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Accelerating ETL on KubeFlow with RAPIDS

Aug 30, 2022 11 minute read #dask, #etl, #kubeflow, #pandas, #rapids, #technical-walkthrough Archive

In the machine learning and MLOps world, GPUs are widely used to speed up model training and inference, but what about the other stages of the workflow like ETL pipelines or hyperparameter optimization?
What is the difference between Dask and RAPIDS?

Jun 22, 2021 3 minute read #rapids, #dask, #pydata Archive

Both Dask and RAPIDS are Python libraries to scale your workflow and empower you to process more data and leverage more compute resources. Both use interfaces modeled after the PyData ecosystem, making them familiar to most data practitioners.
Monitoring Dask + RAPIDS with Prometheus + Grafana

Apr 9, 2021 6 minute read #rapids, #dask, #monitoring, #prometheus, #grafana Archive

Prometheus is a popular monitoring tool within the cloud community. It has out-of-the-box integration with popular platforms including Kubernetes, Open Stack, and the major cloud vendors, and integrates with dashboarding tools like Grafana.
Setting up GPU Data Science Environments for Hackathons

Aug 13, 2019 6 minute read #rapids, #iris, #aws, #jupyterhub, #cuda, #gpu Archive

Originally published on the RAPIDS AI blog on August 13th, 2019.

Background

In my first week working at NVIDIA, I have been spending some time with my previous colleagues at the Met Office to explore how the two organizations can collaborate.

Accelerating ETL on KubeFlow with RAPIDS