An open computing language‐based parallel Brute Force algorithm for formal concept analysis on heterogeneous architectures. (6th February 2021)

• Record Type: Journal Article
• Authors: Novais, João P. P.; Maciel, Lucas A.; Souza, Matheus A.; Song, Mark A. J.; Freitas, Henrique C.
• Other Names: Oh Sangyoon guestEditor.; de Camargo Raphael Y. guestEditor.; Marozzo Fabrizio guestEditor.; Martins Wellington guestEditor.; Kołodziej Joanna guestEditor.; Jaatun Martin Gilje guestEditor.
• Is Part Of: Concurrency and computation. Volume 33:Number 18(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-02-06
• Subjects: Brute Force algorithm -- formal concept analysis -- heterogeneous architectures -- OpenCL; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.6220
• Languages: English
• ISSNs: 1532-0626

Abstract

Abstract: Algorithms for the extraction of formal concepts are widely studied in several areas of knowledge, such as finance, health, and statistics. However, these algorithms require high‐performance processing due to their combinatorial characteristics. In this work, an Open computing language (OpenCL)‐based Brute Force algorithm is proposed and evaluated for formal concept extraction on heterogeneous architectures (CPU+GPU and CPU+FPGA). The CPU+GPU architecture presents higher performance and scalability than other architectures when our Brute Force algorithm processes high dimensional contexts with many objects and attributes. Our parallel approach shows performance results up to 18× better than a smarter sequential algorithm called Data‐Peeler. Moreover, our Brute Force algorithm running on CPU+GPU architecture has greater energy efficiency, reaching at least 1.79× more operations per energy consumption than other algorithms on different architectures explored in this work.