Title :
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
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;
Conference_Titel :
Tools with Artificial Intelligence, 1993. TAI '93. Proceedings., Fifth International Conference on
Conference_Location :
Boston, MA
Print_ISBN :
0-8186-4200-9
DOI :
10.1109/TAI.1993.633998
