no code implementations • 25 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.
no code implementations • 2 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.
no code implementations • 30 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.