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C++ AMP in a nutshell

  • Artykuł

With Visual Studio 2012, you are able to get your hands on a new technology that enables you to tap into the power of heterogeneous hardware and specifically take advantage of accelerators such as the GPU for compute purposes: C++ AMP.

So you'll create an empty C++ project, add a new code file, stick a #include <amp.h> at the top, then add a using namespace concurrency; and then what? I suggest you try typing in our example C++ AMP matrix multiplication code, and trying it out on your DirectX 11 hardware, or download one of our many C++ AMP samples. including the simplistic "Hello World" code.

Then, you can play around with all the new constructs we've added, following the description of each from the following posts:

Beyond the core API above, there is even more for you to explore

If the above is not enough reading, you can read the 130 pages of the C++ AMP open specification.

Beyond the API and language, there is fantastic Visual Studio integration (intellisense, code navigation, project and build system, etc) and in particular I encourage you to explore the support for

You'll no doubt have questions and feedback, and we truly look forward to taking those in our dedicated Native Parallelism forum. Enjoy!

Comments

  • Anonymous
    March 24, 2013
    Hi Daniel, Thanks for sharing these. I am currently changing a CUDA style code to C++ AMP style. I have wonders on how to replace several CUDA keywords. Can you give advice on what C++ AMP can replce the following CUDA codes?

    1. align(16)
    2. Cuda::HostMemoryReference1D<int>
    3. DeviceMemoryLinear2D<int>
    4. DeviceMemoryPitched3D<int>
    5. cuda_safe_call() related 5.1 cuda_safe_call( cudaGetLastError() ); 5.2 cuda_safe_call( cudaUnbindTexture(...) ); 5.3 cuda_safe_call( cudaDeviceSynchronize() );
    6. cudaBindTexture() Thanks in advance!

  • Anonymous
    March 25, 2013
    Looking forward to the answers to the previous questions.

  • Anonymous
    March 26, 2013

  1. align(16) >> The equivalent of this capability in the MS VC++  compiler is __declspec(align(#)) which allows you to control the alignment of user-defined data.
  2. Cuda::HostMemoryReference1D<int> >> The C++ AMP concurrency::array_view type enables multidimensional views over existing CPU memory.
  3. DeviceMemoryLinear2D<int> >> The C++ AMP concurrency::array and concurrency::array_view types are equivalent abstractions of multidimensional data containers.
  4. DeviceMemoryPitched3D<int> >> There is not direct equivalent of this in C++ AMP. However, if you want to use multidimensional data with specific pitch, you can achieve the same through using the "section" capability of array and array_view types in C++ AMP. Note that when doing this, you would be responsible for defining the pitch unlike the CUDA pitched allocations where the CUDA runtime determines the pitch.
  5. cuda_safe_call() related 5.1 cuda_safe_call( cudaGetLastError() ); >> AFAIK cuda_safe_call is just a macro for better error diagnostics for CUDA API calls in debug mode. C++ AMP uses exceptions for runtime errors and when compiling C++ AMP programs in debug mode, you would automatically get detailed debug diagnostics to help you better understand the error. 5.2 cuda_safe_call( cudaUnbindTexture(...) );
  6. cudaBindTexture() >> Please refer to our blog post on textures  to learn about texture capabilities in C++ AMP. 5.3 cuda_safe_call( cudaDeviceSynchronize() ); >> accelerator_view::wait is the equivalent C++ AMP API. Please feel free to ask any further questions on our MSDN forum.
  • Anonymous
    March 26, 2013
    Hi Amit, many thanks for your detailed answer. :)