基于mpi的多关系概念发现的并行化

2011 10th International Conference on Machine Learning and Applications and Workshops Pub Date : 2011-12-18 DOI:10.1109/ICMLA.2011.98

Alev Mutlu, P. Senkul, Y. Kavurucu

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引用次数: 0

摘要

多关系概念发现是一种预测性学习任务，旨在根据过去的经验发现目标概念的描述。并行化已经成为解决概念发现系统中与大型搜索空间相关的效率和可伸缩性问题的一种解决方案。在这项工作中，我们描述了一种基于ilp的概念发现系统的并行化方法，称为CRIS。CRIS的修改方式是，以数据并行的方式重新组织涉及高查询处理的步骤。为了评估最终系统(称为P-CRIS)的性能，进行了一系列实验。

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MPI-based Parallelization for ILP-based Multi-relational Concept Discovery

Multi-relational concept discovery is a predictive learning task that aims to discover descriptions of a target concept in the light of past experiences. Parallelization has emerged as a solution to deal with efficiency and scalability issues relating to large search spaces in concept discovery systems. In this work, we describe a parallelization method for the ILP-based concept discovery system called CRIS. CRIS is modified in such a way that steps involving high query processing are reorganized in a data parallel way. To evaluate the performance of the resulting system, called P-CRIS, a set of experiments is conducted.

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2011 10th International Conference on Machine Learning and Applications and Workshops

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