274 lines
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274 lines
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HTML
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<title>Configuring your PC to use your Nvidia GPU with PCL — Point Cloud Library 1.12.0 documentation</title>
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1.12.0
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<!-- Local TOC -->
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<div class="local-toc"><ul>
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<li><a class="reference internal" href="#">Configuring your PC to use your Nvidia GPU with PCL</a></li>
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<li><a class="reference internal" href="#checking-cuda-version">Checking CUDA Version</a></li>
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<li><a class="reference internal" href="#checking-c-version">Checking C++ Version</a></li>
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<li><a class="reference internal" href="#installing-gcc">Installing GCC</a></li>
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<li><a class="reference internal" href="#installing-eigen">Installing Eigen</a></li>
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<li><a class="reference internal" href="#building-pcl">Building PCL</a></li>
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<li>Configuring your PC to use your Nvidia GPU with PCL</li>
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<div class="section" id="configuring-your-pc-to-use-your-nvidia-gpu-with-pcl">
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<span id="gpu-install"></span><h1>Configuring your PC to use your Nvidia GPU with PCL</h1>
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<p>In this tutorial you will learn how to configure your system to make it compatible to run the GPU methods provided by PCL.
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This tutorial is for Ubuntu, other Linux distrubutions can follow a similar process to set it up.</p>
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<p>Windows is currently <strong>not</strong> officially supported for the GPU methods.</p>
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</div>
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<div class="section" id="checking-cuda-version">
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<h1>Checking CUDA Version</h1>
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<p>In order to run the code you will need a system with an Nvidia GPU, having CUDA Toolkit v9.2+ installed.
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We will not be covering CUDA toolkit installation in this tutorial as there already exists many great tutorials for the same.</p>
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<p>You can check your CUDA toolkit version using the following command:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ nvcc --version | grep "release" | awk '{print $6}' | cut -c2-
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</pre></div>
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</div>
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</div>
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<div class="section" id="checking-c-version">
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<h1>Checking C++ Version</h1>
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<p>The GPU methods in PCL require a min version of GCC 7 or Clang 6 onwards (min version unknown).
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This will not be a problem if you are running Ubuntu 18.04 or later. However on Ubuntu 16.04, you will need to install GCC 7 or Clang 6 (lower versions not tested) manually because the versions available by default are: GCC 5 and Clang 3.8</p>
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<p>You can check your GCC and Clang version using the following commands:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ gcc -dumpversion
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$ clang --version
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</pre></div>
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</div>
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</div>
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<div class="section" id="installing-gcc">
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<h1>Installing GCC</h1>
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<p>To install GCC 7 run the following commands:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ sudo add-apt-repository ppa:ubuntu-toolchain-r/test
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$ sudo apt update && apt install g++-7 -y
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</pre></div>
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</div>
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<p>Set it as the default version:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 60 --slave /usr/bin/g++ g++ /usr/bin/g++-7
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$ sudo update-alternatives --config gcc
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</pre></div>
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</div>
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</div>
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<div class="section" id="installing-eigen">
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<h1>Installing Eigen</h1>
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<p>You will also need Eigen v3.3.7+, since the previous versions are incompatible with the latest CUDA versions.
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If you are on Ubuntu 20 or newer, then there is no issue since Eigen 3.3.7 is shipped by default.
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On older versions Eigen v3.3.7 will need to be installed manually:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ wget -qO- https://gitlab.com/libeigen/eigen/-/archive/3.3.7/eigen-3.3.7.tar.gz | tar xz
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$ sudo apt install -y libblas-dev
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$ cd eigen-3.3.7 && mkdir build && cd build
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$ cmake ..
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$ sudo make install
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$ cd ../.. && rm -rf eigen-3.3.7/ && rm -f eigen-3.3.7.tar.gz
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</pre></div>
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</div>
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</div>
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<div class="section" id="building-pcl">
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<h1>Building PCL</h1>
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<p>Now you can get the latest git master (or another one) of PCL and configure your
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installation to use the CUDA functions.</p>
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<p>Go to your PCL root folder and do:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ mkdir build; cd build
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$ ccmake ..
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</pre></div>
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</div>
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<p>Press c to configure ccmake, press t to toggle to the advanced mode as a number of options
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only appear in advanced mode. The latest CUDA algorithms are being kept in the GPU project, for
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this the BUILD_GPU option needs to be on and the BUILD_gpu_<X> indicate the different
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GPU subprojects.</p>
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<a class="reference internal image-reference" href="_images/gpu_ccmake.png"><img alt="_images/gpu_ccmake.png" src="_images/gpu_ccmake.png" style="width: 400pt;" /></a>
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<p>Press c again to configure for you options, press g to generate the makefiles and to exit. Now
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the makefiles have been generated successfully and can be executed by doing:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ make
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</pre></div>
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</div>
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<p>If you want to install your PCL installation for everybody to use:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ make install
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</pre></div>
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</div>
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<p>Now your installation is finished!</p>
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