44 citations · 87 across the 11 of their papers we have counts for
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cs.PF2018★ 2 cited
Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks
Andrew Anderson, David Gregg
Quantization of weights and activations in Deep Neural Networks (DNNs) is a powerful technique for network compression, and has enjoyed significant attention and success. However,…
math.NA2018
Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks
Barbara Barabasz, Andrew Anderson, Kirk M. Soodhalter +1
Popular deep neural networks (DNNs) spend the majority of their execution time computing convolutions. The Winograd family of algorithms can greatly reduce the number of arithmetic…