By Topic

Pairwise reduction for the direct, parallel solution of sparse, unsymmetric sets of linear equations

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)
Davis, T.A. ; Center for Supercomput. Res. & Dev., Illinois Univ., Urbana, IL, USA ; Davidson, E.S.

A paradigm for concurrent computing is explored in which a group of autonomous, asynchronous processes shares a common memory space and cooperates to solve a single problem. The processes synchronize with only a few others at a time; barrier synchronization is not permitted except at the beginning and end of the computation. The paradigm maps directly to a shared-memory multiprocessor with efficient synchronization primitives and is applied to the solution of a large, sparse system of linear equations. The algorithm, called pairwise solve (or PSolve), is presented with several variants to address some of the limitations of previous algorithms. On the Alliant FX/8, PSolve is faster than Gaussian elimination and two common sparse matrix algorithms

Published in:

Computers, IEEE Transactions on  (Volume:37 ,  Issue: 12 )