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Introduction to
Parallel Programming
using Python
Presented by: Samah Gad
July 11, 2013
Friday, July 12, 13
Road Map
Motivation
Forking Processes
Threads
Interprocess Communication - Overview
The multiprocessing Module - Overview
Friday, July 12, 13
Motivation
Problem:
Most computers spend a lot of time
doing nothing.
Majority of the modern CPU’s capacity
is often spent in an idle state.
Friday, July 12, 13
Motivation -Cont.
Solution:
Running more than one program at a
time.
Dividing the CPU attention among a
set of tasks.
Parallel Processing, Multiprocessing,
or Multitasking.
Friday, July 12, 13
Parallel Processing in
Python
Two main ways to run tasks:
Process forks
Spawned threads
Python built-in tools like: os.fork, threading,
queue, and multiprocessing.
Third Party domains offers more advanced
tools.
Friday, July 12, 13
Forking Processes
Traditional ways to structure parallel
tasks.
Straight forward way to start an
independent program.
What is forking?
Copying programs.
Python Module - os.fork
Friday, July 12, 13
Example 1
Friday, July 12, 13
Example 2
Friday, July 12, 13
Threads
Another way to start activities
running at the same time.
Lightweight processes
Run within the same single process.
Friday, July 12, 13
Threads - Advantages:
Performance
Simplicity
Shared global memory
Portability
Friday, July 12, 13
Python Modules
Python Modules:
_thread module
threading modules
Both modules provide tools for
synchronizing access to shared objects
with locks.
Friday, July 12, 13
The _thread Module
Start new independent threads of
execution within a process.
Doesn't support OOP
Platform independent module.
Friday, July 12, 13
Example 3
Friday, July 12, 13
Example 4
Friday, July 12, 13
Synchronizing access to
shared objects and names
What is problem?
Objects and namespaces in a process
that span the life of threads are
shared by all spawned threads.
Solution:
Threads automatically come with a
cross-task communications
Friday, July 12, 13
Example 5
Friday, July 12, 13
Threading Module
Internally uses the _thread module to
implement objects that represent
threads and common synchronization
tools.
Manage threads with high-level class-
based objects.
Friday, July 12, 13
Example 6
Friday, July 12, 13
Interprocess
Communication - Overview
Other solutions don’t support cross-
program communication
Sockets, Pipes, and Signals
Enable performing Inter-Process
Communication (IPC)
Friday, July 12, 13
The multiprocessing
Module - Overview
Provide the best of processes and threads.
Platform independent.
Uses processes instead of threads.
Provide synchronizations tools.
Leverage the capacity of multiple
processors.
Friday, July 12, 13

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Parallel programming using python