Madani, Sina, Kolovos, Dimitrios S. orcid.org/0000-0002-1724-6563 and Paige, Richard F. orcid.org/0000-0002-1978-9852 (2018) Parallel model validation with epsilon. In: Modelling Foundations and Applications - 14th European Conference, ECMFA 2018, Held as Part of STAF 2018, Proceedings. 14th European Conference on Modelling Foundations and Applications, ECMFA 2018 Held as Part of STAF 2018, 26-28 Jun 2018 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer , FRA , pp. 115-131.
Abstract
Traditional model management programs, such as transformations, often perform poorly when dealing with very large models. Although many such programs are inherently parallelisable, the execution engines of popular model management languages were not designed for concurrency. We propose a scalable data and rule-parallel solution for an established and feature-rich model validation language (EVL). We highlight the challenges encountered with retro-fitting concurrency support and our solutions to these challenges. We evaluate the correctness of our implementation through rigorous automated tests. Our results show up to linear performance improvements with more threads and larger models, with significantly faster execution compared to interpreted OCL.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 10 Jul 2018 11:30 |
Last Modified: | 16 Oct 2024 10:59 |
Published Version: | https://doi.org/10.1007/978-3-319-92997-2_8 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Identification Number: | 10.1007/978-3-319-92997-2_8 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:133088 |