Graph database system with parallelized graph partitioning
WO2025049166A3 Publication Date: 2025-04-03NEO4J SWEDEN AB
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Patent Information
- Application Number
- PCT/US2024/043018
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-08-31
- Filing Date
- 2024-08-20
- Publication Date
- 2025-04-03
AI Technical Summary
Technical Problem
Existing graph database systems face challenges in efficiently performing large graph analytics due to inadequate performance and difficulty in optimizing algorithms for such tasks.
Method used
A graph database system that employs parallelized graph partitioning using multiple threads to perform approximate max-k cut processing, enabling faster processing without introducing inaccuracies.
Benefits of technology
This approach significantly speeds up graph partitioning processes, making them more efficient for a broad range of graph analytics applications while maintaining accuracy.
✦ Generated by Eureka AI based on patent content.
Abstract
A method and high-performance apparatus for creating an approximate maximum k-cut of a graph. In various embodiments, nodes and weighted edges in a graph are used to compute a partitioning of a graph such that the edge weight between partitions is maximized. In various embodiments, the method and apparatus use a greedy random construction of cuts for its first approximation, whose solutions are then subject to local search for better solutions, and local path-relinking for the final level of refinement. In various embodiments, one or more of the greedy random construction, local search, and path relinking are parallelized. A novel parallel algorithm is disclosed for perturbing the state of a cut to see if a better one is cheaply available.
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