支持向量机模型选择的混合并行实现

2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing Pub Date : 2015-03-04 DOI:10.1109/PDP.2015.97

Giuseppe Ripepi, A. Clematis, D. D'Agostino

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引用次数: 3

摘要

模型选择(MS)是任何统计分析的重要组成部分，对于支持向量机来说，为了达到最佳性能是至关重要的。然而，MS是一个计算密集的非凸问题，因此高效的并行化是非常必要的。出于这个原因，在这项工作中，我们比较了两种不同的MS并行化方法，基于MPI和混合MPI+OpenMP组合的使用。结果表明，使用后一种解决方案具有明显的优势。

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A Hybrid Parallel Implementation of Model Selection for Support Vector Machines

The Model Selection (MS) is an important part of any statistical analysis, and for Support Vector Machine becomes crucial in order to reach the best performance. However, the MS is a compute intensive and non-convex problem, therefore an efficient parallelization is highly desirable. For this reason, in this work we compare two different approaches in MS parallelization, based on the use of MPI and hybrid MPI+OpenMP composition. Results show a clear and considerable advantage in using the latter solution.

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来源期刊

2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing

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