cuDF - GPU DataFrame Library

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.

cuGraph - RAPIDS Graph Analytics Library

Spark RAPIDS plugin - accelerate Apache Spark with GPUs

Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, NetworkX, RAPIDS, RDFlib, pySHACL, PyVis, morph-kgc, pslpython, pyarrow, etc.

RAPIDS Memory Manager

GPU accelerated cross filtering with cuDF.

Python client for OmniSci GPU-accelerated SQL engine and analytics platform

Rapid large-scale fractional differencing with NVIDIA RAPIDS and GPU to minimize memory loss while making a time series stationary. 6x-400x speed up over CPU implementation.

Nvidia DLI workshop on AI-based predictive maintenance techniques to identify anomalies and failures in time-series data, estimate the remaining useful life of the corresponding parts, and map anomalies to failure conditions.

Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques.

GPU Accelerated Backend for NetworkX

RAPIDS data science. No setup required.

Template repository for a Python 3-based (data) science project with GPU acceleration using NVIDIA RAPIDS libraries.

The Incredible RAPIDS: a curated list of tutorials, papers, projects, communities and more relating to RAPIDS.

Building NVIDIA's RAPIDS (cuDF, cuML...) in Arch Linux

Utility to run/debug Spark RAPIDS in REPL

A simple demo of cuDF which is a RAPIDS GPU-Accelerated Dataframe Library!