DocumentCode
1736231
Title
Assigning ADT modules with random neural networks
Author
Welch, Lonnie R. ; Stoyenko, Alexander D. ; Chen, Song
Author_Institution
Dept. of Comput. & Inf. Sci., New Jersey Inst. of Technol., Newark, NJ, USA
fYear
1993
Firstpage
546
Abstract
The authors apply random neural networks to the problem of assigning abstract data type modules (ADTs) to the processing elements of parallel computers. Although assignment of tasks has been discussed extensively in the literature, the automatic assignment of ADTs is a relatively new problem, and therefore they describe the problem in detail. This is followed by an introduction to the random neural network model and a presentation of the neural network solution to the assignment problem. Experimental results are presented comparing the solution to those obtained with random assignment and with a greedy heuristic. The random neural network is found to give significantly better results than the other two approaches in virtually every case
Keywords
abstract data types; neural nets; abstract data type modules; processing elements; random neural networks; Computer networks; Concurrent computing; Costs; Data structures; Distributed computing; Information science; Laboratories; Neural networks; Parallel processing; Recurrent neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
System Sciences, 1993, Proceeding of the Twenty-Sixth Hawaii International Conference on
Conference_Location
Wailea, HI
Print_ISBN
0-8186-3230-5
Type
conf
DOI
10.1109/HICSS.1993.284071
Filename
284071
Link To Document