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Add documentation for using Nsight Systems instead of the default Nsight Compute profiling tool

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Cosmin Ștefan Ciocan
2024-02-02 23:08:02 +00:00
parent bac447ef67
commit 0908891a47
2 changed files with 38 additions and 7 deletions
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docs/source/usage.rst
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@@ -225,10 +225,11 @@ Profiling
---------
Another important feature of nvcc4jupyter is its integration with the NVIDIA
Nsight Compute profiler, which you need to make sure is installed and its
executable can be found in a directory in your PATH environment variable.
Nsight Compute / NVIDIA Nsight Systems profilers, which you need to make sure
are installed and the executables can be found in a directory in your PATH
environment variable.
In order to use it and provide the profiler with custom arguments, simply run:
To profile using Nsight Compute with custom arguments:
.. code-block:: c++
@@ -256,6 +257,27 @@ Running the cell above will compile and execute the vector addition code in the
Compute (SM) Throughput % 1.19
----------------------- ------------- ------------
To profile using Nsight Systems with custom arguments:
.. code-block:: c++
%cuda_group_run --group "vector_add" --profiler nsys --profile --profiler-args "profile --stats=true"
Running the cell above will compile and execute the vector addition code in the
"vector_add" group and profile it with Nsight Systems. The output will contain
multiple tables, one of which will look similar to this:
.. code-block::
[5/8] Executing 'cuda_api_sum' stats report
Time (%) Total Time (ns) Num Calls Avg (ns) Med (ns) Min (ns) Max (ns) StdDev (ns) Name
-------- --------------- --------- ------------- ------------- ----------- ----------- ----------- ----------------------
77.3 200,844,276 1 200,844,276.0 200,844,276.0 200,844,276 200,844,276 0.0 cudaMalloc
22.6 58,594,762 2 29,297,381.0 29,297,381.0 29,153,999 29,440,763 202,772.8 cudaMemcpy
0.1 305,450 1 305,450.0 305,450.0 305,450 305,450 0.0 cudaLaunchKernel
0.0 1,970 1 1,970.0 1,970.0 1,970 1,970 0.0 cuModuleGetLoadingMode
Compiler arguments
------------------