March 2026
Intermediate
534 pages
12h 51m
English
Content preview from GPU-Accelerated Computing with Python 3 and CUDABecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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15
Expanding and Deepening Your GPU Programming Knowledge
The aim of this book has been to build a solid foundation of GPU computing with Python. The book started by covering low-level CUDA primitives, such as kernels and streams, built up to high-level libraries, and finished with several case studies. This chapter will look at some advanced topics that may become relevant later in your GPU programming journey.
Technical requirements
To run the code in this chapter, an NVIDIA GPU with compute capability 7.5 or more is required. The CUDA Toolkit, Python 3, and a number of Python packages must also be installed. As explained in Chapter 2, it is recommended to create a pixi environment based on the pixi.lock file in the GitHub repository associated ...
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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.