Graph Algorithms

UMAP is a popular dimension reduction algorithm used in fields like bioinformatics, NLP topic modeling, and ML preprocessing. It works by creating a k-nearest...

CUDA Graphs are a way to define and batch GPU operations as a graph rather than a sequence of stream launches. A CUDA Graph groups a set of CUDA kernels and...

Graphs form the foundation of many modern data and analytics capabilities to find relationships between people, places, things, events, and locations across...

Join us April 12 and ask experts about NVIDIA cuGraph with added support for GNN, accelerated aggregators, models, and extensions to DGL and PyG.

With the latest Memgraph Advanced Graph Extensions (MAGE) release, you can now run GPU-powered graph analytics from Memgraph in seconds, while working in...

Data scientists across various domains use clustering methods to find naturally ‘similar’ groups of observations in their datasets. Popular clustering...

Graphs are mathematical structures used to model many types of relationships and processes in physical, biological, social and information systems. They are...

In this blog post I will briefly discuss the importance and simplicity of graph coloring and its application to one of the most common problems in sparse linear...

Graph analysis is a fundamental tool for domains as diverse as social networks, computational biology, and machine learning. Real-world applications of graph...