11562

A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing

H.I. Alzeini, Sh.A. Hameed, M.H. Habaebi
Electrical and Computer Department, IIUM, PO: 53100, Jalan Gombak, Kuala-Lumpur, Malaysia
arXiv:1402.3781 [cs.DC], (16 Feb 2014)

@article{2014arXiv1402.3781A,

   author={Alzeini}, H. and {Hameed}, S.~A and {Habaebi}, M.},

   title={"{A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1402.3781},

   primaryClass={"cs.DC"},

   keywords={Computer Science – Distributed, Parallel, and Cluster Computing},

   year={2014},

   month={feb},

   adsurl={http://adsabs.harvard.edu/abs/2014arXiv1402.3781A},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

Download Download (PDF)   View View   Source Source   

542

views

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.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: