Title: An enhanced parallel processing algorithm based on TOP-K decomposition of hypercube model

Authors: Quanyou Zhang; Yong Feng; Bao-hua Qiang; Yaohui Li

Addresses: Chongqing University, Chongqing, 400044, China; Xuchang University, Xuchang, 461000, China ' Chongqing University, Chongqing, 400044, China ' Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China; Guangxi Key Laboratory of Optoelectronic Information Processing, Guilin University of Electronic Technology, Guilin 541004, China ' Xuchang University, Xuchang, 461000, China

Abstract: Parallel processing technology has been widely used in many fields. We will discuss the technology of large-scale data parallel computing based on network. The parallel processing method based on hypercube model could divide large-scale data into a large number of sub-datasets, which will be distributed to each processing unit. But empty hypercube units existed because of uneven segmentation. To solve this question, an enhanced parallel processing algorithm based on TOP-K (it is equal to selecting the k^th data from the ordered data) decomposition of hypercube model was proposed to evenly divide large-scale data in parallel processing. Experiment result shows that the proposed algorithm has some enhancement on time complexity, scalability and speedup in contrast with the parallel processing method based on hypercube model.

Keywords: parallel processing; TOP-K decomposition; hypercube model.

DOI: 10.1504/IJADS.2022.121557

International Journal of Applied Decision Sciences, 2022 Vol.15 No.2, pp.143 - 155

Received: 30 Jun 2020
Accepted: 01 Apr 2021
Published online: 18 Mar 2022 *

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