Vertex AI#

RAPIDS can be deployed on Vertex AI Workbench.

Create a new user-managed Notebook#

  1. From the Google Cloud UI, navigate to Vertex AI -> Notebook -> 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.

!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.

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
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