Search Results for author: Maik Riechert

Found 2 papers, 1 papers with code

AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks

1 code implementation ICLR 2018 Alexander L. Gaunt, Matthew A. Johnson, Maik Riechert, Daniel Tarlow, Ryota Tomioka, Dimitrios Vytiniotis, Sam Webster

Through an implementation on multi-core CPUs, we show that AMP training converges to the same accuracy as conventional synchronous training algorithms in a similar number of epochs, but utilizes the available hardware more efficiently even for small minibatch sizes, resulting in significantly shorter overall training times.

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