November 2018
Intermediate to advanced
310 pages
7h 54m
English
Content preview from Hands-On GPU Programming with Python and CUDA
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Summary
In this chapter, we went over some of the options and paths for those that are interested in furthering their background in GPU programming, which is beyond the scope of this book. The first path we covered was expanding your background in pure CUDA and GPGPU programming—some of the things you can learn about that weren't covered in this book include programming systems with multiple GPUs and networked clusters. We also looked at some of the parallel programming languages/APIs besides CUDA, such as MPI and OpenCL. Next, we discussed some of the well-known APIs available to those who are interested in applying GPUs to rendering graphics, such as Vulkan and DirectX 12. We then looked at machine learning and went into some of the basic ...
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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.