PADDi: Highly Scalable Parallel Algorithm for Discord Discovery on Multi-GPU Clusters

• Published in: Lobachevskii journal of mathematics Vol. 46; no. 4; pp. 1480 - 1494
• Main Authors: Kraeva, Y. A., Zymbler, M. L.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.04.2025; Springer Nature B.V
• Subjects: Algebra; Algorithms; Analysis; Clusters; Configuration management; Data exchange; Data mining; Geometry; Mathematical Logic and Foundations; Mathematics; Mathematics and Statistics; Nodes; Probability Theory and Stochastic Processes; Segments; Time series; CUDA; 62M10; anomaly; discord discovery; parallel algorithm; time series; high-performance cluster; GPU; 65Y05

Currently, in a wide spectrum of subject domains, time series data mining requires the efficient subsequence anomaly discovery in a very long time series, which cannot be entirely placed in RAM. At present, one of the best approaches to solving such a problem is to formalize the anomaly as a discord...