Book Image

Python Parallel Programming Cookbook

By : Zaccone
Book Image

Python Parallel Programming Cookbook

By: Zaccone

Overview of this book

This book will teach you parallel programming techniques using examples in Python and will help you explore the many ways in which you can write code that allows more than one process to happen at once. Starting with introducing you to the world of parallel computing, it moves on to cover the fundamentals in Python. This is followed by exploring the thread-based parallelism model using the Python threading module by synchronizing threads and using locks, mutex, semaphores queues, GIL, and the thread pool. Next you will be taught about process-based parallelism where you will synchronize processes using message passing along with learning about the performance of MPI Python Modules. You will then go on to learn the asynchronous parallel programming model using the Python asyncio module along with handling exceptions. Moving on, you will discover distributed computing with Python, and learn how to install a broker, use Celery Python Module, and create a worker. You will understand anche Pycsp, the Scoop framework, and disk modules in Python. Further on, you will learnGPU programming withPython using the PyCUDA module along with evaluating performance limitations.
Table of Contents (8 chapters)
7
Index

Avoiding deadlock problems


A common problem we face is that of the deadlock. This is a situation where two (or more) processes block each other and wait for the other to perform a certain action that serves to another, and vice versa. The mpi4py module doesn't provide any specific functionality to resolve this but only some measures, which the developer must follow to avoid problems of deadlock.

How to do it…

Let's first analyze the following Python code, which will introduce a typical deadlock problem; we have two processes, rank equal to one and rank equal to five, that communicate which each other and both have the data sender and data receiver functionality:

from mpi4py import MPI

comm=MPI.COMM_WORLD
rank = comm.rank
print("my rank is : " , rank)

if rank==1:
    data_send= "a"
    destination_process = 5
    source_process = 5

    data_received=comm.recv(source=source_process)
    comm.send(data_send,dest=destination_process)
    
    print ("sending data %s " %data_send + \
       ...