May 2018
Beginner to intermediate
364 pages
7h 43m
English
Content preview from Hands-On Data Science with Anaconda
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Distributed Computing, Parallel Computing, and HPCC
Since our society has entered a data-intensive era (that is, a big data era), we face larger and larger datasets. For this reason, companies and users are considering what kinds of tools they could use to speed up the process when dealing with data. One obvious solution is to increase their data storage capacity. Unfortunately, there is a huge cost associated with this. The other solutions include distributed computing and some ways to accelerate our process.
In this chapter, we'll cover the following topics:
- Introduction to distributed versus parallel computing
- Understanding MPI
- Parallel processing in Python
- Compute nodes
- Anaconda add-ons
- Introduction to HPCC
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.