Need specific versions such as CUDA 11.5 or Python 3. If you want to use Docker, WSL2, have an uncommon OS, hardware configuration, environment, or Use the Windows WSL2 installation instructions Do I need an Advanced Install? One of these processes is owned by my user, and the other by gdm. Pip install cugraph-cu11 -extra-index-url= Install with DockerĬheck that you have the required environment and then use the install selector Install on Windows I noticed that Ubuntu 20.04 uses almost 400MB more RAM when using Nvidia drivers than with Intel’s drivers and also, looking at the active process, that there are 2 gnome-shell processes running along when using Nvidia’s driver, which not happens with Intel. Install via pip channels: pip install cudf-cu11 dask-cudf-cu11 -extra-index-url= Then quick install RAPIDS with: conda create -n rapids-23.04 -c rapidsai -c conda-forge -c nvidia \ rapids=23.04 python=3.10 cudatoolkit=11.8 Install with pipġ. If conda is not installed, download and run the install script: wget Ģ. Recent CUDA version and NVIDIA driver pairs. Ubuntu 20.04 or 22.04, CentOS 7, Rocky Linux 8, or WSL2 on Windows 11Ĭ. NVIDIA Pascal™ or better GPU with a compute capability 6.0 and aboveī. RAPIDS offers several installation methods, the quickest is shown below.
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