications.
  Giancarlo holds a master's degree in physics from the University of Naples Federico Ⅱ and has completed a second-level postgraduate master's program in scientific computing from the Sapienza University of Rome.

目錄

Preface
Chapter 1: Getting Started with Parallel Computing and Python
Introduction
The parallel computing memory architecture
Memory organization
Parallel programming models
How to design a parallel program
How to evaluate the performance of a parallel program
Introducing Python
Python in a parallel world
Introducing processes and threads
Start working with processes in Python
Start working with threads in Python

Chapter 2: Thread-based Parallelism
Introduction
Using the Python threading module
How to define a thread
How to determine the current thread
How to use a thread in a subclass
Thread synchronization with Lock and RLock
Thread synchronization with RLock
Thread synchronization with semaphores
Thread synchronization with a condition
Thread synchronization with an event
Using the with statement
Thread communication using a queue
Evaluating the performance of multithread applications

Chapter 3: Process-based Parallelism
Introduction
How to spawn a process
How to name a process
How to run a process in the background
How to kill a process
How to use a process in a subclass
How to exchange objects between processes
How to synchronize processes
How to manage a state between processes
How to use a process pool
Using the mpi4py Python module
Point-to-point communication
Avoiding deadlock problems
Collective communication using broadcast
Collective communication using scatter
Collective communication using gather
Collective communication using AIItoall
The reduction operation
How to optimize communication

Chapter 4: Asynchronous Programming
Introduction
Using the concurrent.futures Python modules
Event loop management with Asyncio
Handling coroutines with Asyncio
Task manipulation with Asyncio
Dealing with Asyncio and Futures

Chapter 5: Distributed Python
Introduction
Using Celery to distribute tasks
How to create a task with Celery
Scientific computing with SCOOP
Handling map functions with SCOOP
Remote Method Invocation with Pyro4
Chaining objects with Pyro4
Developing a client-server application with Pyro4
Communicating sequential processes with PyCSP
Using MapReduce with Disco
A remote procedure call with RPyC

Chapter 6: GPU Programming with Python
Introduction
Using the PyCUDA module
How to build a PyCUDA application
Understanding the PyCUDA memory model with matrix manipulation
Kernel invocations with GPUArray
Evaluating element-wise expressions with PyCUDA
The MapReduce operation with PyCUDA
GPU programming with NumbaPro
Using GPU-accelerated libraries with NumbaPro
Using the PyOpenCL module
How to build a PyOpenCL application
Evaluating element-wise expressions with PyOpenCI
Testing your GPU application with PyOpenCL
Index

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