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RAPIDS 24.04 Release

  The RAPIDS 24.04 release is now available, and it includes a new accelerated vector search library, expanded zero-code change experiences for pandas and NetworkX workflows, optional query optimization for Dask workflows, support for Python 3.11 and pandas 2, and more...  
Post by Nick Becker

RAPIDS 24.02 release

  Zero code-change NetworkX, RAPIDS on Databricks with Dask, and more! RAPIDS just released its 24.02 version, which brings with it a major expansion to the new zero-code-change experience for NetworkX users, improvements to XGBoost 2.0, and improvements to cuDF’s parq...  
Post by Alex Ravenel

RAPIDS 23.10 Release

  The RAPIDS 23.10 release takes a huge step forward in breaking down barriers to bringing accelerated computing to the data science community. RAPIDS now enables a zero code change CPU/GPU user experience for dataframes, graph analytics, and machine learning. This rel...  
Post by Nick Becker

Intro to Graph Analysis using cuGraph: Similarity Algorithms

  This is the second chapter in our blog series on GPU-accelerated graph analysis using RAPIDS cuGraph. In the first chapter, we introduced the basics of graphs and analyzed them using a few of the many algorithms in cuGraph. That blog answered some practical questions...  
Post by Don Acosta

Intro to Graph Neural Networks with cuGraph-DGL

  Author: Vibhu Jawa Graph neural networks (GNNs) have emerged as a powerful tool for a variety of machine learning tasks on graph-structured data. These tasks range from node classification and link prediction to graph classification. They also cover a wide range of a...  
Post by Alex Ravenel

RAPIDS 23.08 Release

  The RAPIDS 23.08 release was a big one, with new features to support large-scale text processing and LLMs in both cuDF and RAFT, major new functionality to cuXfilter and cuSpatial (and the new cuProj library for coordinate transforms), impressive performance numbers ...  
Post by Alex Ravenel