rapids

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

cuGraph - RAPIDS Graph Analytics Library

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

NVIDIA cuDF for Apache Spark 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.

GPU accelerated cross filtering with cuDF.

Very fast, accurate speaker diarization

Comparing performance-oriented string-processing libraries for substring search, multi-pattern matching, hashing, edit-distances, sketching, and sorting across CPUs and GPUs in Rust 🦀 and Python 🐍

GPU Accelerated Backend for NetworkX

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.

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.

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!