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独立建站什么意思,网络推广自学,大胡子wordpress主题,该怎么给做网站的提页面需求Python并行编程参考手册(影印版) [Python Parallel Programming Cookbook] pdf epub mobi txt 下载 图书介绍☆☆☆☆☆ [意] 吉安卡洛扎克尼(Giancarlo Zaccone) 著 下载链接在页面底部 发表于2020-11-25 类似图书 点击查看全场最…

Python并行编程参考手册(影印版) [Python Parallel Programming Cookbook] pdf epub mobi txt 下载

图书介绍

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☆☆☆☆☆

[意] 吉安卡洛·扎克尼(Giancarlo Zaccone) 著

下载链接在页面底部

发表于2020-11-25

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出版社: 东南大学出版社

ISBN:9787564170738

版次:1

商品编码:12183364

包装:平装

外文名称:Python Parallel Programming Cookbook

开本:16开

出版时间:2017-04-01

用纸:胶版纸

页数:261

正文语种:英文

Python并行编程参考手册(影印版) [Python Parallel Programming Cookbook] epub 下载 mobi 下载 pdf 下载 txt 下载

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Python并行编程参考手册(影印版) [Python Parallel Programming Cookbook] pdf epub mobi txt 下载

具体描述

内容简介   对于开发人员而言,如今要想充分利用所有可用的计算资源来构建出高效的软件系统,并行编程技术是必不可少的技能。从多核到GPU系统,再到分布式架构,计算量繁重的程序都离不开编程工具和软件库。

《Python并行编程参考手册(影印版)》首先简要介绍了并行编程,然后讲述了Python的基础知识,接着探究了基于线程的并行模型、采用同步线程的Python线程模块以及锁、互斥量、信号量队列、GIL和线程池的用法。

作者简介   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.

目录 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

Python并行编程参考手册(影印版) [Python Parallel Programming Cookbook] 下载 mobi epub pdf txt

Python并行编程参考手册(影印版) [Python Parallel Programming Cookbook] pdf epub mobi txt 下载

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