By Topic

Simulation of neural networks on a massively parallel computer (DAP-510) using sparse matrix techniques

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)
Gupta, S.N. ; Dept. of Comput. Sci., Old Dominion Univ., Norfolk, VA, USA ; Zubair, M. ; Grosch, C.E.

A parallel sparse matrix algorithm is proposed for the simulation of the modified Hopfield-Tank (MHT) network for solving the Traveling Salesman Problem (TSP). The MHT network using this sparse matrix algorithm has been implemented on a DAP-510, a massively parallel SIMD (single-instruction-steam, multiple-data-stream) computer consisting of 1024 processors. Problems of various sizes, ranging from eight cities up to 256 cities, have been simulated. The results show a very large speedup for the algorithm as compared with one using a standard dense matrix implementation

Published in:

Frontiers of Massively Parallel Computation, 1990. Proceedings., 3rd Symposium on the

Date of Conference:

8-10 Oct 1990