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TASO: Time and Space Optimization for Memory-Constrained DNN Inference


May 21, 2020
Yuan Wen, Andrew Anderson, Valentin Radu, Michael F. P. O'Boyle, David Gregg


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Composition of Saliency Metrics for Channel Pruning with a Myopic Oracle


Apr 03, 2020
Kaveena Persand, Andrew Anderson, David Gregg


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Performance-Oriented Neural Architecture Search


Jan 09, 2020
Andrew Anderson, Jing Su, Rozenn Dahyot, David Gregg

* The 2019 International Conference on High Performance Computing & Simulation 

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A Taxonomy of Channel Pruning Signals in CNNs


Jun 11, 2019
Kaveena Persand, Andrew Anderson, David Gregg


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Explaining Reinforcement Learning to Mere Mortals: An Empirical Study


Mar 22, 2019
Andrew Anderson, Jonathan Dodge, Amrita Sadarangani, Zoe Juozapaitis, Evan Newman, Jed Irvine, Souti Chattopadhyay, Alan Fern, Margaret Burnett

* 7 pages 

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Optimal DNN Primitive Selection with Partitioned Boolean Quadratic Programming


Nov 02, 2018
Andrew Anderson, David Gregg


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Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks


Sep 27, 2018
Andrew Anderson, David Gregg


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Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks


Sep 22, 2018
Barbara Barabasz, Andrew Anderson, David Gregg


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Low-memory GEMM-based convolution algorithms for deep neural networks


Sep 08, 2017
Andrew Anderson, Aravind Vasudevan, Cormac Keane, David Gregg

* 13 pages, 16 figures and 3 tables. arXiv admin note: text overlap with arXiv:1704.04428 

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Parallel Multi Channel Convolution using General Matrix Multiplication


Jul 03, 2017
Aravind Vasudevan, Andrew Anderson, David Gregg

* Camera ready version to be published at ASAP 2017 - The 28th Annual IEEE International Conference on Application-specific Systems, Architectures and Processors. 6 pages 

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