Preface
vii
Chapter 4, Asynchronous Programming, explains the asynchronous model for concurrent
programming. In some ways, it is simpler than the threaded one because there is a single
instruction stream and tasks explicitly relinquish control instead of being suspended
arbitrarily. This chapter will show you how to use the Python asyncio module to organize each
task as a sequence of smaller steps that must be executed in an asynchronous manner.
Chapter 5, Distributed Python, introduces you to distributed computing. It is the process of
aggregating several computing units logically and may even be geographically distributed
to collaboratively run a single computational task in a transparent and coherent way. This
chapter will present some of the solutions proposed by Python for the implementation of
these architectures using the OO approach, Celery, SCOOP, and remote procedure calls, such
as Pyro4 and RPyC. It will also include different approaches, such as PyCSP, and nally, Disco,
which is the Python version of the MapReduce algorithm.
Chapter 6, GPU Programming with Python, describes the modern Graphics Processing
Units (GPUs) that provide breakthrough performance for numerical computing at the cost of
increased programming complexity. In fact, the programming models for GPUs require the
programmer to manually manage the data transfer between a CPU and GPU. This chapter will
teach you, through the programming examples and use cases, how to exploit the computing
power provided by the GPU cards, using the powerful Python modules: PyCUDA, NumbaPro,
and PyOpenlCL.
What you need for this book
All the examples of this book can be tested in a Windows 7 32-bit machine. Also, a Linux
environment will be useful.
The Python versions needed to run the examples are:
f Python 3.3 (for the rst ve chapters)
f Python 2.7 (only for Chapter 6, GPU Programming with Python)
The following modules (all of which are freely downloadable) are required:
f mpich-3.1.4
f pip 6.1.1
f mpi4py1.3.1
f asyncio 3.4.3
f Celery 3.1.18
f Numpy 1.9.2
f Flower 0.8.32 (optional)
f SCOOP 0.7.2
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