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Photo by @solenfeyissa

A Quick Look at RAPIDS

From GPU dataframes to GPU accelerated ML algorithms

The tagline for RAPIDS is ‘Open GPU Data Science’. I spotted RAPIDS in a recent article they posted in combination with HuggingFace and Dask.

A quick note on HuggingFace and Dask:

  • “The Hugging Face transformers package is an immensely popular Python library providing pretrained models that are extraordinarily useful for a variety of natural language processing (NLP) tasks.”
  • “Dask provides advanced parallelism for analytics”

Apparently, combining the three could be advantageous according to RAPIDS of course. However, what is RAPIDS?

RAPIDS provides GPU Accelerated libraries for data science.

They have several guides online:

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Screenshot of rapids.ai taken the 14th of September

Alongside documentation.

As well as available repositories online on GitHub, additionally:

“RAPIDS is open source licensed under Apache 2.0, spanning multiple projects that range from GPU dataframes to GPU accelerated ML algorithms. Its also provides native array_interface support, allowing Apache Arrow data to be pushed to deep learning frameworks.”

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Screenshot of rapids.ai taken the 14th of September

It seems there is some form of collaboration with NVIDIA as well.

It looks like an interesting package.

This is #500daysofAI and you are reading article 468. I am writing one new article about or related to artificial intelligence every day for 500 days.

Written by

AI Policy and Ethics at www.nora.ai. Student at University of Copenhagen MSc in Social Data Science. All views are my own. twitter.com/AlexMoltzau

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