RAPIDS | NVIDIA Setup on macOS

Accredian Publication
2 min readJan 27, 2022

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Introduction

Now that you got a basic idea about GPUs and their need in data science and why technologies like RAPIDS are essential, we will show you how to set up RAPIDS on Mac OS. Let’s start.

Installation of Miniconda Distribution

· To download the Miniconda toolkit click here.

· Follow the prompts on the installer screens.

· Test your installation in your terminal window or Anaconda Prompt, run the command conda list.

· A list of installed packages appears if it has been installed correctly.

Installation of CUDA Drivers

Next, you’ll need to download and install CUDA drivers by following the given link. You may choose the release which is most suitable for your system. Once the drivers are installed, you can verify the installation by running the following command:

nvcc -V

Installation of RAPIDS

We’ll be using the conda command to install the packages we need in this step. You can install RAPIDS with a single conda command for a specific CUDA version as shown below:

# for CUDA 11.0conda install -c rapidsai -c nvidia -c numba -c conda-forge \cudf=21.06 python=3.7 cudatoolkit=11.0# or, for CUDA 11.2conda install -c rapidsai -c nvidia -c numba -c conda-forge \cudf=21.06 python=3.7 cudatoolkit=11.2

To test your installation, start up the RAPIDS virtual environment. You can do this by:

· Typing out conda info — envs, which will let you know the name of the installed RAPIDS environment.

· Note: cuDF is supported only on Linux and with Python versions 3.7 and later.

· Finally, import any RAPIDS library or start a Jupyter notebook.

· And that’s it, fellas!

What’s next?

Regression in RAPIDS vs Sklearn

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