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

Author

Gupta, S.N. ; Zubair, M. ; Grosch, C.E.

Author_Institution

Dept. of Comput. Sci., Old Dominion Univ., Norfolk, VA, USA

fYear

1990

fDate

8-10 Oct 1990

Firstpage

376

Lastpage

379

Abstract

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

Keywords

neural nets; parallel algorithms; virtual machines; DAP-510; SIMD; TSP; Traveling Salesman Problem; massively parallel computer; modified Hopfield-Tank; neural networks; sparse matrix techniques; Cities and towns; Computational modeling; Computer networks; Computer simulation; Concurrent computing; Differential equations; Neural networks; Neurons; Sparse matrices; Traveling salesman problems;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

College Park, MD

Print_ISBN

0-8186-2053-6

Type

conf

DOI

10.1109/FMPC.1990.89486

Filename

89486

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2772236