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Parallelization of the DIANA Algorithm in OpenMP

  • Hethini Ribeiro
  • Roberta SpolonEmail author
  • Aleardo ManaceroJr.
  • Renata S. Lobato
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 931)

Abstract

Global data production has been increasing by approximately 40% per year since the beginning of the last decade. These large datasets, also called Big Data, are posing great challenges in many areas and in particular in the Machine Learning (ML) field. Although ML algorithms are able to extract useful information from these large data repositories, they are computationally expensive such as AGNES and DIANA, which have O(n) and O(2n) complexity, respectively. Therefore, the big challenge is to process large amounts of data in a realistic time frame. In this context, this paper proposes the parallelization of the DIANA OpenMP algorithm. Initial tests with a database with 5000 elements presented a speed up of 5,2521. It is believed that, according to Gustafson’s law, for a larger database the results will also be larger.

Keywords

Machine learning Parallelization DIANA OpenMP 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Hethini Ribeiro
    • 1
  • Roberta Spolon
    • 1
    Email author
  • Aleardo ManaceroJr.
    • 2
  • Renata S. Lobato
    • 2
  1. 1.Computer DepartmentUniversidade Estadual Paulista “Júlio de Mesquita Filho” (UNESP)BauruBrazil
  2. 2.Department of Computer Science and StatisticsUniversidade Estadual Paulista “Júlio de Mesquita Filho” (UNESP)São José do Rio PretoBrazil

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