cuGraph Blogs and Presentations

The RAPIDS team blogs at https://medium.com/rapids-ai, and many of these blog posts provide deeper dives into features from cuGraph. Here, we’ve selected just a few that are of particular interest to cuGraph users:

Blogs & Conferences

2022

• GTC: State of cuGraph (video & slides)

• GTC: Scaling and Validating Louvain in cuGraph against Massive Graphs (video & slides)

• KDD Tutorial on Accelerated GNN Training with DGL/PyG and cuGraph

2021

• GTC 21 - State of RAPIDS cuGraph and what’s comming next

2020

• Status of RAPIDS cuGraph — Refactoring Code And Rethinking Graphs

• Tackling Large Graphs with RAPIDS cuGraph and CUDA Unified Memory on GPUs

• RAPIDS cuGraph adds NetworkX and DiGraph Compatibility

• Large Graph Visualization with RAPIDS cuGraph

• GTC 20 Fall - cuGraph Goes Big

2019

• RAPIDS cuGraph

• RAPIDS cuGraph — The vision and journey to version 1.0 and beyond

• RAPIDS cuGraph : multi-GPU PageRank

• Similarity in graphs: Jaccard versus the Overlap Coefficient

• GTC19 Spring - Accelerating Graph Algorithms with RAPIDS

• GTC19 Fall - Multi-Node Multi-GPU Machine Learning and Graph Analytics with RAPIDS

2018

• GTC18 Fall - RAPIDS: Benchmarking Graph Analytics on the DGX-2

Media

• Nvidia Rapids cuGraph: Making graph analysis ubiquitous

• RAPIDS cuGraph – Accelerating all your Graph needs

Academic Papers

• Alex Fender, Brad Rees, Joe Eaton (2022) Massive Graph Analytics Bader, D. (Editor) CRC Press

• S Kang, A. Fender, J. Eaton, B. Rees:Computing PageRank Scores of Web Crawl Data Using DGX A100 Clusters. In IEEE HPEC, Sep. 2020

• Hricik, T., Bader, D., & Green, O. (2020, September). Using RAPIDS AI to accelerate graph data science workflows. In 2020 IEEE High Performance Extreme Computing Conference (HPEC) (pp. 1-4). IEEE.

• Richardson, B., Rees, B., Drabas, T., Oldridge, E., Bader, D. A., & Allen, R. (2020, August). Accelerating and Expanding End-to-End Data Science Workflows with DL/ML Interoperability Using RAPIDS. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 3503-3504).

Other Blogs

• 4 graph algorithms on steroids for data scientists with cugraph

• Where should I walk

• Where really are the parking spots?

• Accelerating Single Cell Genomic Analysis using RAPIDS

• Running Large-Scale Graph Analytics with Memgraph and NVIDIA cuGraph Algorithms

• Dev Blog Repost: Similarity in Graphs: Jaccard Versus the Overlap Coefficient

RAPIDS Event Notebooks

• KDD 2022 Notebook that demonstates using cuDF for ETL/data cleaning and XGBoost for training a fraud predection model.

• SciPy 22 Notebook comparing cuGraph to NetworkX

• KDD 2020 Tutorial Notebooks - Accelerating and Expanding End-to-End Data Science Workflows with DL/ML Interoperability Using RAPIDS