Parallel Matrix Sort Using MPI and CUDA

Priyanka Ojha, Pratibha Singh, Gopalakrishna N. Kini, B. Ashwath Rao, Shwetha Rai

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Sorted data is essential. Apart from information presentation or manual retrieval of information, sorted data is beneficial even when using machines’ computational power. In many science and engineering fields, the sorting of extensive dataset is essential in matrix form. Matrix sort is an algorithm, which can sort a large amount of data in matrix form efficiently. In this paper, parallel algorithms are developed for the Matrix Sort algorithm (designed by S. Kavitha et al. Int J Comput Appl 143(9):1–6, 2016) [1]. This algorithm sorts the matrix rows and columns in parallel, subsequently applying the further procedure on resultant data. The implementations of parallel algorithms have been discussed by comparing the execution time results obtained in sequential and parallel form.

Original languageEnglish
Title of host publicationCommunication and Intelligent Systems - Proceedings of ICCIS 2020
EditorsHarish Sharma, Mukesh Kumar Gupta, G. S. Tomar, Wang Lipo
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages9
ISBN (Print)9789811610882
Publication statusPublished - 2021
Event2nd International Conference on Communication and Intelligent Systems, ICCIS 2020 - Virtual, Online
Duration: 26-12-202027-12-2020

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


Conference2nd International Conference on Communication and Intelligent Systems, ICCIS 2020
CityVirtual, Online

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications


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