While the main data graph showed all the relationships among factors, the team's complementary, "sparser" graph showed only what the scientists call conflicts within the data.

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

Neo4j Aura Graph Analytics comes with more than 65 ready-to-use graph algorithms and is optimized for high-performance AI applications, with support for parallel workflows ensuring any app can ...

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.

In parallel, researchers have developed efficient reduction rules and fixed-parameter algorithms that address NP-complete aspects of computing convexity parameters in various graph structures ...

The offering includes the industry’s largest selection of 65+ ready-to-use graph algorithms, and is optimized for high-performance applications and parallel workflows. Users pay only for the ...

It’s often assumed that Dijkstra’s algorithm, or the A* graph traversal algorithm is used, but the reality is that although these pure graph theory algorithms are decidedly influential, they ...