Kharma, Myriam (2017) GRUEL: An EL Reasoner Using General Purpose Computing on a Graphical Processing Unit. Masters thesis, Concordia University.
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Abstract
Abstract
GRUEL: AN EL REASONER USING GENERAL PURPOSE COMPUTING ON A GRAPHICAL PROCESSING UNIT
Myriam Kharma
The third installment of the worldwide web (Web 3.0) relies on an infrastructure of efficient reasoners, able to quickly infer new knowledge from existing data. We have created a reasoner using general purpose computing on a graphical processing unit (GPU) for the “Existential Language” description language, denoted with EL, that exploits the processing power of a GPU while attempting to solve a logic-based artificial intelligence problem.
To classify small ontologies, our system is nearly 70% faster than other reasoners we have compared it with. Currently far from perfect, GRUEL is planned to improve and expand, yet for the moment proves that better performance is achievable, and that general purpose computing on a GPU is a methodology worth exploring while developing the semantic web.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering |
|---|---|
| Item Type: | Thesis (Masters) |
| Authors: | Kharma, Myriam |
| Institution: | Concordia University |
| Degree Name: | M. Comp. Sc. |
| Program: | Computer Science |
| Date: | April 2017 |
| Thesis Supervisor(s): | Haarslev, Volker |
| ID Code: | 982475 |
| Deposited By: | MYRIAM KHARMA |
| Deposited On: | 09 Jun 2017 15:00 |
| Last Modified: | 18 Jan 2018 17:55 |
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