High-performance computing for data analytics
| Data(s) |
2012
|
|---|---|
| Resumo |
One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques. |
| Formato |
application/pdf |
| Identificador | |
| Publicador |
IEEE Computer Society |
| Relação |
http://eprints.qut.edu.au/82681/1/82681.pdf DOI:10.1109/DS-RT.2012.41 Perrin, D., Bezbradica, M., Crane, M., Ruskin, H.J, & Duhamel, C. (2012) High-performance computing for data analytics. In DS-RT '12 Proceedings of the 2012 IEEE/ACM 16th International Symposium on Distributed Simulation and Real Time Applications, IEEE Computer Society, Dublin, Ireland, pp. 234-242. |
| Direitos |
Copyright 2012 IEEE Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
| Tipo |
Conference Paper |
