Did you know that most of the computers on which you deploy
applications have more power in the GPU on the video card than
in the CPU, even multi-core machines? Harnessing the power of
the GPU is the next step in the manycore/multicore revolution
and can mean astonishing improvements in execution time.
Depending on how data parallel your calculations are, you might
see a speedup of 5, 10, or even 50 times! Imagine a calculation
that takes 24 hours today completing in half an hour instead.
What new capabilities would that enable for your users? Until
recently, running code on the GPU has meant using one of several
"C-like" languages. The upcoming release of C++ Accelerated
Massive Parallelism (AMP) means that you can use accelerators
like the GPU from native C++. Visual Studio includes debugging
and profiling support for C++ AMP, and you don't need to
download or install any new libraries to accelerate your code.
In this session, see the power of C++ AMP and learn the basic
concepts you need to adapt your code