arrow
Volume 14, Issue 4
Analysing the Efficiency of Solving Dense Linear Equations on Dawning1000

X. B. Chi

J. Comp. Math., 14 (1996), pp. 383-386.

Published online: 1996-08

Export citation
  • Abstract

In this paper, we consider solving dense linear equations on Dawning1000 by using matrix partitioning technique. Based on this partitioning of matrix, we give a parallel block LU decomposition method. The efficiency of solving linear equations by different ways is analysed. The numerical results are given on Dawning1000. By running our parallel program, the best speed up on 32 processors is over 25.

  • Keywords

  • AMS Subject Headings

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{JCM-14-383, author = {}, title = {Analysing the Efficiency of Solving Dense Linear Equations on Dawning1000}, journal = {Journal of Computational Mathematics}, year = {1996}, volume = {14}, number = {4}, pages = {383--386}, abstract = {

In this paper, we consider solving dense linear equations on Dawning1000 by using matrix partitioning technique. Based on this partitioning of matrix, we give a parallel block LU decomposition method. The efficiency of solving linear equations by different ways is analysed. The numerical results are given on Dawning1000. By running our parallel program, the best speed up on 32 processors is over 25.

}, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/9246.html} }
TY - JOUR T1 - Analysing the Efficiency of Solving Dense Linear Equations on Dawning1000 JO - Journal of Computational Mathematics VL - 4 SP - 383 EP - 386 PY - 1996 DA - 1996/08 SN - 14 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/9246.html KW - AB -

In this paper, we consider solving dense linear equations on Dawning1000 by using matrix partitioning technique. Based on this partitioning of matrix, we give a parallel block LU decomposition method. The efficiency of solving linear equations by different ways is analysed. The numerical results are given on Dawning1000. By running our parallel program, the best speed up on 32 processors is over 25.

X. B. Chi. (1970). Analysing the Efficiency of Solving Dense Linear Equations on Dawning1000. Journal of Computational Mathematics. 14 (4). 383-386. doi:
Copy to clipboard
The citation has been copied to your clipboard