By Topic

Highly latency tolerant Gaussian elimination

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Endo, T. ; Tokyo Univ., Japan ; Taura, K.

Large latencies over WAN will remain an obstacle to running communication intensive parallel applications on grid environments. This paper takes one of such applications, Gaussian elimination of dense matrices and describes a parallel algorithm that is highly tolerant to latencies. The key technique is a pivoting strategy called batched pivoting, which requires much less frequent synchronizations than other methods. Although it is one of relaxed pivoting methods that may select other pivots than the 'best' ones, we show that it achieves good numerical accuracy. Through experiments with random matrices of the sizes of 64 to 49,152, batched pivoting achieves comparable numerical accuracy to that of partial pivoting. We also evaluate parallel execution speed of our implementation and show that it is much more tolerant to latencies than partial pivoting.

Published in:

Grid Computing, 2005. The 6th IEEE/ACM International Workshop on

Date of Conference:

13-14 Nov. 2005