December 2013
Intermediate to advanced
116 pages
2h 15m
English
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GPU, a vectorial and parallel architecture
GPUs provide an incredible processing power in certain situations. If you ever tried to program a software rasterizer for your CPU, you would have noticed that the performance was terrible. Even the most advanced software rasterizer, taking advantage of vectorial instruction sets such as SSE3, or making intensive use of all available cores through multithreading, offers very poor performance compared with a GPU. CPUs are simply not meant for pixels.
So, why are GPUs so fast at processing fragments, pixels, and vertices compared to a CPU? The answer is that by the scalar nature of a CPU, it always process one instruction after another. On the other side, GPUs process hundreds of instructions simultaneously. ...
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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.