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Title: Implementing Recurrent Back Propagation on the Connection Machine. Final report

Technical Report ·
OSTI ID:6062943

Pineda's Recurrent Back-Propagation algorithm for neural networks was implemented on the Connection Machine, a massively parallel processor. Two fundamentally different graph architectures underlying the nets were tested - one based on arcs, the other on nodes. Confirming the predominance of communication over computation, performance measurements underscore the necessity to make connections the basic unit of representation. Comparisons between these graphs algorithms lead to important conclusions concerning the parallel implementation of neural nets in both software and hardware.

Research Organization:
Naval Research Lab., Washington, DC (USA)
OSTI ID:
6062943
Report Number(s):
AD-A-203796/8/XAB; NRL-9167
Country of Publication:
United States
Language:
English