A framework for developing Real-Time OLAP algorithm using multi-core processing and GPU: Heterogeneous computing

The overwhelmingly increasing amount of stored data has spurred researchers seeking different methods in order to optimally take advantage of it which mostly have faced a response time problem as a result of this enormous size of data. Most of solutions have suggested materialization as a favourite...

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Bibliographic Details
Main Authors: Alzeini, Haytham I M, Hameed, Shihab A., Habaebi, Mohamed Hadi
Format: Conference or Workshop Item
Language:English
English
English
Published: 2013
Subjects:
Online Access:http://irep.iium.edu.my/31940/1/2096.pdf
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http://irep.iium.edu.my/31940/6/icomabstracts.pdf
http://irep.iium.edu.my/31940/
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Summary:The overwhelmingly increasing amount of stored data has spurred researchers seeking different methods in order to optimally take advantage of it which mostly have faced a response time problem as a result of this enormous size of data. Most of solutions have suggested materialization as a favourite solution. However, such a solution cannot attain Real-Time answers anyhow. In this paper we propose a framework illustrating the barriers and suggested solutions in the way of achieving Real-Time OLAP answers that are significantly used in decision support systems and data warehouses.