O'Reilly logo

CUDA by Example: An Introduction to General-Purpose GPU Programming by Edward Kandrot, Jason Sanders

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Chapter 10 Streams

Time and time again in this book we have seen how the massively data-parallel execution engine on a GPU can provide stunning performance gains over comparable CPU code. However, there is yet another class of parallelism to be exploited on NVIDIA graphics processors. This parallelism is similar to the task parallelism that is found in multithreaded CPU applications. Rather than simultaneously computing the same function on lots of data elements as one does with data parallelism, task parallelism involves doing two or more completely different tasks in parallel.

In the context of parallelism, a task could be any number of things. For example, an application could be executing two tasks: redrawing its GUI with one thread while ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required