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Neural network simulation at Warp speed : how we got 17 million connections per second

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journal contribution
posted on 01.01.1998, 00:00 by Dean A. Pomerleau, Artificial Intelligence and Psychology Project.
Abstract: "We describe a fast-propagation algorithm for a linear array of processors. Results of an implementation of this algorithm on Warp, a ten processor, programmable systolic array computer, are reviewed and compared with back-propagation implementations on other machines. Our current Warp simulator is about 8 times faster at simulating the NETtalk text-to-speech network than the fastest back-propagation simulator reported in the literature. This fast simulator on Warp is being used routinely in a road recognition experiment for robot navigation at Carnegie Mellon. Our results indicate that linear systolic array machines can be efficient neural network simulators. Planned extensions and improvements to our current algorithm are discussed."