By Topic

Efficient parallelizations of a competitive learning algorithm for text retrieval on the MasPar

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

3 Author(s)
Inien Syu ; Dept. of Comput. Sci., Central Florida Univ., Orlando, FL, USA ; Lang, S.D. ; Hua, K.A.

In this paper, we present parallel implementations of a connectionist model for text retrieval on the MasPar MP-1, an SIMD machine with up to 16 K processors. The connectionist model was originally developed on a SUN SparcStation 1+ for a sequential implementation. In our parallel implementations, we consider three strategies for mapping the network onto the MasPar: one-to-one, many-to-one, and one-to-many, depending on the ratio of the network size to the number of processors, in order to reduce the computation time. We also consider load balancing among processors for further improvement in performance. Our experimental results demonstrate noticeable speedups in our parallel implementations

Published in:

Frontiers of Massively Parallel Computation, 1995. Proceedings. Frontiers '95., Fifth Symposium on the

Date of Conference:

6-9 Feb 1995