Python Parallel Programming Cookbook · 2nd Edition by Zaccone, Giancarlo -- Read -- Imperial Library of Trantor

Index

Title Page Copyright and Credits

Python Parallel Programming Cookbook Second Edition

Dedication About Packt

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Contributors

About the author About the reviewer Packt is searching for authors like you

Preface

Who this book is for What this book covers To get the most out of this book

Download the example code files Download the color images Conventions used

Sections

Getting ready How to do it… How it works… There's more… See also

Get in touch

Reviews

Getting Started with Parallel Computing and Python

Why do we need parallel computing? Flynn's taxonomy

Single Instruction Single Data (SISD) Multiple Instruction Single Data (MISD) Single Instruction Multiple Data (SIMD) Multiple Instruction Multiple Data (MIMD)

Memory organization

Shared memory Distributed memory Massively Parallel Processing (MPP) Clusters of workstations Heterogeneous architectures

Parallel programming models

Shared memory model Multithread model Message passing model Data-parallel model

Designing a parallel program

Task decomposition Task assignment Agglomeration Mapping Dynamic mapping

Evaluating the performance of a parallel program

Speedup Efficiency Scaling Amdahl's law Gustafson's law

Introducing Python

Help functions Syntax Comments Assignments Data types Strings Flow control Functions Classes Exceptions Importing libraries Managing files List comprehensions Running Python scripts Installing Python packages using pip

Installing pip Updating pip Using pip

Introducing Python parallel programming

Processes and threads

Thread-Based Parallelism

What is a thread? Python threading module Defining a thread

Getting ready How to do it... How it works... There's more...

Determining the current thread

Getting ready How to do it... How it works...

Defining a thread subclass

Getting ready How to do it... How it works... There's more...

Thread synchronization with a lock

Getting ready How to do it... How it works... There's more...

Thread synchronization with RLock

Getting ready How to do it... How it works... There's more...

Thread synchronization with semaphores

Getting ready How to do it... How it works... There's more...

Thread synchronization with a condition

Getting ready How to do it... How it works... There's more...

Thread synchronization with an event

Getting ready How to do it... How it works...

Thread synchronization with a barrier

Getting ready How to do it... How it works...

Thread communication using a queue

Getting ready How to do it... How it works... There's more...

Process-Based Parallelism

Understanding Python's multiprocessing module Spawning a process

Getting ready How to do it... How it works... There's more... See also

Naming a process

Getting ready How to do it... How it works... There's more... See also

Running processes in the background

Getting ready How to do it... How it works... See also

Killing a process

Getting ready How to do it... How it works... See also

Defining processes in a subclass

Getting ready How to do it... How it works... There's more... See also

Using a queue to exchange data

Getting ready How to do it... How it works... There's more... See also

Using pipes to exchange objects

Getting ready How to do it... How it works... There's more... See also

Synchronizing processes

Getting ready How to do it... How it works... There's more... See also

Using a process pool

Getting ready How to do it… How it works… There's more... See also

Message Passing

Technical requirements Understanding the MPI structure Using the mpi4py Python module

How to do it... How it works... There's more... See also

Implementing point-to-point communication

How to do it... How it works... There's more... See also

Avoiding deadlock problems

How to do it... How it works... There's more... See also

Collective communication using a broadcast

Getting ready How to do it... How it works... There's more... See also

Collective communication using the scatter function

How to do it... How it works... There's more... See also

Collective communication using the gather function

Getting ready How to do it... How it works... There's more... See also

Collective communication using Alltoall

How to do it... How it works... There's more... See also

The reduction operation

Getting ready How to do it... How it works... There's more... See also

Optimizing communication

How to do it... How it works... There's more... See also

Asynchronous Programming

Using the concurrent.futures Python module

Getting ready How to do it... How it works... There's more... See also

Managing the event loop with asyncio

Understanding event loops How to do it... How it works... There's more... See also

Handling coroutines with asyncio

Getting ready How to do it... How it works... There's more... See also

Manipulating tasks with asyncio

How to do it... How it works... There's more... See also

Dealing with asyncio and futures

Getting ready How to do it... How it works... There's more... See also

Distributed Python

Introducing distributed computing Types of distributed applications

Client-server applications

Client-server architecture Client-server communications TCP/IP client-server architecture

Multi-level applications

Using the Python socket module

Getting ready How to do it... How it works... There's more...

Types of sockets

Stream sockets

See also

Distributed task management with Celery

Getting ready

Windows setup

How to do it... How it works... There's more... See also

RMI with Pyro4

Getting ready How to do it... How it works... There's more...

Implementing chain topology

See also

Cloud Computing

What is cloud computing? Understanding the cloud computing architecture

Service models

SaaS PaaS IaaS

Distribution models

Public cloud Private cloud Cloud community Hybrid cloud

Cloud computing platforms

Developing web applications with PythonAnywhere

Getting ready How to do it... How it works... There's more... See also

Dockerizing a Python application

Getting ready

Installing Docker for Windows

How to do it... How it works... There's more... See also

Introducing serverless computing

Getting ready How to do it... How it works... There's more...

What is a Lambda function? Why serverless? Possible problems and limitations

See also

Heterogeneous Computing

Understanding heterogeneous computing Understanding the GPU architecture Understanding GPU programming

CUDA OpenCL

Dealing with PyCUDA

Getting ready How to do it... How it works... There's more... See also

Heterogeneous programming with PyCUDA

How to do it... How it works... There's more... See also

Implementing memory management with PyCUDA

Getting ready How to do it... How it works... There's more... See also

Introducing PyOpenCL

Getting ready How to do it... How it works... There's more... See also

Building applications with PyOpenCL

How to do it... How it works... There's more... See also

Element-wise expressions with PyOpenCL

Getting started How to do it... How it works... There's more... See also

Evaluating PyOpenCL applications

Getting started How to do it... How it works... There's more...

Pros of OpenCL and PyOpenCL Cons of OpenCL and PyOpenCL Pros of CUDA and PyCUDA Cons of CUDA and PyCUDA

See also

GPU programming with Numba

Getting ready How to do it... How it works... There's more... See also

Python Debugging and Testing

What is debugging? What is software testing? Debugging using Winpdb Reborn

Getting ready How to do it... How it works... There's more... See also

Interacting with pdb

Getting ready

Interacting with the command line Using the Python interpreter Inserting a directive in the code to debug

How to do it... How it works... There's more... See also

Implementing rpdb for debugging

Getting ready How to do it... How it works... There's more... See also

Dealing with unittest

Getting ready How to do it... How it works... There's more... See also

Application testing using nose

Getting ready How to do it... How it works... There's more... See also

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