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Feature: Passing arguments to NVCC compiler (#26)

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* Add option to give nvcc extra arguments

* Add test for nvcc options that changes c++ dialect from c++17 to c++14

* Add make and the english language pack to devcontainer to be able to build the documentation

* Update documentation config to automatically import the current version of the package

* Document new --compiler-args argument

* Improve tests coverage by testing for bad arguments and the error output during a failed compilation

* Add IPython to docs requirements to allow the __version__ import for readthedocs env

* Change devcontainer base image to have the latest CUDA toolkit

* Mock the nsight compute tool with a bash script

* Add test to compile with opencv

* Add new page to documentation that contains a new notebook that explains compiling with external libraries

* Add autodocstring vscode extension to devcontainer

* Add function that modifies the default profiler/compiler arguments to allow reusing them in multiple magic command calls

* Update pylint exceptions

* Update contributing instructions

* Change version from 1.0.3 to 1.1.0 due to adding features in a backward-compatible manner

* Install latest CUDA toolkit on the test runner to pass the OpenCV compilation test

* Install opencv in test runner and update code coverage install

* Add CUDA bin to PATH in test and coverage runners

* Add cuda bin to path variable in .bashrc

* Update way to set environment variable PATH in github action

* Change devcontainer base image back to ubuntu:22.04 to match the environment from the test runner
This commit is contained in:
Cosmin Ștefan Ciocan
2024-02-12 17:29:26 +01:00
committed by GitHub
parent 5cd225851b
commit 781ff5b76b
19 changed files with 424 additions and 51 deletions
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docs/source/notebooks.rst
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*********
Notebooks
*********
This page provides a list of useful Jupyter notebooks written with the
**nvcc4jupyter** library.
.. note::
These notebooks are written for Google's Colab, but you may run them in
other environments by installing all expected dependencies. If running in
Colab, make sure to set the runtime type to a GPU instance (at the time of
writing this, T4 is the GPU offered for free by Colab).
------
.. _compiling_with_external_libraries:
Compiling with external libraries
=================================
[`NOTEBOOK <https://colab.research.google.com/drive/1iuY46DCwv4hy3SqDhJgFeO8kgpHnzjTh?usp=sharing>`_]
If you need to compile CUDA C++ code that uses external libraries in the host
code (e.g. OpenCV for reading and writing images to disk) then this section is
for you.
To achieve this, use the :ref:`compiler-args <compiler_args>` option of the
:ref:`cuda <cuda_magic>` magic command to pass the correct compiler options
of the OpenCV library to **nvcc** for it to link the OpenCV code with the
code in your Jupyter cell. Those compiler options can be provided by the
`pkg-config <https://www.freedesktop.org/wiki/Software/pkg-config/>`_ tool.
In the notebook we show how to use OpenCV to load an image, blur it with a CUDA
kernel, and then save it back to disk using OpenCV again.