76 citations · 107 across the 3 of their papers we have counts for
3 papers
cs.LG2024
On the Efficiency of Convolutional Neural Networks
Andrew Lavin
Since the breakthrough performance of AlexNet in 2012, convolutional neural networks (convnets) have grown into extremely powerful vision models. Deep learning researchers have use…
cs.NE2015★ 76 cited
Fast Algorithms for Convolutional Neural Networks
Andrew Lavin, Scott Gray
Deep convolutional neural networks take GPU days of compute time to train on large data sets. Pedestrian detection for self driving cars requires very low latency. Image recognitio…
cs.NE2015★ 31 cited
maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs
Andrew Lavin
This paper describes maxDNN, a computationally efficient convolution kernel for deep learning with the NVIDIA Maxwell GPU. maxDNN reaches 96.3% computational efficiency on typical…