Adaptation of RBM learning for intel MIC architecture

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Abstract

In the paper, the parallel realization of the Boltzmann Restricted Machine (RBM) is proposed. The implementation intends to use multicore architectures of modern CPUs and Intel Xeon Phi coprocessor. The learning procedure is based on the matrix description of RBM, where the learning samples are grouped into packages, and represented as matrices. The influence of the package size on convergence of learning, as well as on performance of computation, are studied for various number of threads, using conventional CPU and Intel Phi architecures. Our research confirms a potential usefulness of MIC parallel architecture for implementation of RBM and similar algorithms.

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Olas, T., Mleczko, W. K., Nowicki, R. K., Wyrzykowski, R., & Krzyzak, A. (2015). Adaptation of RBM learning for intel MIC architecture. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 9119, pp. 90–101). Springer Verlag. https://doi.org/10.1007/978-3-319-19324-3_9

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