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 to use this massive parallelism.