Open Access Open Access  Restricted Access Subscription Access

Performance Evaluation of Parallel Bubble Sort Algorithm on Supercomputer IMAN1


Affiliations
1 Department of Computer Science, King Abdullah II School for Information Technology, The University of Jordan, Amman, Jordan
 

Parallel sorting algorithms order a set of elements USING MULTIPLE processors in order to enhance the performance of sequential sorting algorithms. In general, the performance of sorting algorithms are EVALUATED IN term of algorithm growth rate according to the input size. In this paper, the running time, parallel speedup and parallel efficiency OF PARALLEL bubble sort is evaluated and measured. Message Passing Interface (MPI) IS USED for implementing the parallel version of bubble sort and IMAN1 supercomputer is used to conduct the results. The evaluation results show that parallel bubble sort has better running time as the number of processors increases. On other hand, regarding parallel efficiency, parallel bubble sort algorithm is more efficient to be applied OVER SMALL number of processors.

Keywords

MPI, Parallel Bubble Sort, Parallel Efficiency, Speed Up.
User
Notifications
Font Size

  • A. I. Elnashar, (2011) “Parallel performance of mpi sorting algorithms on dual-core processor windows-based systems,” arXiv preprint arXiv:1105.6040.
  • M. Saadeh, H. Saadeh, and M. Qatawneh, “Performance evaluation of parallel sorting algorithms on iman1 supercomputer,” International Journal of Advanced Science and Technology, vol. 95, pp. 57–72, 2016.
  • M. Qatawneh, (2005) “Embedding linear array network into the tree-hypercube network,” European Journal of Scientific Research, vol. 10, no. 2, pp. 72–76.
  • N. Islam, M. S. Islam, M. Kashem, M. Islam, and M. Islam, (2009), “An empirical distributed matrix multiplication algorithm to reduce time complexity,” in Proceedings of the International Multi Conference of Engineers and Computer Scientists, vol. 2, pp. 18–20.
  • M. Qatawneh, (2011) “Multilayer hex-cells: a new class of hex-cell interconnection networks for massively parallel systems,” International journal of Communications, Network and System Sciences, vol. 4, no. 11, p.704.
  • M. Qatawneh, (2011) “Embedding binary tree and bus into hex-cell interconnection network,” Journal of American Sciences, vol. 7, no. 12, p. 0.
  • M. Qatawneh, (2016) “New efficient algorithm for mapping linear array into hex-cell network,” International Journal of Advanced Science and Technology, vol. 90, pp. 9–14.
  • M. Qatawneh, “Adaptive fault tolerant routing algorithm for tree hypercube multicomputer,” Journal of computer Science, vol. 2, no. 2, pp. 124–126, 2006.
  • M. Qatawneh, A. Alamoush ,J. Al Qatawneh, (2015) “Section Based Hex-Cell Routing Algorithm (SBHCR),” International Journal of Computer Networks &Communications, vol. 7, no. 1, p. 167.
  • M. Qatawneh and H. Khattab, (2015), “New routing algorithm for hex-cell network,” International Journal of Future Generation Communication and Networking, vol. 8, no. 2, pp. 295–306.
  • N. Sismanis, N. Pitsianis, and X. Sun, (2012), “Parallel search of k-nearestneighbors with synchronous operations,” in 2012 IEEE Conference onHigh Performance Extreme Computing. IEEE, 2012, pp. 1–6.
  • Mm. Jiang and D. Crookes. (2006), “High-performance 3D median filter architecture for medical image despeckling”. Electronics Letters. 2006. 42(24): p. 1379-1380.
  • Kale V, Solomonik E. (2010), “Parallel sorting pattern. In Proceedings of the 2010 Workshop on Parallel Programming Patterns. p. 10. ACM.
  • Pasetto D, Akhriev A. (2011) “A comparative study of parallel sort algorithms,”. In Proceedings of the ACM international conference companion on Object oriented programming systems languages and applications companion. p. 203-204. ACM.
  • M. Qatawneh, A. Sleit, W. Almobaideen. (2009), “Parallel Implementation of Polygon Clipping Using Transputer”. American Journal of Applied Sciences 6 (2): 214-218, 2009.
  • O. Surakhi, M. Qatawneh, H. Al ofeishat, (2017), “A Parallel Genetic Algorithm for Maximum Flow problem”. International Journal of Advanced Computer Science and Applications, Vol. 8, No. 6, 2017.
  • S. Hijazi and M. Qatawneh. (2017), “Study of Performance Evaluation of Binary Search on Merge Sorted Array Using Different Strategies”. International Journal of Modern Education and Computer Science, 12, 1-8.
  • O. AbuAlghanam, M. Qatawneh, H.al Ofeishat, O. adwan, A. Huneiti. (2017), “A New Parallel Matrix Multiplication Algorithm on Tree-Hypercube Network using IMAN1 Supercomputer”. International Journal of Advanced Computer Science and Applications, Vol. 8, No. 12, 2017.
  • M. Haj Qasem and M. Qatawneh, (2018), “Parallel matrix multiplication for business applications,” vol. 662, 01 pp. 24–36.
  • A. Bany Doumi and M. Qatawneh. PERFORMANCE EVALUATION OF PARALLEL INTERNATIONAL DATA ENCRYPTION ALGORITHM ON IMAN1 SUPER COMPUTER. International Journal of Network Security & Its Applications (IJNSA) Vol. 11, No.1, January 2019.
  • H. Harahsheh and M. Qatawneh. (2018), “Performance Evaluation of Twofish Algorithm on IMAN1 Supercomputer”. International Journal of Computer Applications, Vol. 179 (50).
  • A.Al-Shorman, M. Qatawneh. (2018), “Performance of Parallel RSA on IMAN1 Supercomputer”. International Journal of Computer Applications, Vol. 180 (37)
  • M. Asassfeh ,M. Qatawneh, F.AL-Azzeh. (2018), “PERFORMANCE EVALUATION OF BLOWFISH ALGORITHM ON SUPERCOMPUTER IMAN1”. International Journal of Computer Networks & Communications (IJCNC), Vol. 10 (2), 2018.
  • D. Purnomo, J. Marhaendro , A. Arinaldi, D. Priyantini, A. Wibisono, and A. Febrian. (2016), “mplementation of Serial and Parallel Bubble Sort on FPGA.” Jurnal Ilmu Komputer dan Informasi 9, no. 2: 113-120.
  • Azzam Sleit, Wesam Almobaideen, Mohammad Qatawneh, and Heba Saadeh. “Efficient processing for binary submatrix matching”. American Journal of Applied Science, Vol. 6(1), 2008.
  • Wesam Almobaideen, Mohammad Qatawneh, Azzam Sleit, Imad Salah and Saleh Al-Sharaeh. “Efficient Mapping Scheme of Ring Topology onto Tree-Hypercubes”. Journal of Applied Sciences 7(18), 2007.

Abstract Views: 251

PDF Views: 117




  • Performance Evaluation of Parallel Bubble Sort Algorithm on Supercomputer IMAN1

Abstract Views: 251  |  PDF Views: 117

Authors

Reem Saadeh
Department of Computer Science, King Abdullah II School for Information Technology, The University of Jordan, Amman, Jordan
Mohammad Qatawneh
Department of Computer Science, King Abdullah II School for Information Technology, The University of Jordan, Amman, Jordan

Abstract


Parallel sorting algorithms order a set of elements USING MULTIPLE processors in order to enhance the performance of sequential sorting algorithms. In general, the performance of sorting algorithms are EVALUATED IN term of algorithm growth rate according to the input size. In this paper, the running time, parallel speedup and parallel efficiency OF PARALLEL bubble sort is evaluated and measured. Message Passing Interface (MPI) IS USED for implementing the parallel version of bubble sort and IMAN1 supercomputer is used to conduct the results. The evaluation results show that parallel bubble sort has better running time as the number of processors increases. On other hand, regarding parallel efficiency, parallel bubble sort algorithm is more efficient to be applied OVER SMALL number of processors.

Keywords


MPI, Parallel Bubble Sort, Parallel Efficiency, Speed Up.

References