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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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English English English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/31940/1/2096.pdf http://irep.iium.edu.my/31940/4/image002.png 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. |
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