May 2019
Intermediate to advanced
452 pages
12h 16m
English
Content preview from Hands-On GPU Computing with Python
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Summary
In this chapter, we learned about IDEs and their significance. We learned about different IDEs and also went through PyCharm, PyDev for Eclipse, and Jupyter Lab. We also mentioned another IDE named Eric, along with highlighting some of its many features. We discussed PyCharm in detail and learned the differences between the various editions of PyCharm and also how to apply for a free license as an academician or a dedicated open source developer. Installation steps for PyCharm, PyDev, and Jupyter Lab were covered in detail.
Once we were done setting up our IDE, we were able to dive deeper into the GPU-enabled Python programming perspective, hands-on. We customized and explored various programs through CUDA, PyCUDA-C, OpenCL, PyOpenCL, ...
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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.