Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Parallel Implementation of Back-Propagation Algorithm in Networks of Workstations
IEEE Transactions on Parallel and Distributed Systems
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An analytical model is presented for assessing the performance of multilayer neuralnetworks implemented in linear arrays. Metrics to assess latency, throughput rate, andcomputational and input-output bandwidth are developed. These metrics demonstrate arich and complex interaction between the performance of the hardware and the numberand relative dimensions of the layers in a network. Practical illustration of the use ofthese metrics is demonstrated for a two-hidden-layer network.