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Jupyter notebook plugin to run CUDA C/C++ code

Project description

NVCC Plugin for Jupyter notebook

V2 is available

V2 brings support of multiple source and header files.

Usage
  • Install and load extension
!pip install git+https://github.com/andreinechaev/nvcc4jupyter.git
%load_ext nvcc_plugin
  • Mark a cell to be treated as cuda cell

%%cuda --name example.cu --compile false

NOTE: The cell must contain either code or comments to be run successfully. It accepts 2 arguments. -n | --name - which is the name of either CUDA source or Header The name parameter must have extension .cu or .h Second argument -c | --compile; default value is false. The argument is a flag to specify if the cell will be compiled and run right away or not. It might be usefull if you're playing in the main function

  • To compile and run all CUDA files you need to run
%%cuda_run
# This line just to bypass an exeption and can contain any text
  • To profile your CUDA kernels using NVIDIA Nsight Compute CLI profiler you need to run
%%cu --profile
  • You can add options to the profiler. Keep in mind that any argument after "--profiler-args" will be considered as a profiler argument. For example, to select which sections to collect metrics for you need to run
%%cu --profile --profiler-args --section SpeedOfLight --section MemoryWorkloadAnalysis --section Occupancy

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