Abstract
High performance is a key requirement for a number of Semantic Web applications. Reasoning over large and extra-large data is the most challenging class of Semantic Web applications in terms of the performance demands. For such problems, parallelization is a key technology for achieving high performance and scalability. However. development of parallel application is still a challenge for the majority of Semantic Web algorithms due to their implementation in Java – a programming language whose design does not allow the porting to the High Performance Computing Infrastructures to be trivially achieved. The Message-Passing Interface (MPI) is a well-known programming paradigm, applied beneficially for scientific applications written in the “traditional” programming languages for High Performance Computing, such as C, C++ and Fortran. We describe an MPI based approach for implementing parallel Semantic Web applications and evaluate the performance of a pilot Semantical Statistics application - random indexing over large text volumes.
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Cheptsov, A. (2013). An Approach for Distributed Parallelization of Large-Scale Semantic Web Reasoners Based on MPI. In: Haller, A., Huang, G., Huang, Z., Paik, Hy., Sheng, Q.Z. (eds) Web Information Systems Engineering – WISE 2011 and 2012 Workshops. WISE WISE 2011 2012. Lecture Notes in Computer Science, vol 7652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38333-5_3
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DOI: https://doi.org/10.1007/978-3-642-38333-5_3
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