Truly parallel Model-Matching algorithm in openCL

Abstract

The Model-driven Engineering (MDE) is coming into focus faster and faster nowadays because it can significantly simplify and accelerate the software development and maintenance processes. MDE can efficiently reduce resource requirements not only in development, but also in refactoring and maintenance tasks of complex software systems. There are several tools to support MDE. Although, these tools can deal with the average size of the currently applied domain models, the growing software systems can cause challenges in model manipulations. The growing size of systems can result in such a slow computation which cannot be accepted anymore. Therefore, more efficient model processing methods are needed. We are working on a complex, high performant model-transformation engine for MDE tools. Our solution can take the advantage of parallel computation available for example in modern GPUs. The engine is referred to as PaMMTE (Parallel Multiplatform Model-transformation Engine). In earlier publications, the architecture and functionality of our engine has been introduced and the functional correctness has also been proven. In this paper, we introduce a new pattern matching algorithm. The algorithm is truly parallel, it is scalable and more efficient than the previous version. Moreover, we analyze the current and the new pattern matching algorithms in general and the performance gain achieved. The new pattern matching algorithm can be effectively used not only in PaMMTE, but in any other cases, when high-performant pattern matching computation is required.