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Python Parallel Programming Cookbook

You're reading from   Python Parallel Programming Cookbook Master efficient parallel programming to build powerful applications using Python

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Product type Paperback
Published in Aug 2015
Publisher
ISBN-13 9781785289583
Length 286 pages
Edition 1st Edition
Languages
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Author (1):
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Giancarlo Zaccone Giancarlo Zaccone
Author Profile Icon Giancarlo Zaccone
Giancarlo Zaccone
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Table of Contents (8) Chapters Close

Preface 1. Getting Started with Parallel Computing and Python 2. Thread-based Parallelism FREE CHAPTER 3. Process-based Parallelism 4. Asynchronous Programming 5. Distributed Python 6. GPU Programming with Python 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 + \
       ...
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