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Mastering Matplotlib

Mastering Matplotlib

By : Duncan M. McGreggor, Duncan M McGreggor
3.5 (8)
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Mastering Matplotlib

Mastering Matplotlib

3.5 (8)
By: Duncan M. McGreggor, Duncan M McGreggor

Overview of this book

If you are a scientist, programmer, software engineer, or student who has working knowledge of matplotlib and now want to extend your usage of matplotlib to plot complex graphs and charts and handle large datasets, then this book is for you.
Table of Contents (11 chapters)
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10
Index

Clustering and parallel programming


The term clustering may have a number of operational definitions depending on the situation that one is facing or the organization that one is working with. In this chapter, we will use the term in a very general sense to indicate a system of computing nodes across which a task may be split and whose parts may be executed in parallel with all the system nodes. We won't specify what nodes are, as they may be anything from a collection of processes on the same machine or a computer network to virtual machines or physical computers on a network.

The word "cluster" alludes to a logical collection, but in our definition there is a more important word—parallel. For our purposes, clusters exist to make running code in parallel more efficient or convenient. The topic of parallel computing is a vast one and has an interesting history. However, it rose to greater prominence in 2003 due to the physical limitations that were encountered by the chip-making industry...

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