September 2016
Intermediate to advanced
408 pages
9h 18m
English
Content preview from Haskell High Performance ProgrammingBecome 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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Chapter 11. Programming for the GPU with Accelerate
In recent years, Graphics Processing Units (GPUs) have become prominent hardware in areas other than just plain graphics applications. This practice is known as General-Purpose Computing On Graphics Processing Units (GPGPU). Due to their ability to perform highly parallel computations much more efficiently compared to a CPU, the GPU is often utilized, for instance, in machine-learning applications. The GPU is specialized to perform certain kinds of vectorized computations extremely efficiently. It's not nearly as flexible as a CPU is. Single cores in a GPU are far less powerful than CPU cores, but there are hundreds of smaller cores in a GPU.
Due to their parallel nature, GPUs use wildly different ...
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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.