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Learning Concurrency in Python

You're reading from   Learning Concurrency in Python Build highly efficient, robust, and concurrent applications

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787285378
Length 360 pages
Edition 1st Edition
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Author (1):
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Elliot Forbes Elliot Forbes
Author Profile Icon Elliot Forbes
Elliot Forbes
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Toc

Table of Contents (13) Chapters Close

Preface 1. Speed It Up! FREE CHAPTER 2. Parallelize It 3. Life of a Thread 4. Synchronization between Threads 5. Communication between Threads 6. Debug and Benchmark 7. Executors and Pools 8. Multiprocessing 9. Event-Driven Programming 10. Reactive Programming 11. Using the GPU 12. Choosing a Solution

PyOpenCL

OpenCL, or Open Computing Language in its full form, is a low-level API for heterogeneous computing that runs on CUDA-powered GPUs. PyOpenCL represents the Python implementation of this API that enables us to write Python applications that leverage the power of a whole range of different platforms from CPUs, GPUs, DSPs and FPGAs.

The official documentation for the PyOpenCL library can be found at https://documen.tician.de/pyopencl/.

Example

Let's dissect the example that comes in the official documentation. This will act as a perfect starting point, which we can expand upon later.  

We will first import all the necessary modules at the top and alias NumPy and PyOpenCL as np and cl, respectively. We will...

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