Search Results for author: Ryan Robinett

Found 3 papers, 0 papers with code

GraphChallenge.org Sparse Deep Neural Network Performance

no code implementations25 Mar 2020 Jeremy Kepner, Simon Alford, Vijay Gadepally, Michael Jones, Lauren Milechin, Albert Reuther, Ryan Robinett, Sid Samsi

The Sparse Deep Neural Network (DNN) Challenge draws upon prior challenges from machine learning, high performance computing, and visual analytics to create a challenge that is reflective of emerging sparse AI systems.

Sparse Deep Neural Network Graph Challenge

no code implementations2 Sep 2019 Jeremy Kepner, Simon Alford, Vijay Gadepally, Michael Jones, Lauren Milechin, Ryan Robinett, Sid Samsi

The Sparse DNN Challenge is based on a mathematically well-defined DNN inference computation and can be implemented in any programming environment.

Training Behavior of Sparse Neural Network Topologies

no code implementations30 Sep 2018 Simon Alford, Ryan Robinett, Lauren Milechin, Jeremy Kepner

We test pruning-based topologies, which are derived from an initially dense network whose connections are pruned, as well as RadiX-Nets, a class of network topologies with proven connectivity and sparsity properties.

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