Search Results for author: Sam Webster

Found 4 papers, 1 papers with code

Confidential Machine Learning within Graphcore IPUs

no code implementations18 May 2022 Kapil Vaswani, Stavros Volos, Cédric Fournet, Antonio Nino Diaz, Ken Gordon, Balaji Vembu, Sam Webster, David Chisnall, Saurabh Kulkarni, Graham Cunningham, Richard Osborne, Dan Wilkinson

We present IPU Trusted Extensions (ITX), a set of experimental hardware extensions that enable trusted execution environments in Graphcore's AI accelerators.

BIG-bench Machine Learning

Alexandria: Unsupervised High-Precision Knowledge Base Construction using a Probabilistic Program

no code implementations AKBC 2019 John Winn, John Guiver, Sam Webster, Yordan Zaykov, Martin Kukla, Dany Fabian

The use of a probabilistic program allows uncertainty in the text to be propagated through to the retrieved facts, which increases accuracy and helps merge facts from multiple sources.

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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