The Optimization of Algorithms in the Process of Temporal Data Mining Using the Compute Unified Device Architecture

Alexandru Pirjan ()
Additional contact information
Alexandru Pirjan: Academy of Economic Studies, Bucharest

Database Systems Journal, 2010, vol. 1, issue 1, 37-47

Abstract: Considering the importance and usefulness of real time data mining, in recent years the concern of researchers to discover new hardware architectures that can manage and process large volumes of data has increased significantly. In this paper the performance of algorithms for temporal data mining that are implemented in the new Compute Unified Device Architecture (CUDA) from the latest generation of graphics processing units (GPU) will be analyzed and reviewed. The performance will be evaluated taking into account the type of algorithm, data access, the problems` size, the GPU’s processor generation, the number of threads processed.

Keywords: Temporal data mining; MapReduce; CUDA; GPU; Fermi; thread; kernel. (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://dbjournal.ro/archive/1/1_6_Pirjan_Alexandru.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aes:dbjour:v:1:y:2010:i:1:p:37-47

Access Statistics for this article

Database Systems Journal is currently edited by Ion Lungu

More articles in Database Systems Journal from Academy of Economic Studies - Bucharest, Romania Contact information at EDIRC.
Bibliographic data for series maintained by Adela Bara ().