Within business Intelligence contexts, the importance of data mining algorithms is continuously increasing, particularly from the perspective of applications and users that demand novel algorithms on the one hand and an efficient implementation exploiting novel system architectures on the other hand. Within this paper, we focus on the latter issue and report our experience with the exploitation of graphic card processor technology within the SAP NetWeaver business intelligence accelerator (BIA). The BIA represents a highly distributed analytical engine that supports OLAP and data mining processing primitives. The system organizes data entities in column-wise fashion and its operation is completely main-memory-based. Since case studies have shown that classic data mining queries spend a large portion of their runtime on scanning and filtering the data as a necessary prerequisite to the actual mining step, our main goal was to speed up this expensive scanning and filtering process. In a first step, the paper outlines the basic data mining processing techniques within SAP NetWeaver BIA and illustrates the implementation of scans and filters. In a second step, we give insight into the main features of a hybrid system architecture design exploiting graphic card processor technology. Finally, we sketch the implementation and give details of our vast evaluations.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:78850 |
| Date | 15 June 2022 |
| Creators | Lehner, Wolfgang, Weyerhaeuser, Christoph, Mindnich, Tobias, Faerber, Franz |
| Publisher | IEEE |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 978-0-7695-3503-6, 10.1109/ICDMW.2008.61 |
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