Distributed model validation with Epsilon

Scalable performance is a major challenge with current model management tools. As the size and complexity of models and model management programs increases and the cost of computing falls, one solution for improving performance of model management programs is to perform computations on multiple comp...

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Bibliographic Details
Published in:Software and systems modeling Vol. 20; no. 5; pp. 1689 - 1712
Main Authors: Madani, Sina, Kolovos, Dimitris, Paige, Richard F.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-10-2021
Springer Nature B.V
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Summary:Scalable performance is a major challenge with current model management tools. As the size and complexity of models and model management programs increases and the cost of computing falls, one solution for improving performance of model management programs is to perform computations on multiple computers. In this paper, we demonstrate a low-overhead data-parallel approach for distributed model validation in the context of an OCL-like language. Our approach minimises communication costs by exploiting the deterministic structure of programs and can take advantage of multiple cores on each (heterogeneous) machine with highly configurable computational granularity. Our performance evaluation shows that the implementation is extremely low overhead, achieving a speed up of 24.5 × with 26 computers over the sequential case, and 122 × when utilising all six cores on each computer.
ISSN:1619-1366
1619-1374
DOI:10.1007/s10270-021-00878-x