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I. Introduction into GPU programming.
1. What are GPU and CUDA?
2. Selecting GPU.
3. Setting up development environment.
4. Combined use of Cuda, C++ and boost::python.
5. Debugging of boost::python binary using Visual Studio.
6. Debugging of boost::python/Cuda binary using Visual Studio.
7. Using printf in device code.
II. Exception safe dynamic memory handling in Cuda project.
III. Calculation of partial sums in parallel.
IV. Manipulation of piecewise polynomial functions in parallel.
V. Manipulation of localized piecewise polynomial functions in parallel.
Downloads. Index. Contents.

Debugging of boost::python/Cuda binary using Visual Studio.


vidia Nsight Visual Edition User Guide has a topic "Attach Debugging to a Running Cuda process". It does not work for me. After I select Nvidia debugger in "Debug/Attach to process" menu, my Cuda process is sometimes grayed out.

Therefore, I develop and debug Cuda code in exe-project and then convert it into a boost::python extension.

To debug Cuda code in exe-project, install a breakpoint in Cuda code and go to the menu "Nsight/Start Cuda debugging". Do not start a regular debugger and then try to step into a kernel call.





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