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:
Coming Soon
- 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
- Seunghwa Kang, Chuck Hastings, Joe Eaton, Brad Rees cuGraph C++ primitives: vertex/edge-centric building blocks for parallel graph computing
- 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).
- A Gondhalekar, P Sathre, W Feng Hybrid CPU-GPU Implementation of Edge-Connected Jaccard Similarity in Graph Datasets
- 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