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A Heterogeneous System Based on Latent Semantic Analysis Using GPU and Multi-CPU
Joint Authors
Sánchez-Escobar, Juan J.
León-Paredes, Gabriel A.
Barbosa-Santillán, Liliana Ibeth
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-05
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Latent Semantic Analysis (LSA) is a method that allows us to automatically index and retrieve information from a set of objects by reducing the term-by-document matrix using the Singular Value Decomposition (SVD) technique.
However, LSA has a high computational cost for analyzing large amounts of information.
The goals of this work are (i) to improve the execution time of semantic space construction, dimensionality reduction, and information retrieval stages of LSA based on heterogeneous systems and (ii) to evaluate the accuracy and recall of the information retrieval stage.
We present a heterogeneous Latent Semantic Analysis (hLSA) system, which has been developed using General-Purpose computing on Graphics Processing Units (GPGPUs) architecture, which can solve large numeric problems faster through the thousands of concurrent threads on multiple CUDA cores of GPUs and multi-CPU architecture, which can solve large text problems faster through a multiprocessing environment.
We execute the hLSA system with documents from the PubMed Central (PMC) database.
The results of the experiments show that the acceleration reached by the hLSA system for large matrices with one hundred and fifty thousand million values is around eight times faster than the standard LSA version with an accuracy of 88% and a recall of 100%.
American Psychological Association (APA)
León-Paredes, Gabriel A.& Barbosa-Santillán, Liliana Ibeth& Sánchez-Escobar, Juan J.. 2017. A Heterogeneous System Based on Latent Semantic Analysis Using GPU and Multi-CPU. Scientific Programming،Vol. 2017, no. 2017, pp.1-19.
https://search.emarefa.net/detail/BIM-1203475
Modern Language Association (MLA)
León-Paredes, Gabriel A.…[et al.]. A Heterogeneous System Based on Latent Semantic Analysis Using GPU and Multi-CPU. Scientific Programming No. 2017 (2017), pp.1-19.
https://search.emarefa.net/detail/BIM-1203475
American Medical Association (AMA)
León-Paredes, Gabriel A.& Barbosa-Santillán, Liliana Ibeth& Sánchez-Escobar, Juan J.. A Heterogeneous System Based on Latent Semantic Analysis Using GPU and Multi-CPU. Scientific Programming. 2017. Vol. 2017, no. 2017, pp.1-19.
https://search.emarefa.net/detail/BIM-1203475
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1203475