This paper examines implementations of a multi-layer perceptron (MLP) on bus-based shared memory (SM) and on distributed memory (DM) multiprocessor systems. The goal has been to optimize HW and SW architectures in order to obtain the fastest response possible. Prototyping parallel MLP algorithms for up to 8 processing nodes with the DM as well as SM memory was done using CSP-based TRANSIM tool. The results of prototyping MLPs of different sizes on various number of processing nodes demonstrate the feasible speedups, efficiency and time responses for the given CPU speed, link speed or bus bandwidth.
Index Terms:
Performance modeling/prediction, prototyping parallel programs, parallel implementations of neural networks
Citation:
Vaclav Dvorak, Rudolf Cejka, "A Choice of SM/DM Parallel ANN Implementation for Embedded Applications," ecbs, pp.18, 7th IEEE International Conference and Workshop on the Engineering of Computer Based Systems, 2000