RAPIDS AI

Topic modeling for text processing, Deep Learning based embedding creation, reduction, and clustering on GPUs.

Bringing more integration points, expanding functionality, and improving performance.

RAPIDS 21.12 strengthens the GPU analytics foundation, improves ecosystem compatibility, and brings new functionality and integrations.

Release 21.10 continues to work toward the vision of making GPU speed available to everyone

Learn how to use RAPIDS and Dask to make NLP pipelines for indexing, summation, and text clustering much faster.

We’re excited to announce the release of RAPIDS version 21.08! See the latest core features and community updates.

With GPU acceleration, PyCaret modeling times can be between 2 and 200 times faster depending on the workload.

See what kinds of workloads are accelerated with RAPIDS and how to get started right away on Paperspace Gradient

Introducing node-RAPIDS

New Features Added to RAPIDS cuXfilter GPU-Accelerated Cross Filtering Library

Together, Dask and RAPIDS allow you to scale up and scale out production Python workloads at the same time.

RAPIDS Versioning for Continuous Improvement

Learn how we’re fuzz testing IO readers and writers with randomly generated data and parameters to catch bugs and improve reliability

RAPIDS 0.19 Released at GTC Spring 2021

RAPIDS cuDF release 0.19 introduces improved support for nested types such as lists and structs.

Use Prometheus and Grafana to instrument your RAPIDS deployment and monitor how your workflows are performing on your system.

Checkout the latest features and updates.

A tutorial to run RAPIDS and your favorite Linux software, including NVIDIA CUDA, on Windows.

See why you should push the filtering operation down to the read calls whenever possible.

This release is focused on improvements in three main areas: performance, functionality, and user experience.

Simply sprinkling RAPIDS cuDF scalars into your workflow can result in nontrivial speedup without any additional code changes.

Scale RAPIDS from a local machine to a multi-GPU cluster on GCP with Dask. Explore w/ affordable cloud resources and scale when ready.

TL;DR — With the release of XGBoost 1.3 comes an exciting new feature for model interpretability — GPU accelerated SHAP values. SHAP…

Covers setup of remote repositories on Artifactory 7.x and RAPIDS conda installation