A new metric for self-organizing feature maps allows mapping of arbitrary parallel programs

Author

Meyer, Jürgen W.

Author_Institution

Tech. Inf. 2, Tech. Univ. Hamburg-Harburg, Germany

fYear

1993

fDate

8-11 Nov 1993

Firstpage

452

Lastpage

453

Abstract

A modification of Kohonen´s (1982) self-organizing feature maps offers solutions for a wide range of graph mapping problems. This is reached by replacing the Euclidian metric of the target space by a new metric. A sample implementation for mapping parallel programs onto processor networks demonstrates the properties of this method

Keywords

graph theory; multiprocessor interconnection networks; parallel programming; processor scheduling; programming theory; self-organising feature maps; software metrics; Euclidian metric; arbitrary parallel programs; graph mapping problems; processor networks; self-organizing feature maps; Computational modeling; Computer architecture; Concurrent computing; Iterative algorithms; Neurons; Parallel processing; Programming profession; Simulated annealing; Stochastic processes; Workstations;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence, 1993. TAI '93. Proceedings., Fifth International Conference on

Conference_Location

Boston, MA

ISSN

1063-6730

Print_ISBN

0-8186-4200-9

Type

conf

DOI

10.1109/TAI.1993.633998

Filename

633998

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1963252