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

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...

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Bibliographic Details
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
ISSN:	1995-0802, 1818-9962
Online Access:	Get full text
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