cuGraph - RAPIDS Graph Analytics Library

cuDF - GPU DataFrame Library

A header-only library for accelerating vector searches using Intel AMX (Advanced Matrix Extensions)

RAPIDS Memory Manager

Spark RAPIDS plugin - accelerate Apache Spark with GPUs

GPU accelerated cross filtering with cuDF.

GPU Accelerated Backend for NetworkX

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

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.

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.

Utility to run/debug Spark RAPIDS in REPL

Supercharge Your Polars Code with RAPIDS cuDF on a GPU

RAPIDS cuDF Instantly Accelerates pandas up to 50x on Google Colab With Demo

For graphics processing unit accelerated data science via rapids.ai

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.

Rapids and rivers pattern interpretation and implementation

Códigos PYTHON. Pandas, Scikit-Learning, Rapids, Cuml, Cudf.

GPU-based ML to classify Higgs boson signal from background in particle physics using RAPIDS framework

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

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