A Hybrid Approach for Optimizing Parallel Clustering Throughput using the GPU

We introduce Hybrid-Dbscan , that uses the GPU and CPUs for optimizing clustering throughput. The main idea is to exploit the memory bandwidth on the GPU for fast index searches, and optimize data transfers between host and GPU, to alleviate the potential negative performance impact of the PCIe inte...

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Bibliographic Details
Published in:	IEEE transactions on parallel and distributed systems Vol. 30; no. 4; pp. 766 - 777
Main Authors:	Gowanlock, Michael, Rude, Cody M., Blair, David M., Li, Justin D., Pankratius, Victor
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.04.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Clustering Clustering algorithms Datasets DBSCAN Galaxies GPGPU Graphics processing units in-memory database Indexing Kernel Optimization parallel clustering Performance degradation query optimization Red shift Response time (computers) Sky surveys (astronomy) spatial databases Throughput Time factors
ISSN:	1045-9219, 1558-2183
Online Access:	Get full text
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