Abstract
Data mining (DM) applications are composed of computing-intensive processing tasks working on huge datasets. Due to its computing-intensive nature, these applications are natural candidates for execution on high performance, high throughput platforms such as PC clusters and computational grids. Many data mining algorithms can be implemented as bag-of-tasks (BoT) applications, i.e., parallel applications composed of independent tasks. This paper discusses the use of computing grids for the execution of DM algorithms as BoT applications, investigates the scalability of the execution of an application and proposes an approach to improve its scalability.
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da Silva, F.A.B., Carvalho, S., Senger, H., Hruschka, E.R., de Farias, C.R.G. (2004). Running Data Mining Applications on the Grid: A Bag-of-Tasks Approach. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds) Computational Science and Its Applications – ICCSA 2004. ICCSA 2004. Lecture Notes in Computer Science, vol 3044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24709-8_18
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DOI: https://doi.org/10.1007/978-3-540-24709-8_18
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