# Vertex AI RAPIDS can be deployed on [Vertex AI Workbench](https://cloud.google.com/vertex-ai-workbench). ## Create a new user-managed Notebook 1. From the Google Cloud UI, navigate to [**Vertex AI**](https://console.cloud.google.com/vertex-ai/workbench/user-managed) -> **Workbench** 2. Make sure you select **User-Managed Notebooks** (**Managed Notebooks** are currently not supported) and select **+ CREATE NEW**. 3. In the **Details** section give the instance a name. 4. Under the **Environment** section choose "Python 3 with CUDA 11.8". 5. Check the "Attach 1 NVIDIA T4 GPU" option. 6. After customizing any other aspects of the machine you wish, click **CREATE**. ```{tip} If you want to select a different GPU or select other hardware options you can select "Advanced Options" at the bottom and then make changes in the "Machine type" seciton. ``` ## Install RAPIDS Once the instance has started select **OPEN JUPYTER LAB** and at the top of a notebook install the RAPIDS libraries you wish to use. ```bash !pip install cudf-cu11 dask-cudf-cu11 --extra-index-url=https://pypi.nvidia.com !pip install cuml-cu11 --extra-index-url=https://pypi.nvidia.com !pip install cugraph-cu11 --extra-index-url=https://pypi.nvidia.com ``` ## Test RAPIDS You should now be able to open a notebook and use RAPIDS. For example we could import and use RAPIDS libraries like `cudf`. ```ipython In [1]: import cudf In [2]: df = cudf.datasets.timeseries() In [3]: df.head() Out[3]: id name x y timestamp 2000-01-01 00:00:00 1020 Kevin 0.091536 0.664482 2000-01-01 00:00:01 974 Frank 0.683788 -0.467281 2000-01-01 00:00:02 1000 Charlie 0.419740 -0.796866 2000-01-01 00:00:03 1019 Edith 0.488411 0.731661 2000-01-01 00:00:04 998 Quinn 0.651381 -0.525398 ``` ```{relatedexamples} ```